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BLS E conom ic G row th
[M3@ System Used fo r
d]®Q
P rojections to 1990
U.S Department of Labor
Bureau of Labor Statistics
April 1982
Bulletin 2112




A

3 -'

BLS Econom ic Growth
Model System Used for
Projections I© 1990
U.S. Department of Labor
Raymond J. Donovan, Secretary
Bureau of Labor Statistics
Janet L. Norwood, Commissioner
April 1982
Bulletin 2112




For sale by fhe Supertendent of Documents, U.S. Government Printing Office
Washington, D.C. 20402 - Price $5.50




Preface

This bulletin describes the Bureau of Labor Statistics
current Economic Growth model which was used to
develop the revised 1990 industry and occupational em­
ployment projections. It is intended primarily for those
analysts who desire detailed information on the BLS
projection methods, models, and techniques. The text
covers the components of the Economic Growth sys­
tem used to develop these projections in the sequence
of their application. The appendixes provide the de­
tailed equations used in the various model systems.
The revised 1990 employment projections, based
upon changed economic conditions and later data, were
published in the August 1981 Monthly Labor Review..
The results of the earlier version of the 1990 projec­
tions were presented in three articles published in the
Monthly Labor Review in December 1978 and April
1979.
Earlier projections of industry and occupational em­
ployment for 1970, 1975, 1980, and 1985 are cited in
the text. Industry employment projections are used as
a basis for the occupational projections developed in
the last part of the projections cycle. The occupation­
al projections are used in planning training programs
and in counseling students and workers and by busi­
nesses for personnel planning and market research. The




industry projections 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 Econom­
ic Growth and Employment Projections, under the su­
pervision of Ronald E. Kutscher, Assistant Commis­
sioner for Economic Growth and Employment Projec­
tions. The report was prepared by Richard Oliver.
Howard Fullerton provided the explanation of labor
force projections. Norman C. Saunders contributed the
methodology on the macroeconomic projections. Ma­
terial on the techniques of projecting interindustry co­
efficients was provided by Karen Horowitz. Method­
ologies used in projecting the major final demand sec­
tors were provided by Arthur Andreassen, Betty Su,
and David Frank. Valerie Personick developed the es­
timates of industry employment. Neal Rosenthal pre­
pared the section on occupational methodology and
John Tschetter the section on areas of new develop­
ment. Marilyn Queen assisted in the preparation of the
manuscript.
Material in this publication is in the public domain
and may, with appropriate credit, be reproduced with­
out permission.




Page
Chapter 1. BLS projections system ...................................................
1
Current methodology........................................................................................................ 1
Chart 1. Employment projections system .......................................................

3

Chapter 2. Aggregate labor force projections ..........................
4
Assumptions ..........................................................................................................
4
Data sources.......................................................................................................................4
Projecting labor force p attern s..............................
4
Population projections .................................................................................................... 6
Projection of the total and civilian labor force ................................................................6
Interpreting the projections.............................................................................................. 7
Chapter 3. Aggregate economic projections........................................................................... 8
Assumptions of the macro projections......................
8
10
Supply G N P .........................................
Income flow s........... ........................................................................................................11
Demand GNP ..................................................................................................................12
Price/wage se c to r................................ ..........................................................................13
Balancing the macro m o d e l......................
13
Solving the macro model ....................................................................
.13
Chapter 4. Final demand projections.............................................................
14
Assumptions ..........................
14
Personal consumption expenditures..............................
15
Gross private domestic investm ent................................................................................. 17
Foreign tra d e .............................................................................................
18
State and local government.............................................................................................20
Federal Government..................................
21
Chapters. Intermediate demand projections........................................................................22
Changes from earlier BEA studies..................................................................
22
Secondary products................................................................................
22
Valuation of transactions................................................................................................ 23
Projecting coefficients .................................................................................................... 23
Chapter 6. Industry output and employment projections.................................................... 24
Factor demand model............................................
24
Solving the m o d e l....................
25
Disaggregation of results ................................................................................................ 26




v

Contents—Continued
Page
Chapter 7. Occupational employment projections...............................................................27
Developing base year employment estimates and projections ...................................... 27
Wage and salary workers in OES survey industries....................................................... 27
Difficulties encountered using the OES survey ..............................................................28
Projecting the ratios in OES survey industries.............................. ..............................29
Wage and salary workers, non-OES survey industries ..................................................29
Projecting the ratios ............................... ........................... .......... ...............................29
Self-employed and unpaid family workers..................................
30
Total occupational employment ...................................................
.30
Chapter 8. Planned changes in the projection system ......................................................... 31
Labor force supply model................................................................................................ 31
Industry-occupational employment ............................................................................... 31
* Job openings ........................................................................................
31
Evaluation of projections................................................................................................ 32
Appendixes:
A. Labor force projection scenarios...............................................................................33
B. Macroeconomic model: Equations, identities, and variables......................
35
C. Personal consumption model: Variables and equations...........................................47
D. Federal Government equations.................................................................................80
E. Labor demand equations...........................................................................................82
F. Economic Growth sectoring plan................................................................................91
G. Occupations included in the industry-occupational model....................................... 95
H. Industries included in the industry-occupational model......................................... 102
I. Data sources...............
107




vi

Chapter 1. EBLS Pr@|e©ti©ins

System

productivity, hours, and employment at the industry
level of detail; and (7) the projection of an industry-oc­
cupational matrix used to project occupational employ­
ment levels.
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 com­
puterized feedback from a later step to an earlier one.
However, results at certain stages are compared ana­
lytically with earlier controls, and adjustments are made.

The revised 1990 employment projections are the
latest in a seiies that started in the mid-1960’s as an
interagency project to study the conditions and require­
ments for balanced economic growth in the United
States. The first Economic Growth model, formulated
in 1963 for the 1970 projections, was a conventional
application of the input-output technique using only one
other model. Since that time, projection studies have
been completed for 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, other models, more
rigorous analytical techniques, a more automatic sys­
tem for processing calculations, and broader coverage
including labor force and occupational projections in
the current version. The interagency character of the
projections has also changed. Although certain data as­
sumptions are still coordinated with other agencies, the
projections have become more a b l s responsibility.

Brief overview o f Economic Growth system. The revised
employment projections, using this current methodol­
ogy, began with an estimate of the size of the aggre­
gate labor force available in 1990. To cover a range of
uncertainties, three alternative scenarios were prepared:
A high, low, and middle estimate of the projected la­
bor force. Population projections prepared by the Bu­
reau of the Census for various age, sex, and racial groups
were used as a basis for the labor force supply estimates.
Labor force participation rates for each group were
projected by extrapolating past growth rates. Different
base periods were used in the regression for each age
group to provide the basis for the different alternatives.
The total labor force was calculated for each group by
multiplying the projected participation ratios by the
census projections of population in each group. These
projections were used as an input to the macroeconomic
model projections. The high-trend I version of eco­
nomic growth used the high labor force alternative.
The low-trend version of economic growth and the
high-trend II version used the middle-level labor force
estimate.
Next, a set of assumptions, or scenarios, describing
alternative conditions of growth in the economy were
developed. Various assumptions, such as policy targets,
were formulated and used in conjunction with the
macroeconometric model, along with base period data.
This model used these assumptions to develop consis­
tent projections of supply or potential g n p growth
and the resulting income flows. Income flows were next
used by the model in projecting demand g n p by ma­
jor components. Supply and demand g n p were bal­
anced in the model providing control totals for the pur­
chases of various final demand sectors consistent with
all conditions and assumptions.

Current methodology

In the current version of the BLS Economic Growth
system, two functions were made a formal part of the
Economic Growth model system: The aggregate labor
force projections and the projection of occupational
employment levels. There are currently seven major
steps in projecting employment levels: (1) A projection
of labor force supply; (2) a macro model projection of
the aggregate economy; (3) a disaggregation of gross
national product to detailed demand categories; (4) a
distribution of each demand category to producing in­
dustries; (5) projection of an input-output table and its
use in solving for industry outputs; (6) a projection of
1 ploym ent Projections f o r the 1980’s, Bulletin 2030 (Bureau of
Em
Labor Statistics, 1979). Occupational Projections and Training Data,
1980 Edition, Bulletin 2052 (Bureau of Labor Statistics, 1980).
“ Revised BLS Projections to 1980 and 1985,” M onthly Labor
Review, March, August, and November 1976 and “ Revised Occupa­
tional Projections to 1985,” M onthly Labor Review, November 1976.
The following Bureau o f Labor Statistics bulletins: Occupational P ro­
jections and Training Data, Bulletin 2020 (1979); The Structure o f the
U.S. Econom y in 1980 and 1985, Bulletin 1831 (1975); The U.S.
Econom y in 1985, Bulletin 1733 (1974); Projections o f the PostVietnam Economy, 1975, Bulletin 1733 (1972); The U.S. Economy in
1980, Bulletin 1673 (1970); Patterns o f U.S. Economic Growth,
Bulletin 1672 (1970); and Projections 1970: Interindustry Relation­
ships, Potential Dem and and Employment, Bulletin 1536 (1966).




1

The industry employment projections were used for
calculating the occupational employment levels. The
method incorporated an industry-occupational model
to distribute industry employment levels to various oc­
cupations. This projection method involved first devel­
oping the occupational staffing patterns for each indus­
try in a current period (1978). These patterns were pro­
jected to 1990 based upon past experience and various
analyses. The projected employment levels in each in­
dustry were multiplied by the occupational distribution
for the industry. Summing across industries provided
an estimate of the total projected employment in each
occupation consistent with the industry projections.
An outline of the various analytical stages of the pro­
jections is given below. Chart 1 shows the computa­
tional blocks of the system.

Control totals for each of the categories of demand
GNP developed in the macro model were used with
various techniques and submodels to distribute aggre­
gate demand to detailed categories of demand or prod­
uct groups. For example, personal consumption ex­
penditures for nondurable goods were distributed to
various product groups, such as food purchased for use
at home, while investment in producers’ durable equip­
ment was distributed by producing industry; i.e., com­
puters or metalworking machinery.
The next step was to distribute the functional or prod­
uct level demand in each sector to specific purchases
of goods and services produced by 156 different indus­
try demand sectors using projected distribution factors
or “bridge” tables. The industry classification in this
sequence of the model is always consistent with the in­
terindustry models used in subsequent steps to project
intermediate demand. The coefficients of the input-out­
put models were projected separately based upon such
factors as expected changes in industry technology,
shifts in inputs, and changes in the mix of products.
These projected ratios provided the framework for esti­
mating the purchases each industry must make to sup­
port its projected sales. The projected interindustry ta­
bles, or matrices, provided estimates of the projected
output needed from each industry for all final and in­
termediate demand requirements. At this stage in the
model sequence, each industry’s output level was evalu­
ated 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 varied significantly from past experi­
ence, the reasons were reexamined and changes made
in the final demand purchases or coefficients where
necessary.
The projections sequence in the BLS Economic
Growth model system then proceeded to estimate in­
dustry employment requirements. A labor demand
model was used to project productivity changes in each
industry. With the industry productivity projections,
industry output requirements were converted to indus­
try employment requirements. Finally, the industry em­
ployment changes were compared to historical change.
If the growth in employment appeared reasonable, it
was aggregated and compared with levels used at the
macro stage. At all steps in this process, the disaggre­
gated estimates were made consistent with their macro
counterparts.




A. Labor force projections
1. Project labor participation rates
2. Apply rates to population projections
3. Calculate labor force size
B. Macroeconomic projections
1. Policy inputs
2. Potential g n p
3. Income flows
4. Demand sectors
C. Final demand purchases
1. Functional levels
2. Industry purchases
D. Interindustry tables
1. Base period tables
2. Coefficient projections
3. Projected tables
E. Projected industry outputs
1. Calculation of gross outputs
2. Evaluation and feedback
F. Projected industry employment
1. Productivity changes
2. Labor demand
3. Evaluation and feedback
G. Projected occupational employment
1. Industry occupational staffing patterns
2. Total employment by occupation

2

Chart 1: Employment Projections System




3

Chapter 2„ Aggregate Labor
F@
re@ Projdetions

tained a series consisting of the ratio of the annual aver­
age total labor force to the July 1 total population, in­
cluding Armed Forces overseas. The published annual
average labor force series is the ratio of the annual aver­
age labor force to the annual average population with
those in institutions removed. The total labor force
series used in projecting the labor force, although not
published, is available upon request. The civilian labor
force series is published in the January issue of Employ­
ment and Earnings.

To project the labor force, the proportion of the pop­
ulation in the labor force (labor force participation rate)
was projected and multiplied by the projected popula­
tion. The population projections used were prepared by
the Bureau of the Census. The projections of the per­
cent of the population expected to be in the labor force
were prepared by BLS; this involved projections of
changes in labor force participation rates. The popula­
tion was grouped by age, sex, and race and then the par­
ticipation rates were projected for each group. This re­
sulted in 54 groups which were projected using a regres­
sion approach. These projected groups were combined
into the aggregate labor force projections and used as
input to the macro model system. The high-trend ver­
sion of economic growth used the high labor force
growth alternative. The medium alternative for labor
force growth was incorporated in the other two ver­
sions.

Projecting labor force patterns

Three possible growth scenarios for labor force par­
ticipation rates were projected for each age, sex, and
racial group based on past growth rates. (Details of the
three scenarios are summarized in appendix A.)
Middle-growth pattern. For white male youths (16 to
24), using labor force participation rates observed over
a short period yielded a high rate of growth, while using
the estimates measured over a longer period yielded a
low rate of growth. The middle-growth rate was a
weighted combination of the high and low patterns:

A ssum p tion s

In the time horizon used (to the year 2000), it was as­
sumed that work patterns would not change significant­
ly. For example, the labor force participation rate of
women generally would not exceed that of men the same
age; similiarly, a sharply reduced workweek would not
become the standard full-time workweek. There would
be no major wars or great social disturbances. Finally,
there would be no substantial changes in prevailing defi­
nitions of labor force, employment, and unemploy­
ment.2

(1) middle rate = b' (high rate.) + (1 - b1 (low
)
rate.) where b = 0.90 i, and i is the number of
years since 1979.
The general pattern observed in labor force participa­
tion has been increasing rates of change, whether up or
down, with few changes in the sign of the growth rates.
Mature (25 to 54) white men exhibited this pattern.
Thus, this rate of change measured over the 1960 to
1979 period showed a slower rate of decrease than the
rate measured over the 1972 to 1979 period; for the mid­
dle-growth alternative, the rate from the longer interval
was used. The amount of change, r, for each projection
was decreased exponentially according to the following
equation:

Data sou rces

Since the Bureau of the Census projects a population
series known as “ total population including Armed
Forces overseas,” it was necessary to maintain a series
for this base. The Bureau of Labor Statistics has main­
2A Commission on Employment and Unemployment Statistics
recommended no changes in difinitions o f the basic labor force con­
cepts when it reported in the fall of 1979. See National Commission on
Employment and Unemployment Statistics, Counting the L abor
Force, Washington, 1979. The last revision of definitions was im­
plemented in 1967. See Robert L. Stein, “ New Definitions for
Employment and Unemployment,” Em ploym ent and Earnings,
February 1967, pp. 1-25. The Current Population Survey design was
modified in January 1973 to reflect the 1970 census and was expanded
in January 1978.




(2) r = r0 [552 - i2 + i]/552
where i is the number of years since 1979, and r0
is the rate of change estimated over the historic
period. The number 552 is derived from n2 + n,
where n = 24. n is set so that it is beyond the
projection period.

4

the black total labor force ratio equal to the comparable
high white male ratio in the year 2000. The path is ex­
pressed by the two equations:

Different middle-growth path scenarios were devel­
oped for two age groups of black-and-other men
younger than retirement age; those 16 to 24, and those
25 to 59. Because of the higher sampling variability ob­
served in the total labor force rates at this level of disag­
gregation, the short-term labor force rate of change es­
timates were discarded for men 16 to 24. The moder­
ate-growth pattern was based on the upper confi­
dence-interval estimate of change measured over the
long run for young black-and-other men. For men 25
to 59, the middle-growth rate pattern was based on the
rate of change measured over the short run. Once a
growth rate was estimated, it was projected according to
equation (2).
For the middle-growth scenario, women of both
racial groups under 65 years of age were divided into
three age groups, 16 to 19, 20 to 44, and 45 to 64. The
rate of growth was measured over the recent past for
women ages 16 to 44 and was measured over the longer
period for women ages 45 to 64. For women 20 to 44,
the rate of growth was projected to increase at an in­
creasing rate for 3 years, then to increase at a decreasing
rate according to an adjusted version of equation (2).
The divisor in equation (2) was changed so that the rate
of growth became zero in 1995; then between 1995 and
2000, the labor force rate grew by a percentage point.
For women 45 to 64, equation (2) was used unchanged,
which implied that the rate of growth would continue to
change until 2000. In no scenario was the labor force
participation rate for women allowed to exceed the rate
attained in 2000 by men of the same age and ethnic
group.
The same three retirement age scenarios (65 and over
for women, 60 and over for black-and-other men, 55
and over for white men) were used for all racial and sex
groups. The middle-growth scenario used the long-run
rate, r, which was divided by two before being exponen­
tially decreased according to equation (2).

(3) r = [log(black Ifpr 1979) - log(white lfpr
2000)]/21 and then
using:
(4) ro = (black lfpr 1979) exp [r (i)]
where i is the number of years since 1979, and
lfpr is the labor force participation rate.
For the high-growth scenario, women of both racial
groups under 65 years of age were divided into three age
groups, 16 to 19, 20 to 44, and 45 to 64. For women 20
to 44, it was assumed that the growth measured over the
shorter term would continue to increase at an increasing
rate for 5 years, while for women 16 to 19 and 45 to 64,
growth was projected to accelerate for only 3 years.
After that, the growth rates were projected to increase
at a decreasing rate according to an adjusted version of
equation (2). The divisor in equation (2) was changed so
that the rate of growth would become zero in 1995; be­
tween 1995 and 2000, the labor force rate grew slightly,
by 1 percentage point. The effect was to have a more
rapid increase in the short run than the middle-growth
scenario.
The high labor force growth scenario for those at the
retirement ages was the same for all sex-ethnic groups.
It reflects, at least implicity, the assumption that recent
legislation and high inflation will stop the pattern of de­
clining labor force participation. The rate of decrease
was held at zero or the participation rate was set to hold
constant over the entire 1980 to 2000 period.
Low-growth pattern. For white male youths, using
labor force participation rates observed over the long
range provided a low rate of growth, as the rate of
change measured over the 1958-77 period yielded the
lower rate of growth. The rate of change for prime-age
white men as measured over the 1958-77 period showed
a slower rate of decrease than the rate measured over the
1970-77 period. For the low-growth alternative, the de­
creasing pattern since 1970 was projected. The amount
of change, r, for each was estimated according to equa­
tion (2). For black-and-other men, ages 16 to 64, the
low alternative projection was based on the change mea­
sured over the long run, with the rate of change de­
creasing according to equation (2).
For women 16 to 19, the rates from the long-run esti­
mates were used, while for women 20 to 64, the rates
from the short-run estimates were used. For both
groups, the lower estimate of labor force growth
(smallest increase or greatest decrease) was used to make
the projection. The rate of change was then projected
according to equation (2).
For the low-growth retirement age projection, which
was made in the same way for all sex-ethnic groups, the

High-growth pattern. For white youths (16 to 24), the
labor force participation rates observed over a short pe­
riod yielded the high rate of growth. They were pro­
jected according to equation (2). The rate of change in
participation of white men 25 to 64 measured over the
1960 to 1979 period showed a slower rate of decrease
than the rate measured over the 1972 to 1979 period.
For the upper growth rate alternative, the assumption
was made that labor force participation for the age
group 25 to 39 would increase at the same rate it had de­
clined over the 1960-79 period; for men 40 to 64, the
rate of change was set at zero, continuing the last ob­
served labor force participation rate. The amount of
change, r, for each projection was decreased exponen­
tially according to equation (2).
The high-growth scenario for black-and-other men
ages 16 to 64 was that rate of change which would make



5

rates of change were measured over the short term with
its more rapid rate of decrease. For all of these older age
groups, the labor force rate was kept above 1.2 percent.

The Bureau of the Census Series II population projec­
tion was used for the labor force projections. Series II
projects an ultimate fertility rate of 2.1 children per
women. The current rate of fertility is following the
Series II projection well, because the Bureau of the Cen­
sus projected the fertility rate to drop to below replace­
ment levels before rising in the 1980’s. Although there is
nothing to indicate that the fertility rate will return to
replacement levels in this century, it should be above the
Series III level. The selection of a population projection
series makes no difference in the labor force projection
until after 1992.
Two population estimates were made concurrently
with the new round of labor force projections: The civil­
ian noninstitutional population, and the total noninstitutional population. The projection of the civilian non­
institutional population was made in two steps: Estima­
tion of the noninstitutional population, and removal of
the Armed Forces. The total noninstitutional popula­
tion has only the institutional population removed.
The civilian noninstitutional population for each age
group, 16 and 17, 18 and 19, 20 to 24, 25 to 29, 70 to 74,
75 and over, was calculated using the ratios of the total
noninstitutional population to the total population pub­
lished with the population estimates.4 After this, the
Armed Forces were subtracted.

P@pylati©p prom otions

Although the emphasis in the presentation of these
projections was on labor force participation rates, some
discussion of population projections is necessary, as
they affect the levels of the projected labor force.3 There
are three elements to a population projection: Future
births, future deaths, and future migration. The Bureau
of the Census projects birth and survival rates but only
the level of net migration . Evaluating the effect of these
in reverse order, data on emigration have not been col­
lected for more than a decade because of their dubious
accuracy. Although documented immigrants presum­
ably are counted accurately, if they then leave, they are
not necessarily counted. Further, most conjectures
about the number of undocumented workers put their
level above that of legal net migration. However, it is
necessary to distinguish between a net flow of 400,C X
K)
migrants and the conjectured stock of 1.5 to 6 million il­
legal migrants. Although most migrants are of working
age, the labor force projections should be affected only
if the assumptions are off by a factor of 2. It may be
quite difficult to do appreciably better than the Bureau
of the Census assumption of 400,000 net migrants per
year.
Mortality assumptions allow for a small decrease be­
tween now and the year 2050. Given the sudden and un­
expected decrease in mortality rates recently, this as­
sumption looks quite conservative. However, the effects
of this will be upon the older population, who have low
and declining labor force participation rates.
Of the three elements in a population projection, the
Bureau of the Census has prepared alternatives only for
level of fertility. These alternatives vary according to the
ultimate level of fertility that will be attained. The cen­
tral population projection, Series II, embodies an as­
sumption that, ultimately, fertility will be at replace­
ment levels so that the native-born population will not
increase in size (starting about the year 2050). The upper
population projection, Series I, reflects the pattern that
would occur if fertility returned to the high levels of the
early sixties; the low population projection, Series III,
presents a pattern that leads to a falling population in
the next century. By 1995, the size of the younger labor
force would be affected by these scenarios, but before
then, fertility paths only enter the model as they affect
women’s labor force participation. Since mothers of
young children have been increasing their labor force
participation, different patterns of fertility change
should make less and less difference as time passes.

The total labor force was calculated by multiplying
the projected total labor force participation ratios by
the Series II population projection; the civilian labor
force was projected by subtracting the Armed Forces
from the total labor force. Two more labor force rates
were calculated: The ratio of the civilian labor force to
the projected civilian noninstitutional population, the
civilian labor force participation rate; and the ratio of
the total labor force to the total noninstitutional popu­
lation, the total labor force participation rate. Since the
labor force participation rates as published for survey
data are the ratio of the annual average labor force to
the annual population (always with the institutional
population removed), the rates were not strictly com­
parable to the historical data.
At the time the projections were prepared, the goal of
the Department of Defense for 1985 was an active duty
force of 2,061,000 people: 254,000 women and
1,807,000 men in the Armed Forces by 1985. In order to
make the projections consistent with Current Popula­
tion Survey estimates, it was necessary to include the
Coast Guard and reserves on active duty for less than 6
months. To make the labor force projections, it was
necessary to have an age-race distribution also. To ob­
tain that, it was assumed that each sex group would

3The methodology and assumptions for the most recent Bureau of
the Census population projections are in Current Population Reports,
Series P-25, No. 704 (Bureau o f the Census, 1947), pp. 9-11.

4Current Population Reports, Series P-25, No. 643 (Bureau o f the
Census, 1977), table A-3.




Projection © the
f

6

total

and civ ilia n labor force

have the same ethnic-age structure as in 1979, the most
recent year for which Bureau of the Census data were
available.5 From 1986 on, the Armed Forces were as­
sumed to have the same age structure as that projected
for 1985. With the addition of the Coast Guard and re­
serves, the Armed Forces would have the following
composition (in thousands):

1980
1981
1982
1983
1984
1985

,
.......
...,...
.......
.......
.......
.......

Both
sexes
2,088
2,099
2,111
2,120
2,125
2,129

Men
1,910
1,900
1,892
1,885
1,876
1,871

Women
178
199
219
235
249
258

interpreting the projections

If the future labor force could be determined with no
error, then only one series would be necessary; this ac­
curacy was not possible. Most users would like an as­
sessment as to the likelihood of the forecast occurring.
Given the judgmental aspects involved in making these
forecasts, formal confidence intervals could not be con­
structed. However, four comments should be helpful.
First, the three forecasts were made with reasonable as­
sumptions about the future of the labor force. Second,
only the high projection has any turning points; it is
quite likely that some of the labor force series will in­
deed change direction. Third, as Theil points out, pro­
jections must at some place in their structure hold
change constant, whether it is the level of net migration
or the rate of change; this has the effect of underesti­
mating the amount of change. Further, as Mincer and

‘Henry Theil, A pplied Econometric Forecasting (Chicago, Rand
McNally and Co. 1977), pp. 13-14. Jacob Mincer and Victor Zar­
nowitz, “ The Evaluation o f Economic Forecasts,” in Jacob Mince,
ed., Economic Forecasts and Expectations: Analyses o f Forecasting
Behavior and Performance (New York, National Bureau o f Economic
Research, Columbia University Press, 1969), pp. 3-46.

5Current Population Reports, Estimates o f the Population, by
Age, Sex, and Race: July 1, 1977 to 1979, P-25, No. 870, 1980.




Zarnowitz indicate, it is harder to project a rising level
of activity.6 For men, this tendency would overestimate
the level of their labor force activity, while the rate and
level of women’s activity would be underestimated. The
relative sizes of the two components of the labor force
would be even more poorly projected. Since several
groups of both men and women had rates that appeared
to be changing at an increasing rate, the problem will
likely continue, even if all such phenomena must stop.
Finally, examination of several labor force projections
and of sensitivity studies of labor force models indicated
that the confidence interval was at least as wide as 6 per­
centage points, which suggested that a crude, but useful,
rule of thumb would be to use the unemployment levels
and rates for age groups as confidence intervals.
Users should avoid the temptation to use the mid­
dle-growth projection simply because it is in the middle.
For some purposes, either the high- or low-growth sce­
narios will prove more useful. The high-growth scenar­
ios will be useful in exploring not only the aspects of
faster labor force growth, but also those of convergence
of labor force activity rates. The low-growth alternative
presents the opportunity to explore aspects of more di­
vergent labor force trends. The way in which the projec­
tions were made allows modularity; for example, re­
combining the high-growth labor force projections for
older workers with low-growth projections for other
workers. Alternately, under an assumption of competi­
tion of male and female labor force activity, the male
high-growth scenario could be combined with the fe­
male low-growth scenario.

7

Chapter 3. Aggregate
Economic Projections

The b l s macroeconomic model provides estimates
of growth in the major sectors of the economy that are
consistent with all assumptions and conditions of a par­
ticular projection scenario. The purpose of the aggre­
gate 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 1969.7
The b l s macro model is a relatively small-scale
model (approximately 50 equations) whose purpose is
to capture the impacts of those factors which affect de­
mand and supply over the medium to long term. The
model is structured around a framework in which out­
put produced is balanced with output demanded via in­
come flows. To bring about this balance between sup­
ply and demand g n p , the model is structured to re­
spond 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. Major exogenous variables are pointed out as
necessary. All of the behavioral equations and major
model identities referred to are detailed in appendix B.
The four computational blocks of the macroeconomic
model are outlined below. It is important to note that
all blocks are solved simultaneously.

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 g n p
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 g n p 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 had to be estimated
externally in various ways for the projected periods.
From a solution point of view, all exogenous variables
are considered assumptions. From a structural approach,
however, the exogenous variables must be grouped in
three ways. First were those items projected with so­
phisticated techniques outside the Office of Economic
Growth and Employment Projections such as the popu­
lation projections. Second were items which repre­
sented either policy instruments 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,

A. Supply-side g n p
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
7Lester C. Thurow, “A Fiscal Policy Model o f the United States,”
Survey o f Current Business, June 1969, pp. 45-64.




8

wage base and the combined employer/employee tax
rate. Federal purchases of goods and services, exclud­
ing compensation, were assumed to grow slowly in real
terms, increasing at an average of slightly less than 2
percent per year. Federal transfer payments consisted
of: (1) Unemployment insurance benefits; (2) social se­
curity benefits; (3) Federal civilian employee retirement;
(4) railroad retirement; (5) veterans’ benefits; (6) hospi­
tal and supplementary medical insurance; (7) supple­
mentary security income; and (8) all other Federal trans­
fer payments. Projections of each category were gen­
erally based upon expected inflation, changes in the size
of client populations, and expected real changes in bene­
fits. For this projection series, all categories were as­
sumed to maintain the same level of real benefits through
1983; after 1983, modest annual increases in real bene­
fits were assumed for each. Grants-in-aid to States and
localities and subsidies to Federal Government enter­
prises were assumed to continue unchanged in real
terms.

were the result of such measures. Finally, there were
those exogenous variables which were assumptions in
the narrowest sense; i.e., 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 were projected and con­
sidered as a whole, they presented a picture of the eco­
nomic conditions assumed for a particular set of pro­
jections. All of the projection results were heavily in­
fluenced by the initial assumptions required to operate
the macro model. These followed from the nature of
the scenario or the conditions examined for their effects
on employment. Four categories of explicit assumptions
were developed for each scenario: Demographic, fiscal
policy, price, and productivity assumptions. In addition,
certain general goals or guidelines affected the projec­
tions process. For example, the effects of rising energy
prices and potential energy shortages were considered
and were assumed, or expected, to be insufficient to
have a significant effect on 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 approxi­
mately to balance budget receipts and expenditures to
the extent the scenarios permitted.

Price. While price assumptions did not directly affect
the determination of real GNP, they did affect the pro­
jections in several important ways. First, wage rates
and interest rates were influenced to a great extent by
price changes. These in turn affected consumption ex­
penditures and residential investment. Second, price
changes affected the Federal budget. They entered im­
plicitly into the determination of various expenditure
levels, while on the revenue side, they affected personal
income taxes because of the progressive tax structure.
The movement of prices in the future, of course, could
not be adequately projected. Price assumptions used in
the projections were judgments that might contain sub­
stantial 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.

Demographic. Demographic assumptions included 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 assump­
tions were the current and expected level and age dis­
tribution of the population based on the three projected
population series.8 The series II projections were used
for the base projections. Projections of the number of
households and the number of students were also avail­
able from the Bureau of the Census.9 It was assumed
that recent trends in urban population growth would
continue throughout the projected period.

Productivity and employment. Private nonfarm produc­
tivity was assumed to grow slowly during the projected
period; above the average for the period 1968-77, but
below that for 1955-68. A slow recovery to rates of
growth typical of the 1960’s was assumed, predicated
upon the reversal of some previously depressing fac­
tors. Members of the post-World War II baby boom
would be more experienced as workers during the
1980’s. Also, recent rapid growth in the levels of in­
vestment in environmental and energy conservation
equipment was expected to slow down by 1985, allow­
ing a greater proportion of investment funds to be spent
on more industrially productive plant and equipment.
The moderate labor force projection was adopted for
the base case and its alternative, while the higher labor
force estimate was used for the high-trend alternative.
From these levels, assumptions were then made as to

Fiscal policy. Fiscal policy included a variety of as­
sumptions about personal and business taxes, Federal
purchases of goods and services, Federal transfer pay­
ments, grants-in-aid, and subsidies. Federal personal in­
come tax cuts were assumed for the 1980’s of sufficient
magnitude to offset the impact of inflation on the per­
sonal tax rate. The tax rate on corporate profits was
assumed to drop moderately, leveling off at 45 percent
after 1980. Estimates of contributions for social secu­
rity programs were based upon the expected taxable
8Current Population Reports, Series P-25, No. 704, July 1977 and
1978.
9 Projections o f the number o f households were from Current Popu­
lation Reports, Series P-25, No. 607, July 1977 and 1978. School en­
rollment participation rates by age group were drawn from Current
Population Reports, Series P-20, No. 278, July 1977 and 1978.




9

in the private sector is allocated to that sector regard­
less 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 in­
come accounting conventions to originate in the pri­
vate 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 la­
bor force participation rates for males and females. The
current version takes the labor force as exogenous. La­
bor force projections start with population projections
made by the Bureau of the Census. The principal area
of uncertainty in these projections is the estimate of the
labor force participation rate for women. The un­
employment rate of the civilian labor force was set
exogenously as a target variable. Thus, civilian employ­
ment as a count of persons is determined by multiply­
ing the civilian labor force by the employment rate
(equation 1, appendix B).
Employment data at the industry level of detail are
available from the monthly BLS survey of business es­
tablishments.1 This survey is a count of jobs, whereas
0
the household survey, which forms the basis for the
historical time series on the labor force and unemploy­
ment rate, is a count of persons. In order to maintain
consistency between aggregate and industry results,
equation 2 (appendix B), is used to relate establishment
based civilian employment to civilian employment on
a persons basis and the unemployment rate. A major
difference between the two series arises from individuals
who hold more than one job, who would be counted
only once in the household survey as being employed,
but more than once in the establishment survey. Other
differences between the two series have been examined
in detail elsewhere.1 The absolute difference between
1
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 in 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. Pur-

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 he em­
ployed. The unemployment rate, treated as a policy ob­
jective in the projections, had a major impact on the
results. After recovery from the 1980 recession, un­
employment was assumed to achieve a stable long-run
rate.
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 deflector
Farm equipment purchases
Farm structures purchases
Equipment discards
Structures discards
Residential structures discards
Statistical discrepancy
Unemployment insurance contribution rate
Combined social security contribution rate
Social security benefits coverage 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
Sup p ly

gwp

The first stage in the model sequence is to determine
what the economy can produce. This occurs in the sup­
ply 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



1 This BLS survey is described in monthly issues o f Employment
0
and Earnings (Bureau of Labor Statistics).
"Gloria P. Green, “Comparing Employment Estimates From
Household and Payroll Surveys,” Monthly Labor Review, December
1969.

10

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 included to arrive at compensation for
Federal military, Federal civilian, State and local edu­
cation, and State and local noneducation employees
(equations 22-25). In all four cases, the equations con­
tain 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).

chases 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. Fed­
eral civilian employment and private farm employment
were 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 was 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,
however, is 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 to­
tal hours worked in the farm and nonfarm sectors. To­
tal hours worked in the two sectors are transformed
into 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 se­
ries are maintained as well for residential structures and
business inventories (equations 16 and 17). However,
these two stock series do not enter the production re­
lationships. Stocks are updated by adding current in­
vestment to last year’s capital stock and subtracting dis­
cards. 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 in­
dexes form the capital input to the macro model pro­
duction relationships.
The final step in calculating private supply gnp is
to translate hours worked and capital stocks into a re­
sulting flow of goods and services via a production re­
lationship. Two production functions are used 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 changing capac­
ity utilization (as indicated by the unemployment rate),
the impact of available labor and capital, and disem­
bodied 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 diminish­
ing rate. In the original formulation of these relation­
ships, 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



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 (equa­
tion 28), defined as book corporate profits and capital
consumption allowances, is estimated as a function of
nominal private gnp , capacity utilization, and the rela­
tive movements of output prices and labor costs. Sec­
ond, corporate capital consumption allowances, with
(equation 29) and without (equation 30) the capital con­
sumption adjustment, are related to the fixed stock of
business capital. Third, Federal corporate profits taxes
are determined in equation 31 as a function of corpor­
ate profits and the Federal corporate profits tax rate.
State and local corporate profits taxes are exogenous.
Corporate dividend payments are derived (equation
32) as a function of lagged dividend payments, reflect­
ing the importance of precedent on this item, and to
corporate internal funds net of fixed investment ex­
penditures. 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 undistrib­
uted corporate profits.
The key to personal income is an identity which ex­
presses 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

11

Plus:
Equals:
Less:
Plus:

Equals:

and coverage ratio are exogenous as is the wage base
in the historical period. In the projection period, how­
ever, attempts have been made to relate the wage base
to changes in nominal average compensation, lagged
two periods. State insurance funds are related to ad­
justed compensation of State employees only. All other
contributions to Federal programs, such as Federal ci­
vilian 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 so­
cial 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 yield 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 equa­
tion 49. Progressivity is built into the equation by in­
cluding the average tax rate on median family income.
State and local personal taxes (equation 50) are a func­
tion of personal income, lagged taxes, and a time trend.
Deducting personal taxes from personal income (equa­
tion 51) yields an estimate of disposable personal in­
come. Personal savings are related to the level of dis­
posable income, medium-term interest rates, and the in­
flation rate in equation 52. Aggregate personal con­
sumption expenditures are determined by an identity in
equation 53.

Business transfer payments
Statistical discrepancy
Subsidies less current surplus of
government enterprises
National income
Book corporate profits
Social insurance contributions
Transfer payments
Net interest
Consumer interest
Dividends
Business transfer payments
Personal income

Noncorporate capital consumption allowances (equa­
tion 36) depend upon the housing stock as the princi­
pal explanatory variable. The housing stock multiplied
by a time trend is used as an additional explanatory
variable. Determined in real terms, noncorporate con­
sumption allowances are then converted to current dol­
lars with the capital consumption deflator in equation
37. Federal indirect business taxes (equation 38) are re­
lated to private nominal G NP, the Federal tax rate on
gasoline, projected motor fuel usage, and a dummy vari­
able 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 Fed­
eral Government. Business transfer payments, the sta­
tistical 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 mar­
ketable bills, bonds, and notes, incremented by the value
of the Federal deficit ( + ) or surplus (— in each suc­
)
ceeding year. State and local interest payments are
exogenous.
Social insurance contributions are determined by four
equations and one identity. The major determining vari­
able in three of the equations is compensation adjusted
for employer contributions for social insurance. There­
fore, equation 41 relates the employer share of social
insurance contributions to total contributions. Follow­
ing this determination are three equations (equations
42-44) for the following types of contributions: (1) Un­
employment insurance funds, (2) social security funds,
and (3) all State and local government social insurance
funds. The unemployment fund contributions are de­
termined as a function of adjusted compensation and
the exogenous average employer contribution rate for
this category of social insurance. Social security con­
tributions are related to the adjusted level of compen­
sation, the wage base, social security coverage, and the
combined employer/employee tax rate. The tax rate



Demand g n p
There are currently three equations (equations 54-56)
in the model for personal consumption expenditures.
The durable goods equation depends upon total per­
sonal consumption as an income proxy as well as the
unemployment rate, the previous year’s residential in­
vestment, 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 the unemployment rate. Consumption of
services is a function of total consumption, the un­
employment rate, and the stock of residential structures.
There are four equations for investment (equations
57-60). Nonfarm equipment purchases depend upon pri­
vate nonfarm g n p , the internal flow of funds available
for investment, the existing stock of equipment, and the
interaction between capacity utilization and profitabil­
ity as measured by the previous year’s ratio of internal
funds to the capital stock. Nonfarm structures purchases
are related to private nonfarm g n p and the previous
year’s investment in structures. Farm purchases of
equipment and structures are exogenous.
The equation for changes in the stock of business in­
ventories is not formulated to capture short-run fluc­
tuations in inventories. Rather, it represents an attempt

12

65) determines the implicit deflator for private g n p 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 identi­
ties for private compensation per hour, private com­
pensation, unit labor costs, and the spread between price
change and wage change. Equations 71-79 are deriva­
tions of other deflators as a function of the private g n p
deflator. Finally, equation 80 is an identity for the total
GNP deflator as a weighted sum of the various demand
component deflators.

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 vari­
able 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 equa­
tion 61 by real incomes, relative prices, lagged imports,
and a capacity-pressure variable based upon the spread
between potential and actual g n p . This particular vari­
able 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 Gov­
ernment are determined by an identity given in equa­
tion 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 nonedu­
cation (equation 64) sectors. Noneducation purchases
are related to private g n p , Federal grants-in-aid for
noneducational uses, and the unemployment rate. Edu­
cation purchases are determined as a function of pri­
vate GNP, Federal education grants, and school
enrollments.

Balancing the macro model
Summation of the derived real components of de­
mand in equation 81 yields the demand-side estimate of
g n p . The demand- and supply-side estimates of gnp
ordinarily will 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 incomes for all of the sectors neces­
sarily equals the estimate of the g n p , demand for g n p
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.

Price/wage sector

As was previously noted, the supply and demand
blocks of the BLS macro model are determined in con­
stant 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 ac­
complished with a set of exogenously specified defla­
tors. The price/wage sector has been added to insure
Solving the macro model
internal consistency between price and wage determi­
The solution of the model is somewhat different from
nation and to determine the rate of inflation within the
the foregoing discussion of behavioral relationships and
model.'2
identities. In order to facilitate solution, equations are
There are two major equations and four identities in
arranged by block, where equations within a block are
this sector of the model. The price equation (equation1
2
simultaneous. Initial estimates of the key block results
are provided and iterative solution techniques are ap­
1 Richard C. Barth, “The Development of Wage and Price Rela­
2
plied to refine the initial solution until the model arrives
tionships for a Long-Term Econometric Model,” Survey o f Current
at a consistent solution.
Business, August 1972, pp. 15-20.




13

Chapter 4. Final Demand
Projections

Gross national product is the final output of the econ­
omy 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
involved estimating the future purchases of each de­
mand sector, by industry of origin. For the 1990 pro­
jections, the economy was disaggregated into 156 dif­
ferent industries. These industries define the bills of
goods, or lists of purchases, prepared for each final de­
mand 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 pub­
lished input-output studies (1958, 1963, 1967, and 1972);
1 1972 became a base year for the projections. In addi­
3
tion, many data series were available through 1979, pro­
viding recent trends. These historical data were used
with a variety of techniques and submodels to project
purchases.
Assum ptions

Various assumptions underlay projections of the de­
tailed purchases of the final demand sectors. In gener­
al, these assumptions followed the conditions of the
scenarios being examined; major changes expected in
the magnitude and nature of the activities of each de­
mand sector; and in some cases, changes in the demand,
price, and availability of particular products. While as­
sumptions were developed primarily for functional lev­
els 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 developed.
Major functional areas were considered first. For ex­
ample, the recent history of health care was examined
for trends, and various current proposals for change1
3
1 The Input-Output Structure o f the United States, 1958-, 1963; 79(57;
3
and 1972 (U.S. Department of Commerce, Bureau o f Economic
Analysis).




14

were considered. Since the classification of health pur­
chases is different for private and public buyers, the
extent of increased Federal Government participation
through 1990 had to be examined. Since information at
the time was limited, it was assumed that Federal Gov­
ernment participation would increase slightly, but that
no comprehensive 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 peri­
od, the size of the school-age population was expected
to decline, but the post-World War II baby boom mem­
bers would be entering childbearing age. The possibil­
ity of the private sector increasing its share of school
expenditures, relative to the public share, also had to
be evaluated. In addition, the impact of increasing en­
ergy costs and shortages on purchases of different types
of transportation services was 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. pol­
icies on military sales to foreign governments. Aircraft
purchases were heavily influenced by defense assump­
tions, expected foreign military sales, and airline invest­
ments. Energy was the principal area where assump­
tions were made on a product level. Energy assump­
tions in the projections were based, in general, on fore­
casts prepared by the Department of Energy which
were primarily forecasts of the total use of energy by
type of fuel. These projections provided the basis for
estimating the output levels of domestic energy indus­
tries. In some cases, estimates were also available on
consumption by particular demand sector. In other
cases, energy purchases by final demand sector were
estimated using past trends, constrained by the projec­
ted total use of each type of energy. In general, it was
assumed that the prices of natural gas and oil would
increase more rapidly than the prices of coal and elec­

Product projections. A consumption submodel was used
to project the 12 major product groups as well as the
82 detailed product categories. This model, which re­
lated consumer expenditures primarily to income and
prices, was originally developed by Houthakker-Taylor,1 with the 1958 constant-dollar data from 1929 to
6
1964, used to estimate a set of 82 product expenditure
categories. Total PCE and the annual change in PCE
are primary variables used as a proxy for disposable in­
come. PCE has a high level of explanatory power in
these equations. Relative prices, which were calculated
as the implicit price deflator for that good or service
divided by the implicit price deflator for total PCE,
were also used extensively. The lag structure of the
equations allowed changes in explanatory variables to
be distributed over time.

tricity. Coal and electricity were assumed to be more
readily available through 1990.
Personal consum ption expenditures

Personal consumption expenditures (PCE) are the
value of all consumer goods and services purchased by
individuals and other nonprofit institutions. Purchases
of dwellings are not included, although the rental val­
ue of owner-occupied dwellings is imputed to consump­
tion outlays.
The distribution of P C E to producing industries was
accomplished in two major steps. After total consump­
tion was determined by the BLS macroeconometric
model, the first step was to project consumption, by
type of expenditure, for 12 major product groups de­
fined by the Department of Commerce: (1) Food and
tobacco; (2) clothing, accessories, and jewelry; (3) per­
sonal care; (4) housing; (5) household operation; (6)
medical care expenses; (7) personal business; (8) trans­
portation; (9) recreation; (10) private education and re­
search; (11) religious and welfare activities; and (12)
foreign travel and other, net. These 12 major product
groups were summed up and then scaled to the projec­
ted total consumption controls of the macro model.
Next, using these 12 product groups, a set of 82 lower
level product categories, defined by the Department of
Commerce as well, were projected. These 82 detailed
product categories were also forced and scaled to sum
to their appropriate 12 aggregate controls. Historical
data for each of these categories were available from
the Department of Commerce as part of the National
Income and Product Accounts.1 These data were used
4
to develop two sets of behavioral equations to project
the 12 major product groups and the 82 detailed prod­
uct categories.
The second step was to distribute these 82 product
expenditures to the producing industries. This task was
accomplished with the use of projected “bridge” tables
or matrices which distributed each of these 82 catego­
ries to its component industries as well as to the trans­
portation, insurance, and trade industries. The result
was the PCE bills of goods, the largest component of
final demand.
Input-output tables constructed by the Department
of Commerce exist for the years 1958, 1963, 1967, and
1972.1 Each input-output table has an associated PCE
5
bridge table which distributes expenditures for the 82
products. Each product was assigned to one or more
of the Bureau of Economic Analysis (BEA) 496 sectors
or industries. The BEA estimates these products for
each year and benchmarks them to new bridge tables
as they become available.

For these projections, 1947-78 data, in 1972 constant
dollars, were used to reestimate real consumption ex­
penditures for the 12 major groups and the 82 detailed
categories. It was assumed that consumer decisions are
based on a bundle of goods and services purchased si­
multaneously rather than on purchasing one good or
one service at a time. Based upon this expenditure con­
cept, a set of 12 major product equations was simulated
first over the projection period, using preliminary total
PCE controls from the macro model. For these projec­
tions, the macro model prepared three alternative fore­
casts of trend growth, differing primarily in the assumed
labor force growth, unemployment rates, inflation rates,
and production levels. Thus, total PCE controls in the
alternative forecasts were provided by the macro mod­
el. The lagged value of the particular product equation,
disposable personal income obtained from the macro
model, and relative prices1 were primary determinants
7
in these equations. Additionally, with regard to the in­
fluence of other factors on consumption, the gross stocks

1
6 H. S. Houthakker and L. D. Taylor, Consumer Demand in the
U.S.: Analyses and Projections (Cambridge, Mass., Harvard Universi­
ty Press, 1970).
1
7
The price model assumed a markup specification; the input costs,
such as labor and energy, were marked up to yield final product
prices. This is naive in that it is not based on any particular formation.
A specification equation is formed as follows:
pt = AO + Al(time) + A2(unit labor costs)tl + A3(energy prices)t }
where p = implicit price deflator in year t o f the good,
1972 = 100
time = time trend, 1945 = 1
unit labor costst = unit labor costs, private business
economy, in year t
energy pricest = producer price index o f fuels and
related products,
and power in year t, 1967 = 100
The price equation is essential, not in itself, but as a vehicle to close
the consumption model. Time series data for the explanatory
variables-unit labor costs and energy prices, both historical and pro­
jected period-were provided by the macro model.

14Survey o f Current Business, July issues, tables 2.4 and 2.5.
1 The Input-Output Structure o f the United States, 1958- 1963; 1967;
5
and 1972 (Bureau o f Economic Analysis).




15

of durable goods1 and demographic variables1 were
8
9
also introduced into these equations. For example, the
stock of television sets was found to be an important
determinant in the recreation group, and the population
18-34 age group was found to be important in explain­
ing the expenditures in the household operation group.
Using time series data, the estimation of the specifi­
cation regression occurred at the product level. One of
two estimation techniques was used—either the
Cochrane-Orcutt or nonlinear least squares. The results
were evaluated from the economic and statistical points
of view. If the regression coefficients either had an ec­
onomically incorrect sign or were statistically insignif­
icant, the respective variables were dropped from the
estimated equation. For these 12 major product equa­
tions, the income coefficients were statistically signifi­
cant and had a positive value for 11 of the 12; the price
coefficients were significant and had a negative sign for
10 of the 12; the coefficients of the gross stocks of du­
rable goods were significant and had a negative value
in 2 equations; and the coefficients of the demographic
variable were significant in 6 equations.
As mentioned above, the sum of the projected 12
major product groups was brought into balance with
macro consumption totals by allocating the difference
to groups according to their weighted average values.
After the 12 subtotals were forecast, the 82 detailed
equations were projected by using their appropriate
subtotal PCE controls, their relative prices (derived in
the same manner), and the lagged value of the partic­
ular individual good or service, also, the gross stocks
of durable goods were introduced into those 11 dura­
ble goods equations. Due to time limitations, demo­
graphic variables were not used in the 82 product cate­
gories. Using the same estimation techniques to estimate
these 82 detailed products, the income coefficients were
statistically significant and had a positive sign for 72 of
the 82; the price coefficients were significant and had
a negative sign for 65 of the 82; and the coefficients
were significant and had a negative sign for 7 of the 11
durable goods equations. Finally, the 82 product equa-

tions were aggregated to their appropriate 12 major
groups and were balanced with their corresponding
subtotals by scaling the difference to categories accord­
ing to their weighted average values. A complete PCE.
variable list and all of the behavioral equations, both
consumption and price, are given in appendix C.
Industry projections. The 82 product expenditure cate­
gories were transformed to a set of final demands con­
sistent with the input-output framework. Each of these
82 categories was made up of many types of goods and
services, produced by different industries. A bridge ta­
ble or matrix was used to transform the product fore­
casts into the 156 industries used in the projections.
A bridge table distributes the 82 product categories
to their component goods and services and to the mar­
gin industries; i.e., wholesale and retail trade margin
and transportation costs. The products are expressed in
purchasers’ values, while the bills of goods or the pro­
ducing industries are expressed in producers’ values.
The difference is the cost added to a particular indus­
try’s output in getting that output from the point of
production to the consumer, including transportation
costs (railroad, truck, water, air, and pipe- line costs),
insurance costs (for imports only), and wholesale and
retail trade markups. The bridge table accomplishes two
tasks at once—it allocates each of the 82 product cate­
gories to its producing industries, and removes the trans­
portation and trade margins from the product and al­
locates 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, 1967,
and 1972. Each bridge table had been prepared in cur­
rent dollars. For this project, the 1963 and 1967 tables
were reestimated in 1972 constant dollars and readjusted
based on the 1972 Standard Industrial Classification
(SIC). Also, the 1963 and 1967 tables were further mod­
ified in the way imports were handled.2 First, imports
0
were valued at domestic port value instead of foreign
port value, decreasing the margin entries by the amount
of margins associated with transporting the goods be­
tween the foreign and domestic ports and increasing
the producers’ value by an appropriate amount. Sec­
ond, imports were assigned to the relevant domestic
industry based on the nature of the product. For the
1972 bridge table, except for those noncomparable im­
ports, all of the comparable imports were already val-

1 The gross stock o f durable goods is identified as:
8
stockt = stockt j + investment - discardt
where discard{ = AO + Al(tim e) + A2(stock)t j
and investm ent = AO + A l(consum ption expenditures)t

The annual data for investment in durable goods are made available
by the Bureau of Economic Analysis in the form of worksheets, while
the gross stock o f durable goods appears in John C. Musgrave, “ Dur­
able Goods Owned by Consumers in the United States, 1925-77,”
Survey o f Current Business, March 1979, pp. 17-25.

20 The treatment of foreign trade was changed in these projections
to yield domestic rather than total output. Imports that were com ­
petitive were 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 on foreign trade in this
chapter.

1 The ratio o f population age group 18-34 to the age group 16 and
9
over was chosen in the consumption model. Annual historical data
and projected data were obtained from the Bureau o f the Census
population estimates or the BLS macro model data base.




16

ued at domestic port value by the BEA; therefore, no
further adjustment was needed.2
1
The 1972 bridge table was used as an initial estimate
of the projected bridge tables. However, feedback from
the final demand-output review required extensive work
for some of these 82 products, especially for the prod­
uct of “food for off-premise consumption,” changing
their relationships among industries producing these
goods and services, as well as the margin industries in
the projected years. In total, changes were made for 38
of the 82 categories, of which 13 were changed sub­
stantially and the rest only marginally for three alter­
native forecast versions.
G ross private etomestie investm ent

Gross private domestic investment is composed of
fixed investment and the change in business inventories.
Fixed investment represents purchases of durable equip­
ment and structures by both business and nonprofit in­
stitutions 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 in­
dustrial composition of investment demand, four cate­
gories 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 deri­
ved 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 1979 was developed from
data from the national income accounts. These data
showed the movement of the detailed types of residen­
tial construction, such as single-family homes, multi­
family units, and additions and alterations. For nonres­
idential structures, detailed data from the national in­
come 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 us­
ing 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.

2 The B E A ’s latest 1972 input-output tables were used in their
1
present benchmark revision. However, during these projections, the
revised estimates of the National Income and Product Accounts were
only available for 1972. The changes of rate between the revised
PCE and the previously published PCE for 1972 were weighted by
each of the 82 product levels, and these weights were carried over
by products in the projection period.




17

The development of historical bills of goods for pro­
ducers durable equipment (PDE) involved two ap­
proaches that provided a check on the consistency of
the data base from which the projections were made.
The first approach studied the growth of demand in
equipment over time. Annually, the national income ac­
counts show PDE distributed among 24 major catego­
ries such as agricultural machinery, construction ma­
chinery, communication equipment, etc. Each of the 24
categories was in purchaser prices and contained a vary­
ing number of supplying industries. For the years for
which input-output tables were prepared (1-0 years),
bridge tables were available which allocated each of
these 24 categories to the margin and the supplying in­
dustries. Bridge tables for non-I-0 years were construc­
ted by interpolation to provide annual PDE bills of
goods for the period 1958 to 1979.
The second approach made use of the assumption
that an industry’s investment was a function of its out­
put. The Annual Survey of Manufactures and the Census
of Manufactures are the sources for equipment invest­
ment for the historical period. For 1-0 years, capital
flows tables are available which allocate the total in­
vestment of each industry to the supplying industries,
thus, producing a PDE bill of goods. Bills of goods
derived by these two approaches can be compared to
spotlight changes that are occurring in the bridge table
and the capital flows matrix.
To make PDE projections, both investment output
ratios and capital flows were projected based on the
historical trends they have demonstrated. Projected out­
put by industry was first derived, then the projected
investment output ratios were applied to derive the lev­
el of investment by each industry. This level of invest­
ment was run through a capital flows table giving a
PDE bill of goods. This investment in total was made
to equal total PDE as derived from the macro model
runs. Obviously, changes in the distribution of PDE by
industry changed the output level of each industry
which caused a further change in the required invest­
ment. Adjustments were made repeatedly to the PDE
column until PDE demand in each industry equaled the
level of investment that was actually required by the
distribution of output.
The handling of the business structures and residen­
tial new construction was different from the BEA in­
put-output and past construction procedures. Previous­
ly, the inputs into the construction industries were
shown in the body of the table; total construction final
demands were shown in the gross private fixed invest­
ment and the government bills of goods. The output of
the construction industry equals the final demand of
this industry since there is no intermediate demand; i.e.,
there are no values in the row of the construction in­
dustry representing sales to other industries since con­
struction does not contribute material inputs to the pro­

duction process. The new construction industries were
removed from the table and were placed in final de­
mand columns composed of the materials and services
purchased by the new construction industries with val­
ue added appearing as a new industry; i.e., the con­
struction industry. The purchases of new construction
on the part of the Federal and the State and local gov­
ernments were included also in the bills of goods as di­
rect purchase of the inputs. In order to derive the con­
struction bills of goods, the input columns from histor­
ical tables were removed and made final demand col­
umns. For the projected period, changes that could be
expected in the input structure were incorporated in
the projected bills of goods.
Historical data for the inventory change bill of goods
are available only for the 1-0 years. Input-output con­
ventions allocate inventory change to the producing
industry, no matter which industry held it. Using Cen­
sus and Annual Survey o f Manufactures data, inventoryto-shipments ratios for historical periods were derived
and benchmarked to input-output conventions. These
inventory-to-shipments ratios were projected and ap­
plied to projected outputs giving a change in invento­
ry bills of goods.
Investment in equipment is allocated to many differ­
ent 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 oil-field machinery to amuse­
ment 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 in­
dustry except construction and services. The relative
importance of any entry can change greatly from year
to year. Detailed bills of goods are available only in 1-0
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 1979 were used to project the movement of
these detailed categories into the future. These individ­
ual projections were aggregated and evaluated against
the projected controls obtained from the macro model.
Changes were made as necessary to the detailed pro­
jections until they added to the control totals. These
estimates, along with estimates of the other final de­
mand bills of goods, were used to generate initial esti­
mates 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 ini­
tially 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, was 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 indus­
tries 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 was a complex process.
Initially, producers’ durable equipment was projec­
ted for detailed industries based on historical trends. As
in the case of nonresidential structures, these estimates
were used to generate initial estimates of output by in­
dustry. 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 in­
vestment, investment-output ratios and capital flows ta­
bles 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 in­
dustry was used as an initial estimate of the bill of goods.
Industries which had a perishable product were adjust­
ed to be more in line with past levels. The initial pro­
jections 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 in­
dustries since this item is relatively unimportant in longrun projections.
Foreign trade

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 consis­
tent 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 input-

18

output industry sectors. Data on both exports and im­
ports can be obtained from the detailed merchandise
trade statistics published annually by the Bureau of the
Census. For exports, this included SIC product codes
and schedule B commodity codes. For imports, data
were available by SIC-based product codes and by spe­
cial U.S. tariff schedule codes. Data requirements after
aggregation involved modification and augmentation to
reflect
balance-of-payments
and
input-output
conventions.
Although exports are treated the same as any other
component of final demand in the input-output system,
imports require a unique treatment. Total imports are
projected by an equation in the macroeconometric mod­
el. This total is divided into two categories in the in­
put-output system. The first category consists of all im­
ports by final users, as well as intermediate imports,
which are competitive with domestic products. The
second category consists of intermediate imports which
have no domestic counterparts, such as coffee and
diamonds.
In the input-output system, this first category of im­
ports is shown as a negative column of demand; that
is, subtracted from final demand in order to yield de­
mand for domestic output rather than total output for
each industry. Automobiles are a good example of im­
ports not subject to further processing. 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 domes­
tic goods which, when applied to the coefficients of
the input-output table, produces estimates of domestic,
rather than total, output by industry.
The projection of competitive imports by industry
was mainly based on analysis of existing and expected
shares of the domestic market. Trade agreements which
might restrict imports were also taken into account.
The second category of imports encompasses inter­
mediate 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 allo­
cated to the industries which use them in their produc­
tion processes. Thus, coffee, which is not produced in
the United States, is directly allocated to the food prod­
ucts industry where it is ground, blended, and packaged
before being allocated to the personal consumption ex­
penditure category of final demand. Once the interme­
diate, 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.




19

After imports were initially projected, the level of
exports was set so as to reach a nearly zero currentdollar trade balance in the projected years, an assump­
tion or policy target. The value of total exports was
distributed by industry, primarily on the basis of time
trends and expected world conditions. It was necessary
to rely on simple forecasting techniques to project ex­
ports by industry because long-term estimates of for­
eign income and prices were not widely available.
Industry projections. For most industries, the foreign
trade projections relied on an analysis of the trends of
imports and exports as shares of total output. The ra­
tios for 1963, 1967, 1972, and, for merchandise trade,
1977 were compared, and the trend carried out to 1985
and 1990. The ratios were applied initially to estimates
of 1985 and 1990 output to compute imports and ex­
ports. The industry levels of imports and exports were
added and scaled to the total values of the macro model.
The results were sometimes modified based on a com­
parison with previous BLS projections of imports and
exports. Where the previous projections relied on spe­
cial analysis or special trade agreements that were still
in effect, these were taken into account. A detailed dis­
cussion of the assumptions of the previous foreign trade
projections is available in an earlier bulletin.2
2
For most industries, it was assumed that the ratios of
imports and exports to output would continue to change
according to past trends. One exception was the motor
vehicle industry. Imports of all cars, trucks, buses, vans,
and spare automotive parts have grown substantially as
a share of the total output of these items purchased in
the United States. This rise was assumed to continue
through the early part of the 1980’s as the auto indus­
try struggles to recover from the 1980 recession. In the
latter part of the decade, however, the import share
was projected to stabilize. This was expected to occur
as the result of two trends: (1) American cars would
begin to compete effectively with gas-economizing im­
ports; and (2) more foreign automakers would set up
factories *in the United States.
Specific assumptions were also made for the energy
industries. To the degree possible, these assumptions
were based on the midprice scenario in the 1979 Annu­
al Report to the Congress of the Department of Energy
in June 1980. It assumed that crude oil nominal prices
would rise from $31.37 a barrel in 1979 to $51.14 in
1985 and to $81.33 in 1990. The Department of Ener­
gy’s projected rates of growth for domestic output and
imports under these price conditions were applied to
BLS historical data to derive the 1985 and 1990 levels

22 Methodology for Projections o f Industry Employment to 1990, Bul­
letin 2036 (Bureau of Labor Statistics, February 1980).

The State and local government model predicts ex­
penditures and employment in current dollars for 20
functions. These functions are projected based upon
Census and BEA data by calendar year. They include:
(1) Elementary and secondary education, (2) higher ed­
ucation, (3) other education, (4) libraries, (5) highways,
(6) health, (7) hospitals, (8) sewerage, (9) public utili­
ties, (10) natural resources, (11) corrections, (12) police,
(13) fire, (14) sanitation, (15) public welfare, (16) local
parks and recreation, (17) general government, (18) oth­
er government enterprises, (19) public housing, and (20)
water and air terminals. The model structure was based
upon data for the years 1960-73. Equations for each
function were first estimated for expenditures and em­
ployment. Expenditures in the model are in current dol­
lars and apply to all outlays, not just purchases of goods
and services. Another set of equations was used to con­
vert expenditures to purchases and compensation. A fi­
nal set of equations was used to convert purchases to
constant dollars. Employment was estimated in full-time
equivalent units. The model is driven by four major
groups of variables: Growth in personal income; demo­
graphic data; grants-in-aid; and an “all other” category
that included interest rates, prices, and unemployment
rates.
BEA data also provided a basis for projecting func­
tional 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, high­
er education, libraries, and other education. There are
five health, welfare, and sanitation functions: Health,
hospitals, sewers, sanitation, and welfare. Three func­
tions are included in safety: Police, fire, and corrections.
Other functions include: General government, high­
ways, natural resources, parks and recreation, water
and air terminals, public housing, public utilities, and
other enterprises. These functional categories were in­
itially projected based upon historical trends and ex­
pected changes.
The next step in the projections procedure was to
reconcile the results of the macro model, the State and
local model, and the projections of the functional BEA
data base. Employment projections from the State and
local model were converted to compensation in the de­
sired format. Compensation was adjusted to agree with
the macro model controls. Construction purchases were
obtained by estimating the proportion of capital expend­
itures that were equal to new and used construction
purchases by function. The results were extrapolated
toward the projection years. As with total purchases
and compensation, construction purchases were con­
verted to constant dollars and calendar years. Ultimate­
ly, control totals were determined for the 20 functions

of domestic production of various types of energy and
the level of oil imports.
Oil imports were assumed by the Department of En­
ergy to be cut back drastically in the 1980’s in the Unit­
ed States and other industrialized nations, reflecting the
assumption that high prices and uncertain supply would
force conservation and a shift to other energy sources.
The principal alternative energy source was assumed
to be coal—coal production and coal exports were pro­
jected to rise dramatically in the upcoming decade.
State and local governm ent

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 used
were education, health, welfare and sanitation, public
safety, and all other. Each of these functional catego­
ries was further distributed to a total of 20 different
sublevels. Each of the 20 was further divided into em­
ployment, compensation, construction, and an all other
purchases category.
The projection of State and local government pur­
chases started with the overall control totals for pur­
chases projected by the macroeconomic model. These
levels were then distributed to 20 different State and
local government functions using both a State and lo­
cal government model and historical data trends. His­
torical data on 20 State and local government functions
are maintained by BEA, broken out by compensation,
construction, and all other purchases. These levels were
projected based upon trends and special studies as well
as by use of the State and local model. The results of
the macro model and the two functional projection ap­
proaches were compared and reconciled to provide ac­
ceptable levels for each of the 20 functions and their
components. The “all other purchases” component for
each of the 20 functions was allocated to individual in­
dustries by projecting historical distribution patterns for
the functions developed by BEA.
The macroeconomic model estimates of projected
State and local government purchases were 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 cate­
gories are divided into compensation and all other
purchases.




20

for compensation, construction, and other purchases
which were compatible with the controls provided by
the macro model for education and noneducation.
These levels of functional purchases were distributed
to the purchases projected to be made from 156 differ­
ent industry sectors. This was accomplished by projec­
ting base-period purchases for each function. Detailed
purchase data by function were obtained from BEA
worksheets for 1963, 1967, and 1972. These years pro­
vided a limited basis for projecting detailed industry
purchases. The projections of purchases for each func­
tion were examined by annual rate of change and
changes in the distribution pattern by industry. Where
changes in a projected year seemed extreme, the pro­
jections were reexamined and revised if necessary.

balancing supply and demand GNP. This model pro­
vides values for total purchases, total compensation of
military and civilian employees, as well as the number
of civilian and military employees. The levels were es­
tablished to insure consistency with overall projection
assumptions. Assumptions were of major importance in
the Federal sector since, in many cases, past experience
was not useful for projection. For example, the projec­
tions have always assumed peaceful conditions without
international tensions. A contrary assumption of war
would result in unpredictably larger Federal purchases
and a much larger defense share.
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 de­
fense and space. The six subfunctions were modified
until they came to the established macro totals. Real
compensation was also derived for each subfunction us­
ing regression equations. Historical data for defense and
nondefense new construction from 1952 to 1979 were
used to derive regression equations to project purchases
from the six new construction industries for each ma­
jor component of the Federal sector; these two values
were then allocated to the six subfunctions based on
historical trends. (See preceding discussion on invest­
ment in structures regarding the handling of new con­
struction in the Government account.)

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 Fed­
eral expenditures, which also include grants, transfers,
and net interest. On the demand side of the national in­
come and product accounts, the Federal sector is di­
vided into the major components of defense and non­
defense, 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 avail­
able. For these projections, the defense sector was dis­
aggregated into two subsectors: Defense nuclear activ­
ities and other defense purchases. In addition, foreign
military sales were examined and projected. The non­
defense 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 his­
torical purchase patterns, expected changes, and as­
sumptions and expectations of Government priorities in
the future. Principal data sources were the Department
of Commerce input-output studies and various unpub­
lished records of agency purchases. Employment data
were obtained from Office of Personnel Management
reports, BLS data, and the U.S Budget appendixes.
Construction data were obtained from a Department of
Commerce series. As with other sectors, projected lev­
els of total purchases were derived from the macro
model. These were first broken down by functional ac­
tivities, and then projected to industry purchases.
The macro model levels of projected Federal pur­
chases were established exogenously in the process of




Purchases, excluding compensation and new con­
struction, for each of the six subsectors were distribu­
ted 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 con­
ditions similar to those assumed for the projected years.
Industry data for recent years, available from the Bu­
reau of the Census, were of particular importance.
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,
particularly for defense and space. Bills of goods were
projected for each of the six subfunctions in 1972 dol­
lars, based upon trends and expected program changes.
Projected imports for the defense and nondefense sec­
tors were shifted to the foreign trade bills of goods.
Since most of the historical defense data bases includ­
ed foreign military sales, these were projected separate­
ly. 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.

21

Chapter 5. intermediate
Demand Projections

change was the differentiation between a commodity
and an industry. A commodity was defined as the pri­
mary product of the industry with the same name. (The
secondary product of one industry is the primary prod­
uct of another industry.) For the first time, it was pos­
sible to solve for both commodity and industry output,
thus making possible differing analyses of the data. The
third major change was in the handling of secondary
products. Previous tables allowed for both redefinitions
and transfers of these products, while in the new 1972
table, all secondary products were redefined. Another
change was the inclusion of a new industry, Eating and
Drinking Places, and the omission of two dummy in­
dustries, Business Travel and Entertainment and Office
Supplies.
There are two commodities for which there are no
industries in the BEA sectoring plan: (1) Scrap, used,
and secondhand goods, and (2) noncomparable imports.
There are five industries in the BEA table which have
no commodities: (1) Forest products, (2) Federal elec­
tric utilities, (3) Commodity Credit Corporation, (4)
Local government passenger transit, and (5) State and
local electric utilities. Otherwise, each industry has a
matching commodity.

After final demand purchases were projected, the in­
termediate demand, or additional output of each indus­
try that is required to support the projected final de­
mands, was calculated using an input-output model.
This model provides a framework for projecting indus­
try outputs, or the total of final and intermediate sales
required of each industry.
An input-output “use” 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 each commodity (the primary prod­
uct of the industry with the same name) to every con­
suming industry and final demand. The sum of all the
entries in a row represents commodity output. Each
column of the matrix shows the inputs of commodities
to that industry which are used to produce its output.
The sum of purchased inputs plus value added (returns
to capital, labor, and entrepreneurial ability) equals the
output of the industry.
A second table, the “make” table, is a rectangular
matrix which shows the production of commodities by
each industry. Each row of the matrix shows which
commodities that industry produces, and each row sums
to industry output. Each column of the matrix repre­
sents a commodity and shows which industries produce
the commodity. Each column sums to commodity
output.
The 1972 BEA input-output study represents a ma­
jor conceptual change from earlier benchmark inputoutput studies. The 1972 study went a long way in
bringing the United States closer to United Nations
conventions in input-output studies, and thus closer con­
ceptually to many other countries. This study was used
as a basis for the revised BLS projections, even though
changes in the study and timing difficulties limited BLS
ability to create a time series of consistent input-output
tables for this set of projections. Consequently, many
of the input coefficients remained unchanged over the
projected period.

Secondary products
The make table, or market shares matrix, mechani­
cally redefines many of the secondary products using
an “industry technology” approach. This means that
the secondary products are assumed to have the same
technology as the primary products of the industry
where they were produced. When redefining these com­
modities, the structure of the producing industry is left
unchanged, but the structure of the primary producer
is modified to account for the differing technologies of
the different industries which may be producing the
commodity. Other secondary products which were not
included in the make table were redefined using a “com­
modity technology” approach. This assumes that the
secondary products differed greatly from primary prod­
ucts of the industry in which they were produced. For
these, the input structure of the primary industry was
used to adjust the input structure of the producing in­
dustry. These specific redefinitions were taken care of
in the use table.

Changes from earlier BEA studies
The changes introduced in the 1972 input-output
study were of several varieties. The most obvious
change was the use of 1972 SIC codes, which resulted
in changes in many industry definitions. The second




22

Valuation ©f transactions

handle compensation and value added in new construc­
tion. The 1985 and 1990 tables were also projected in
constant dollars based upon the 1972 table. Some data
were updated to 1977, but in many cases, due to a lack
of resources, coefficients were unchanged from 1972
over the projected period.

Input-output relationships may be expressed either in
producers’ values or purchasers’ values. Both BLS and
BEA value inputs purchased by a consuming industry
at the price the producer received. Trade margins and
transportation costs associated with these inputs appear
as direct purchases by the consuming industry from the
trade and transportation industries. Since the input-out­
put tables are in producers’ values, all trade and trans­
portation margins had to be stated as demand on those
sectors. This method allows BLS to maintain the detail
on actual purchases of specific materials—materials are
not sold to or purchased from the trade industry. The
output of these trade sectors is measured in terms of
total margins—operating expenses plus profits.
The transactions recorded in the input-output tables
are based on data contained in the Census of Manufac­
tures and the other economic censuses. The Bureau of
the Census assigns establishments to an industry based
on the establishment’s primary output—those products
or services which produce the largest part of its reve­
nue. Many establishments also produce other products
which are different from the primary output—second­
ary products. A commodity is the primary production
of the industry with the same name, and may be pro­
duced anywhere in the economy. Final demand is ex­
pressed in terms of commodities, as is the demand for
goods used in production. But, these commodities may
be produced by a variety of industries. The marketshare matrix, derived from the make table, indicates
what proportion of each commodity is produced in each
industry. This allows an increase in demand for a com­
modity to increase production in each industry which
produces it.
The Economic Growth projections for 1990 involved
three sets of input-output tables—1972, 1985, and 1990.
All tables were prepared in 1972 constant dollars. The
1972 tables represent an aggregation of the 496-order
BEA tables to the BLS 156 sectors. The major differ­
ence in the BLS and BEA tables resulted from the
movement of new construction materials purchases to
final demand and the inclusion of a dummy industry to




Projecting coefficients

Coefficients are projected to change for several rea­
sons— technological change is an important factor, but
not the only one. Changes in product mix or relative
prices can also cause significant changes in coefficients.
Because the BLS industries are aggregates of the more
detailed BEA sectors, a simple change in the relative
importance of those sectors can have a large impact on
the coefficients. Also, as the relative price or availabil­
ity of substitute inputs change, substitutions might
occur.
Several different methods were used in projecting
coefficients. Energy coefficients, both as inputs to oth­
er industries and as inputs from other sectors to energy
producing industries, were projected using projections
available from the Department of Energy. Several in­
dustries were studied intensively to pick up structural
changes which had occurred since 1972, and changes
were then projected forward (for example, the metals
industries). In other industries, changes in expectations
were incorporated (for example, a decrease in sugar in
foods and soft drinks). For other commodities, the rows
of the input-output tables were evaluated and increases
or decreases throughout the economy were made based
upon overall trends in the economy. In some cases, 1972
coefficients were reweighted based upon expected
changes in the relative importance of detailed indus­
tries. Where resources were not available to study spe­
cific coefficients, they were left unchanged from their
1972 or 1977 level.
The same total requirements tables, calculated to
show industry output required to meet demand for com­
modities, were used for each of the alternative models.
The use and make tables consistent with each of these
scenarios were calculated.

23

Chapter 6. Industry Output
and Employment Projeetions

Factor demand model

As described in the previous sections, the multiplica­
tion of projected final demand by the projected in­
put-output matrix yielded initial estimates of gross
domestic output by industry. These estimates were eval­
uated in light of past output trends and expectations for
the future.

The model used to project annual industry employ­
ment and productivity was a factor demand model,
which takes into account the interdependence of both
labor and capital requirements in each industry. In this
model, the demand for labor is a function of the in­
dustry’s output, capacity utilization (measured by the
unemployment rate of last industry employed),
technical change (as approximated by a time trend), and
the stock of capital measured in efficiency units. The
form of the model utilizes a c e s (constant elasticity of
substitution) production function, involving fac­
tor-augmenting technical change. Allowing for eco­
nomies of scale, the production function can be written
as follows:

The historical data against which the initial output
projections were compared are generally derived from a
variety of sources. Manufacturing output is based on
the value of shipments plus net inventory change for
each 4-digit sic industry that is published annually in
the Census o f Manufactures or in the Annual Survey o f
Manufactures. Measures of nonmanufacturing output
are derived from a variety of sources, including the
Minerals Yearbook, Agricultural Statistics, and Busi­
ness Income Tax Returns. The various output measures
are benchmarked to the input-output tables published
by the Bureau of Economic Analysis, in this case, to the
recently released 1972 table. Benchmarking the raw out­
put data takes account of the production of secondary
products, which are treated as transfers to the primary
producing industries under input-output conventions.
After benchmarking, the historical output data are
converted into real dollar terms. To be consistent with
the national income accounts, constant-dollar output is
based on current-year-weighted deflators. These de­
flators are derived from the b l s industry, producer, and
consumer price index series.

(1) Y = Capu[x(AL * L)~w + y(BE * E)~w +
Z(CP * P ) - w ] v / w
— output
= labor services
= equipment stocks
= plant stocks
= efficiency augmenting function for
labor
BE = efficiency augmenting function
for equipment stock
CP = efficiency augmenting function for
plant stock
Cap = capacity utilization

where Y
L
E
P
AL

The final projections of industry output then become
the principal input to the industry employment projec­
tions. The industry employment projections count the
number of wage and salary workers, the self-employed,
and the unpaid family workers. Historical wage and
salary data are based on the b l s establishment series of
employment published in Employment and Earnings,
and the self-employed and unpaid family worker data
are derived from the Bureau of the Census’ Current
Population Survey. (A detailed description of the out­
put and employment data base is available in other pub­
lications.)2
3

and x, y, and z are distribution parameters which
are greater than zero and sum to unity.
w = substitution parameter
v = economies of scale
u = utilization parameter
The elasticity of substitution is equal to 1/(1 + w).
This model uses the concept of efficiency units. In
essence, the concept assumes that labor and capital in­
puts are each a composite of quality and quantity, and
one unit of quantity is not necessarily equal to one unit
of quality. Quality and quantity are differentiated by
the respective functions AL and L for labor; BE and E
for equipment stock; and CP and P for plant stock.

23Time Series Data f o r Input-Output Industries, Bulletin 2018
(Bureau o f Labor Statistics, March 1979), and an updated version to
be published in 1981.




24

These considerations suggested that an estimator such
as Zellner’s minimum distance estimator should be
used. Zellner’s estimator involved stacking the regres­
sion, allowing the errors of the labor equation and the
errors of the capital equation to interact to achieve con­
sistent estimates. However, preliminary tests indicated
severe problems in achieving convergence with the
Zellner estimator.2 To maintain the substitution
4
parameter in both the capital and labor equations, and
to conserve degrees of freedom, the two regressions
were stacked and estimated with ordinary least squares.
This meant that the errors of the labor equation and the
capital equation were jointly minimized. This hybrid ap­
proach yielded 26 observations for each industry—two
equations with 13 observations per equation.
In addition to the output and employment data base,
this model also relied on industry capital stocks data
from the Economic Growth industry data base. These
stocks are documented in another bls publication.2
5

The efficiency functions, AL, BE, and CP, are mea­
sured by technical change as approximated by a time
trend. These efficiency functions are:
It T im e
(2)

A L = a0 e

(3)

BE = b0 e

(4)

CP = C e
o

et T im e

pt T im e

The parameter It is the elasticity of labor efficiency with
respect to pure technical change; et is the elasticity of
equipment efficiency with respect to technical change;
and pt is the elasticity of plant efficiency with respect to
technical change. Assuming competitive factor imputa­
tions, it can be demonstrated that
(5) Lt = a0 + a,Yt + a2Capt + a3 Time
where L, Y, and Cap are expressed in natural logs
and a0 = scalar
ai = 1/v
a2 = u/v
a3 = lt/v

Solving the model
Average weekly hours for each industry were pro­
jected by relating the change in the current year’s work­
week to the change in the current year’s output plus a
constant term. This is written:

(6) Et = b0 + b,Yt + b2Capt + b 3
Time
where E, Y, and Cap are expressed in natural logs
- and b0 = scalar
b, = 1/v
b2 = u/v
b3 - et/v

(8) Change in workweekt = constant + a * change in outputt

Finally, the employment estimates were an identity —
labor hours derived in equation (5) divided by the work­
week.

(7) Pt = C + c,Yt + c2Capt + c3
o
Time
where P, Y, and Cap are expressed in natural logs
and C = scalar
o
c, = 1/v
c2 = u/v
c3 = pt/v

(9) Jobst = labor hourst/workweekt* (52)

Wage and salary employment was computed as a con­
stant share of total jobs, based on the historical time
trend.
After the equations of the mode! produced their in­
itial values, the projections of jobs and hours were scal­
ed to the total jobs and hours used in the macro model.
Finally, the results were reviewed and, where they dif­
fered sharply from expectations with no valid reason for
the deviation, an adjustment was made. These adjust­
ments were usually required when the historical and
projected output trends were very divergent, such as in
the energy industries; when the output and employment
series were unrelated, such as in some transportation in­
dustries; and when the labor productivity trend implied
negative employment, such as for wooden containers,
leather products, and leather tanning.

Estimation. There were several considerations in choos­
ing an estimator of this aggregate multifactor product
model. First, the structure of technology is character­
ized by the input demand equations (5), (6), and (7). A
key element of this characterization is the concept of in­
terrelated demand functions. The estimator of this
model had to maintain this concept. To accomplish this,
it was assumed that deviation of the labor, equipment
stock, and plant stock services from the logarithmic fac­
tor demand equations were the result of random errors
in cost minimizing behavior.
A second consideration was that the substitution
parameter, v, appeared in equations (5), (6), and (7) in
the a’s, b’s, and c’s. Estimates of v with ordinary least
squares would depend upon which equation was used.
The estimation of this factor demand model had to en­
sure that identical values of v were obtained from each
equation. Finally, degrees of freedom posed a problem.
There were only 16 years of available data.



“ Arnold Zellner, “ An Efficient Method for Estimating Seemingly
Unrelated Regressions and Tests for Aggregation,” Journal o f the
American Statistical A ssociation, No. 57, pp. 348-68.
Capital Stocks Estimates f o r Input-Output Industries: Sources and
Data, Bulletin 2034 (Bureau o f Labor Statistics, September 1979).

25

Disaggregation! of results

industry expressing employment as a function of total
civilian employment, the level of the Armed Forces,
output of the corresponding economic growth sector
(156-order), and employment at the appropriate ag­
gregate 2-digit Sic level. An example of the form the
equations took is:

The factor demand model was estimated for only 76
industries, due to the limited amount of employee com­
pensation data which is an input in the estimation of
labor services. In order to expand the results to the 156
industries in the Economic Growth system, least squares
time trends of labor productivity and average weekly
hours were computed for each of the 156 industries and
combined with the 156-order output projections to cal­
culate hours and employment. Then, these estimates
were scaled to the projections from the factor demand
model.
Further disaggregations were required in order to de­
velop occupational projections. Occupational forecasts
were estimated at the 3-digit sic level, totaling about 450
individual industries. Only wage and salary employment
data were prepared at this level. The estimates of jobs at
this level of detail were based on an equation for each




Wage and salary jobs = a0+ ai (total unemployment rate)
-l- a2 (Armed Forces)
-(- a3 (output of corresponding
economic growth sector)
+ a4 (wage and salary employ­
ment at corresponding 2digit industry)
The coefficients were estimates using ordinary least
squares. The results of these equations were scaled to
the wage and salary employment projections of the
156-order industries.

26

©hapSdir 7„ Occupational
Employment Projections

Wag® and salary workers in OES surwey
industries

The method used to develop the 1990 occupational
projections incorporated the industry-occupational ma­
trix as the basic analytical tool. The general approach
was to develop current (1978) estimates of occupation­
al staffing patterns of industries, project these patterns
to the target year of the projections (1990), and multi­
ply the projected patterns by projected industry em­
ployment levels. The products, projected occupational
employment by industry, were then summed across in­
dustries to derive an estimate of projected total employ­
ment by occupation.
This basic approach has been used by the BLS to
develop occupational projections since the mid-1960’s.
The step-by-step procedures used in developing the
1978-90 projections, however, were somewhat differ­
ent than in previous years, in large part because the
primary data base for occupational employment
changed from the decennial census and the Current
Population Survey to the Occupational Employment
Statistics (OES) Surveys. Procedures had to be modi­
fied with the change in data base largely because the
new data base resulted in a shorter historical series and
because of changes in occupational and industry clas­
sifications. As a result of these changes, the size of the
matrix in the 1978-90 projections increased to 1,678 de­
tailed occupations in 378 industries (primarily the 3-dig­
it SIC level detail) from 377 occupations and 201 in­
dustries in the 1970 census based-matrix.

Base year estimates. Data on occupational employment
of wage and salary workers were derived from the OES
surveys for all industries except agriculture and private
households, which are not included in the OES survey
program, and education, which is included but for which
data were not yet tabulated when the matrix was de­
veloped. The OES surveys are conducted by mail from
a sample of employers in each industry. They are con­
ducted on a 3-year cycle—manufacturing industries 1
year and nonmanufacturing industries divided in the
other 2 years of the cycle. To develop occupational
employment estimates for 1978, the occupational staff­
ing patterns from the most recent OES survey data for
each industry were applied to 1978 estimates of total
wage and salary employment in that industry. The Bu­
reau’s Federal-State cooperative establishment survey
(CES) was the source of the annual average industry
employment. The 1978 staffing patterns were based on
OES surveys of manufacturing industries in 1977; non­
manufacturing, except trade, transportation, communi­
cation, and public utilities industries and State and lo­
cal government, in 1978; and trade and regulated in­
dustries and State and local governments in 1979.
In some industries, employment data in some detailed
occupations were not collected in the OES surveys be­
cause the numbers were too small to be measured ac­
curately and because the survey questionnaire in each
industry was limited to 200 occupations found in that
industry. To develop total employment estimates for
each occupation not included in a survey questionnaire,
a procedure was used whereby detailed occupational
employment could be disaggregated from the appropri­
ate survey residual that included the detailed occupa­
tion. Data collected in the 1970 census provided the
raw data to disaggregate the survey residuals.
In developing the procedures for preparing the QESsurvey-based matrix, a decision was made to use the
disaggregation procedure only for occupations for
which OES survey data were believed to account for
at least 90 percent of total wage and salary worker em­
ployment in the occupation. As a result of this decision,
about 400 OES survey occupations were collapsed into

0®¥el@piing bas® year emptoymeoit ©staates and
projections
Separate estimates of current employment were de­
veloped for wage and salary workers, self-employed
workers, and unpaid family workers. Data on wage and
salary worker occupational employment were devel­
oped in an industry-occupational matrix format. Esti­
mates of occupational employment of self-employed and
unpaid family workers were developed at the total (all­
industry) level only. They were added to the total of
wage and salary workers to derive total employment
by detailed occupation for the entire economy. The
method used required the development of base year
employment estimates and then the projections.



27

year. These initially developed mechanical projections
were then reviewed in detail for consistency with
knowledge about technological change and other fac­
tors affecting the occupational composition of indus­
tries. Changes in the ratios developed through analyti­
cal judgments were placed in an updated matrix which
was iterated to force it to add to 100 percent in each
industry. The final step in the procedure was to apply
the projected staffing pattern to projected industry em­
ployment totals.

residuals in the OES-survey-based matrix. The disag­
gregation procedure was used, however, to estimate
employment in selected industries for 200 occupations.
The proportion of total national employment estimated
through the procedure was less than 4 percent.
Total wage and salary worker employment in the
agriculture and private household industries was devel­
oped from data in the Current Population Survey. These
data are not strictly comparable with data developed
in the CES. The CPS is a count of persons where each
person is counted once in his or her primary job; the
CES and OES are counts of jobs and a person is counted
in all jobs he or she holds. Also, in the CPS, data in­
clude workers only 16 years of age and older. In the
CES and OES, workers younger than 16 may be in­
cluded because the data are based on payroll records.
Workers on unpaid absences are counted in the CPS,
but excluded from the CES.
The occupational distributions of wage and salary
workers in the agriculture and private household in­
dustries were based on the 1978 census-based matrix.
Those estimates were based on 1970 census data mod­
ified by 1971-78 CPS trends in large occupations in
these industries. Since the occupational configuration
of the matrix was based on the OES survey classifica­
tion scheme, the 1978 census matrix employment data
for 377 detailed occupations were distributed into the
1,678 detailed occupations in the OES-based matrix. In
this procedure, CPS data were generally used as control
totals, which were distributed into appropriate detailed
OES-survey-matrix occupations. This distribution was
based on established relationships between the Census
and OES occupational classifications. Many analytical
judgments were necessary to establish relationships for
many occupations because a perfect match between one
or more OES and one or more CPS occupations was
not always possible.
The initial 1978 matrix, which provided occupation­
al employment by industry developed through the pro­
cedures indicated above, was reviewed in detail on a
cell-by-cell basis. The focus of the review was on the
estimates generated through the disaggregation proce­
dure. A procedure was used to update computer gen­
erated estimates where necessary. In the review, virtu­
ally no detailed occupational cells derived from staff­
ing patterns based on OES-survey data were changed,
except for data in residual categories to which data
were either added or subtracted as needed because of
changes in cells for detailed occupations resulting from
disaggregation procedures.

Difficulties encountered using the OES survey
The first step in developing the 1990 projections for
employment covered in the OES surveys was to devel­
op data for the last two OES survey rounds for each
industry to use as a base for developing trends in ratios.
The objective was to compile national data for each
occupation in each industry from one survey round to
the next. However, many difficulties were encountered
in this procedure because of changes between the last
two survey rounds in industry definitions, occupation­
al changes on survey forms, and geographical coverage.
Industry definition. Periodically the Standard Industri­
al Classification System used as the basis for survey
universes is changed. For the last two OES survey
rounds providing data for the 1978-90 matrix, several
industries were affected by an SIC change. As a result,
trends could not be developed because data were not
comparable. In these cases, the data from the last sur­
vey round were held constant at the 1978 level in 1990
for the initial projected matrix. Trends were developed
only in industries in which 95 percent or more of em­
ployment was comparable in the 1967 and 1972 SIC
revisions.
Occupational changes on survey forms. Between the last
two survey rounds, definitions were changed for sev­
eral survey occupational categories. When occupations
were added, trends could not be developed for these
occupations because data for two points in time were
not available. Furthermore, the category in which the
occupation had been included in the previous round
could not be projected because of inconsistent defini­
tions. Similar situations resulted when occupations were
deleted from the survey.
Geographical coverage. The OES survey has been con­
ducted since 1971 as a Federal-State cooperative pro­
gram. All States are not in the program and the num­
ber in each survey round has changed. Since 1977, BLS
has developed national data by surveying the nonpar­
ticipating States as a whole with funds provided by the
National Science Foundation. Because national data
were not available for the last two survey rounds in
any industry, data from States that participated in both
surveys for each industry were summed and used as a

Projections. The basic procedure for projecting occu­
pational employment was to develop data on past trends
of the proportions of employment in each industry re­
presented by each detailed occupation and extend this
trend through an extrapolation technique to the target



28

proxy for national data. The number of States in each
survey round providing data used in developing trends
to 1990 was as follows: Manufacturing, 1974 and 1977,
27; trade, 1975 and 1978, 19; and other nonmanufactur­
ing, 1975 and 1978, 29. The development of trends,
therefore, excluded some States that may have had sig­
nificant employment in a specific occupation. In devel­
oping projections in the future, this weakness will be
eliminated as national data will become available for
two points in time beginning with the results of the
1980 survey.

Projecting the ratios in OES survey industries
In projecting occupational staffing patterns of indus­
tries in previous projection cycles, decennial census data
were extrapolated into the future based on decade-todecade changes. Considerable analysis and review to
identify the factors that caused changes in staffing pat­
terns resulted in many changes to the mechanically de­
veloped extrapolated ratios. A review of the 1975 oc­
cupational projections done just prior to the develop­
ment of the most recent 1990 projections (based on OES
survey data) indicated that the major cause of errors in
the projections was incorrect projections of occupa­
tional ratios. An intensive effort, therefore, was devot­
ed to research on methods of projecting OES-surveybased staffing patterns.
In general, the research tested the merits of a varie­
ty of extrapolation techniques. The results of these tests
indicated that first approximations of the projected ra­
tios could be developed better, on average, through an
exponential method than other extrapolation techniques.
In this method, an annual rate of change was estimated
for the historical period, and this rate was applied to
the most current year’s slot to derive the projected year.
There was, however, a question whether this method
produced any better results than using current patterns
in the projected matrix. In the tests, use of current staff­
ing patterns in the projected years generally produced
better results, on average, than any extrapolation tech­
nique. However, for large occupations that were" not
affected by any problems related to changes in survey
definitions or SIC problems, the exponential extrapola­
tion technique generally outperformed the constant ra­
tio estimates. Since the tests were performed for data
over a short period of time and the exponential meth­
od worked well for large occupations representing a
very significant proportion of employment, this tech­
nique was chosen. However, the research also con­
firmed earlier convictions that ratios developed through
mechanical means must undergo intensive analytical
review.
To overcome the problems of comparability of sur­
veys, only those occupations that did not change defi­
nitions between the last two surveys and were found
in industries that did not change SIC content were pro­



29

jected through the exponential extrapolation technique
to 1990. All other ratios were held constant at the 1978
level in the initial 1990 matrix.
The initial projected staffing pattern in each industry
was then applied to projected industry employment to­
tals for wage and salary workers to develop the pre­
liminary 1990 occupational projections. These projec­
tions were analyzed in detail over a 6-month period
based on studies of occupations and industries conduct­
ed during preparation of the Occupational Outlook Hand­
book. Factors considered included changes in produc­
tion methods, technological changes affecting occupa­
tional mix, changes in product mix of industries, changes
in average size of establishments in industries, and oth­
er economic factors affecting specific occupations.
In addition, some occupations were projected inde­
pendently of the matrix based on the relationship of the
occupation to more closely associated variables. For
example, projections of elementary and secondary
school teachers were based on estimates of the schoolage population and pupil-teacher ratios. Projections de­
veloped in this manner were placed in the matrix and
adjustments in the staffing patterns for other occupa­
tions were made when necessary.
In the analytical procedure, relationships were estab­
lished between occupations in the census-based matrix
and the OES-survey-based matrix to obtain the benefit
of a longer time series. Changes were made in the ini­
tial projected OES matrix based on the analysis de­
scribed above, and an iteration procedure was used to
assure that the staffing patterns in each industry added
to 100 percent. The resulting ratios were applied to to­
tal projected employment of wage and salary workers
in each industry to develop the final occupational pro­
jections of wage and salary workers.

Wag© and salary workers, rt®n°GES survey
industries
Developing past trends. For the agriculture, private
households, and education industries, past trends in oc­
cupational distribution were developed based on data
in the 1970 decennial census and Current Population
Surveys conducted during the 1970’s. Since 1971, the
occupational configuration of this data series was that
used in the 1970 census and, therefore, different from
the OES survey configuration that was used in the
1978-90 OES-survey-based matrix. However, there was
no need to adjust data within the historical series since
the data were comparable for each year from 1971 to
1978. Some adjustments were made to the staffing pat­
terns in education based on limited available OES sur­
vey data.

Projecting the ratios
The initial projected 1990 ratios for these two indus­
try sectors were taken directly from the 1990 census-

Data for self-employed and unpaid family workers
were developed only at the all-industry level because
of the unreliability of these data at the detailed indus­
try level.

based matrix developed by the Bureau in 1978. These
projected ratios were analyzed based on data that be­
came available after the earlier matrix was developed
and a few ratios were adjusted. The census-based oc­
cupational distribution was converted to the OES sur­
vey distribution based on the same distribution of cen­
sus categories to OES survey categories used to devel­
op the 1978 wage and salary base-year matrix described
above.
The projected ratios were then applied to the 1990
industry projections developed for the 1978-90 OESsurvey-based matrix. The resulting employment and ra­
tios were reviewed in detail in the same manner as the
wage and salary workers for OES-survey-based indus­
tries. Changes in patterns that resulted from this review
were incorporated in the final matrix.

Projections. To develop the projections, the percent
distributions of self-employed and unpaid family work­
ers by occupation from the 1971-78 CPS data were ex­
trapolated to 1990 and forced to add to 100 percent. A
distribution of these proportions was made to OES sur­
vey occupations based on the distribution of 1978 data.
These distributions were then reviewed and changes
made where deemed appropriate. The resulting distri­
bution was applied to projected totals for self-employed
and unpaid family workers developed through the Bu­
reau’s economic model. The resulting projected em­
ployment totals were reviewed for consistency with in­
formation developed in the course of other occupation­
al research, and changes were made where necessary.

Self-employed and unpaid family workers
Base-year estimates. Estimates of self-employed and
unpaid family workers by occupation were based on
1978 annual averages as in previous census-based ma­
trices since no alternative data series exist. Similar to
the procedure used for wage and salary workers in the
agriculture and private household industries, the em­
ployment data in the detailed census matrix occupations
were distributed to the 1,678 occupations in the OESsurvey-based matrix. In general, CPS data were used
as control totals that were distributed to appropriate
detailed OES survey matrix occupations falling within
the CPS definition. The distributions were based large­
ly on the distribution of OES-survey-based wage and
salary employment unless other data were available or
analytical judgment indicated that this procedure re­
sulted in incorrect data. For example, certain jobs found
only in government often fell into a broader CPS cat­
egory which contained self-employed and unpaid fam­
ily workers. In such cases, a distribution was not made
based on the wage and salary worker distribution.




Total occupational employment
To develop total employment estimates by occupa­
tion, employment of wage and salary workers was added
to totals of self-employed and unpaid family workers.
Unlike previous estimates of total national employment,
the totals represented the number of jobs by occupa­
tion, not the number of persons employed by occupa­
tion.2 These totals are different because one person may
6
have more than one job. The difference between the
number of jobs and number of persons employed in
1990 is roughly 7 percent.
26The total number o f jobs was even higher than the number shown
because persons who were self-employed as a secondary job were in
the wage and salary worker totals and not in the self-employed to­
tals. They would report only their primary job in the CPS, which
was the source o f data on the self-employed. Similarly, wage and
salary workers in agriculture and private households were only
counted once even if they held more than one job because the CPS
was also the source o f data for these industries.

30

Chapter 8. Planned Changes
in the Projection System

Labor lore© supply model
Research is currently underway to develop a labor
force supply model. The objective is to examine the
effect on labor force participation of economic and de­
mographic factors in order to provide a behavioral
model as an alternative future basis for deriving these
projections.
The procedures being utilized involve estimation of
labor force participation equations for various age, sex,
and marital status cohorts. Specifications of these equa­
tions include wage, income, education, presence of
children, and other explanatory variables. The data are
derived primarily from the March Current Population
Survey and are organized by geographic region in or­
der to form a body of pooled time series-cross section
observations. A typical labor force participation equa­
tion includes such variables as the unemployment rate,
wages, nonearned income, industrial mix, taxes, and ec­
onomic-demographic variables designed to capture the
movements in labor force behavior of the various co­
horts under examination.
In general, preliminary empirical results confirm
many expectations about the effect of economic and
demographic influences on labor force behavior. Sev­
eral variables, such as wages, industry mix, and the
population cohort are statistically important determi­
nants of labor force variation. Other variables, such as
presence of children, schooling, and pensions, contrib­
ute substantially to the explanation of labor force par­
ticipation for specific population groups. These findings
will facilitate an analysis of the underlying reasons for
developments in labor force behavior.

Sndustry-oeeupational employment
With the merging of the labor force, economic, and
occupational projection programs, efforts began to com­
puterize the linkages and to introduce explicit feedbacks
between the respective programs. Currently, the de­
tailed economic projections of industry labor demand
are the determinant of occupational demand projec­
tions. Should the initial industry employment projec­
tions be inconsistent with either the projected staffing
patterns or total occupational projections, the projec­
tions would be reviewed and the inconsistency elimi­
nated if necessary. This is usually the approach when



31

the demand for a particular occupation is unique to an
individual industry.
In line with this approach, a respecification of the
labor demand equations for individual industries is un­
der consideration. The current labor demand equations
are based on a general specification: An industry’s em­
ployment is related to the industry’s output plus tech­
nical trends and capacity. Because of the final demand
and input-output projections, this output projection
should embody shifting demographic, energy, and gov­
ernment expenditure trends. However, for selected in­
dustries, such as education or medical services, occu­
pational surpluses or shortages visibly affect the indus­
try’s projected employment as much as the demand fac­
tor. The surplus or shortage of people to fill specific
occupations should affect relative wages, and these, in
turn, should encourage either capital/labor substitution
or technical innovations. Research is now underway to
deal with such occupational supply phenomena.
Job openings

Projections of occupational employment require
more detailed information about the number of people
expected to have jobs at some future time. By compar­
ing projected with current employment data, the num­
ber of job openings resulting from growth in an occu­
pation, if employment increases—or the number lost, if
employment declines—can be determined. While use­
ful, employment-change data alone do not identify the
total number of jobs available. Total job-openings data
are an obvious part of the assessment of supply and de­
mand relationships.
There are several sources of job openings in an oc­
cupation: (a) Increase in employment due to the econ­
omy’s growth, and (b) the need to replace individuals
who transfer to another occupation or who retire, die,
or leave the labor force for some other reason. The la­
bor force, macro, and industry models and the indus­
try-occupation matrix, described earlier, were used in
projecting employment and estimating growth. In the
past, working-life tables were used to estimate replace­
ment needs resulting from death and labor force sepa­
rations. These replacement needs estimates had limita­
tions, however, because:

ment needs, but are of special interest because they per­
mit comparisons of matched and retrospective data for
January 1977-78. These comparisons fostered addition­
al confidence in the reliability of merged CPS matched
and retrospective data about movements into, out of,
and between occupations. As a result, the merged and
retrospective data will be used in the preparation of the
1982-83 editions of the Occupational Outlook Handbook
and Occupational Projections and Training Data to esti­
mate replacement needs, to document descriptions of
occupational movements already being presented, and
to add information not currently available. For exam­
ple, the data will document information about the large
number of jobs for food counter workers resulting from
the need to replace young people who temporarily leave
the labor force. By using merged CPS matched and
retrospective data about occupational movements and
by describing how jobs are created and filled, informa­
tion about employment opportunities is expected to im­
prove significantly.

1. The estimates of labor force separations were
based on working- life tables that pertained to the
entire population and, therefore, did not reflect ac­
tual differences in patterns among occupations.
2. The estimates did not include all persons who
left the labor force temporarily.
3. The estimates did not include job openings re­
sulting from occupational transfers.
Because replacement needs are a far more significant
source of job openings than economic growth in almost
all occupations, improved data have been the focus of
recent research efforts. Data are being developed from
the Current Population Survey on the need to replace
individuals who transfer to another occupation, retire,
die, or leave the labor force for some other reason. The
BLS publication Measuring Labor Force Movements: A
New Approach. (Report 581) explained the need for im­
proved data about replacement needs and described
preliminary efforts to develop this information.
The longitudinal character of the CPS results in data
being collected for the same individual in surveys 12
months apart. By tabulating occupational and labor
force status data, annual data on movements into and
out of occupations are obtained. Because individuals
are identified by matching household, age, race, and
sex information, these longitudinal data are termed CPS
matched data.
However, CPS matched data overstate occupational
changes. To overcome this weakness, CPS retrospec­
tive data from supplemental questions on occupational
mobility were combined with CPS matched data to es­
timate occupational transfers. The longitudinal data
which result from combining CPS matched and CPS
retrospective data are termed merged CPS matched and
retrospective data.
Since the 1974-75 data were published in Report 581,
1977-78 CPS matched and retrospective data have been
developed. These more recent data are not only of in­
terest for the information they provide about replace­




Evaluation of projections
As indicated, for over 15 years BLS has developed
a series of labor force, economic, and occupational pro­
jections. The first set of these comprehensive projec­
tions were developed in 1965 for the year 1970. Subse­
quent projections were developed for 1975, 1980, 1985,
and 1990. Recent evaluations of 1975 projections in­
clude, “An Evaluation of BLS Projections of 1975 Pro­
duction and Employment,” by Paul Christy and Karen
Horowitz (Monthly Labor Review, August 1979) and
“Evaluating the 1975 Projections of Occupational Em­
ployment,” by Max Carey (Monthly Labor Review, June
1980). Work has recently begun on evaluating the 1980
projections. This work involves assembling the concep­
tual and benchmark changes which might affect the
differences between actual and projected data and as­
sembling the methodologies of each 1980 projection to
determine the sources of errors.

32

Appendix A. Labor Force Projection Scenarios

Tab§® A-1. Tftra® alternative projection scenarios for women
Measured rate of increase
Age

High growth1

Low growth

Middle growth

1960 to 1979

1972 to 1979

White
16 and 1 7 ........................... SR: RG
18 and 1 9 ........................... SR: RG

Short-run estimate
Short-run estimate

LR
LR

1.20
.81

1.30
1.31

SR
SR
SR
SR
SR

_
-

1.42
2.55
2.37
1.91
1.62

SR
SR
SR
SR

.64
.32
.11
.25

.92
.40
.08
-.23

-.22
-.15
-.05

-.14
-.08
-.12

0.29
.06

0.75
.59

20 to 2 4 ..............................
25 to 2 9 ..............................
30 to 3 4 ....... .......................
35 to 3 9 ..............................
40 to 44 ..............................

SR:
SR:
SR:
SR:
SR:

RG
RG
RG
RG
RG

LR:
LR:
LR:
LR:
LR:

45
50
55
60

LR:
LR:
LR:
LR:

RG
RG
RG
RG

Long-run
Long-run
Long-run
Long-run

to
to
to
to

49 ..............................
54 ..............................
59 ..............................
6 4 ..............................

Relative growth1
Relative growth1
Relative growth1
Relative growth1
Relative grow th1
estimate
estimate
estimate
estimate

65 to 6 9 .............................. Constant
70 to 7 4 .............................. Constant
75 and o v e r........................ Constant

Half of LR
Half of LR
Half of LR

SR
SR
SR

16 and 1 7 ........................... SR: RG
18 and 1 9 ........................... SR: RG

Short-run estimate
Short-run estimate

LR
LR

20
25
30
35
40

to
to
to
to
to

24 ..............................
2 9 ..............................
3 4 ..............................
39 ..............................
44 ..............................

SR:
SR:
SR:
SR:
SR:

RG
RG
RG
RG
RG

LR:
LR:
LR:
LR:
LR:

45
50
55
60

to
to
to
to

49 ..............................
54 ..............................
59 ..............................
6 4 ..............................

LR:
LR:
LR:
LR:

RG
RG
RG
RG

Long-run
Long-run
Long-run
Long-run

-

Black and other

65 to 6 9 .............................. Constant
70 to 74 .............................. Constant
75 and o v e r........................ Constant

Relative
Relative
Relative
Relative
Relative

growth
growth
growth
growth
growth

SR
SR
SR
SR
SR

1
'
'
1
'

-.16
-.18
-.22
-.24

.93
.26
-.18
.05

SR
SR
SR

Half of LR
Half of LR
Half of LR

-

.92
1.38
2.13
1.32
.95

SR
SR
SR
SR

estimate
estimate
estimate
estimate

1 Different from the 1978 projection.
NOTE: LR denotes estimated over the 1960 to 1979 period; SR




_

-.22
-.27
-.12

-.11

-

-.42
-.16

denotes estimated over the 1972 to 1979 period; and RG denotes the use
of a relative growth model.

33

Table A-2. Three alternative projections scenarios for men
Measured rate of increase
Age

High growth

Low growth

Middle growth

1960 to 1979

1972 to 1979

White
16 and 1 7 ........................... SR
18 and 1 9 ........................... SR
20 to 24 .............................. SR

Average of LR & SR
Average of LR & SR
Average of LR & SR

LR
LR
LR

0.66
.51
.01

0.88
.74
.28

25 to 2 9 .............................. LR: Up
30 to 34 .............................. LR: Up
35 to 39 .............................. LR: Up

Long-run estimate
Long-run estimate
Long-run estimate

SR
SR
SR

-.10
-.36
-.20

.05
.20
.14

45 to 49 .............................. Constant
50 to 54 .............................. Constant

Long-run estimate
Long-run estimate

SR
SR
SR

- 12
-.17
-.31

01
-.12
-.06

Half
Half
Half
Half
Half

SR
SR
SR
SR
SR

-.27
-.55
-.60
-.26
-.31

-.75
-1.47
-1.80
-.56
-.32

-0.67
-.23
-.74

-

55
60
65
70
75

to 59 ..............................
to 64 ..............................
to 69 ..............................
to 74 ..............................
and o v e r........................

Constant1
Constant1
Constant1
Constant1
Constant1

of
of
of
of
of

LR
LR
LR
LR
LR

Black and other
16 and 1 7 ........................... Convergence
18 and 1 9 ........................... Convergence
20 to 2 4 .............................. Convergence

LR2
LR2
LR2

25
30
35
40
45
50

to
to
to
to
to
to

..............................
..............................
..............................
..............................
..............................
..............................

Convergence
Convergence
Convergence
Convergence
Convergence
Convergence

Long-run
Long-run
Long-run
Long-run
Long-run
Long-run

estimate
estimate
estimate
estimate
estimate
estimate

SR
SR
SR
SR
SR
SR

-.34
-.23
-.34
-.34
-.44
-.60

.23
.01
.23
.23
.08
.02

55
60
65
70
75

to 59 ..............................
to 64 ..............................
to 69 ..............................
to 74 ..............................
and o v e r........................

Convergence
Convergence
Constant
Constant
Constant

Long-run estimate
Half of LR
Half of LR
Half of LR
Half of LR

SR
SR
SR
SR
SR

-.56
-.66
-.56
-.25
-.14

-.59
-.71
-.71
-.57
-.14

1
2
rate
3
rate

29
34
39
44
49
54

Different from the 1978 projection.
Indicates the use of the higher 95-percent confidence
of change; this reflects data limitations for young black
Indicates the use of the lower 95-percent confidence
of change; this reflects data limitations for young black




LR3
LR3
LR3

interval for the
men.
interval for the
men.

34

NOTE: LR denotes estimated over the 1970 to 1979 period; SR
denotes estimated over the 1972 to 1979 period; RG denotes the use of
a relative growth model, and convergence indicates moving the black
labor force participation to the white rate in the year 2000.

Appendix B. i¥3acr©@con@mie
Model” Equations, Identities,
and Variables

(Abbreviations for variables are explained at the end of the
appendix.)
Supply sector

1. ECLF = LFC * (1.0 -U )
2.

ECJOBS = -0.751 + 1.078 ECLF - 0.199 U - 0.344 DM59 + 0.303 DM67 - 0.37 DM72
(-0 .6 )
(51.1)
(-4 .5 )
(-1 .7 )
(1.2)
(-1 .3 )

R-squared
D.W.
3.

Estimation period:

1947-79

EMPE/POP = -0.003 + 0.098 PUREC/POP
(-8 .6 )
(75.2)
R-squared
D.W.

4.

= 0.999
= 1.458

= 0.996
= 1.061

Estimation period:

1952-79

ln(EMPNE/PQP) = - 4.469 + 1.921 ln(PURNEC/PQP) - 0.186 ln(URBAN/POP)
(-14.2) (9.5)
(-0 .3 )
R-squared
D.W.

= 0.988
= 0.462

Estimation period:

1952-79

5.

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

6.

AAHF = 1965.150 - 13.656 U - 9.037 U (t- 1) + 27.839 FPOP + 7.623 TIME
(9.9)
(-2 .1 )
(-1 .3 )
(3.3)
(1.4)
R-squared
D.W.

7.

= 0.877
= 0.960

Estimation period:

1948-79

A A H N F = 2392.730 - 7.728 U + 4.661 U (t--1) - 7.764 FLFPR - 3.365 TIME
(54.2)
(-5 .5 )
(-4 .8 )
(-8 .1 )
(4.7)
R-squared
D.W.




= 0.994
= 1.950

Estimation period:

1948-79

35

8. MHF = AAHF * EFJBS
9.

MHNF = AAHNF * ENFJBS

10. MHIF = MHF/MHF(1972)
11.

MHINF = MHNF/MHNF(1972)

12. KEF = K E F (t-l) + IEF - DEF
13. KENF = K E N F (t-l) + IENF - BENF
14. KSF = K S F (t-l) + ISF - DSF
15.

KSNF = K SN F (t-l) + ISNF - DSNF

16. KINV = K IN V (t-l) + IVCHG
17.

KHS = K H S (t-l) + IR - ORES

18.

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

19.

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

20.

ln(GNPFC/IKADJF) = 2.881 + 0.0002 U * U + 0.450 !n(MHIF/IKABJF) + 0.013 T29
(27.7) (2.8)
(11.3)
(5.5)
R-squared
D.W.

= 0.957
= 1.453

Estimation period:

1929-40, 1946-79

21. ln(GNPNFC/IKADJNF) = 6.065 - 0.0002 U * U + 0.805 ln(MHINF/IKADJNF) + 0.020 T29
(192.1) (-5 .0 )
(22.0)
(31.0)
R-squared = 0.990
=
B.W.
= 0.874
22.

1929-40, 1946-79

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

23.

Estimation period:

Estimation period:

1947-79

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:

1947-79

36

24.

SEREDC = 3.770 + 0.80! (EMPE * 8.288) + 0.219 TIME
(23.0)
(39.6)
(7.1)
R-squared - 0.999
D.W.
= 1.281

25.

Estimation period:

1947-79

SERNEC = -0.707 -1 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:

1947-79

26.

GGP = SERFCC + SERFMC + SEREDC + SERNEC

27.

GNPTC = GNPFC + GNPNFC + GGP

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)
(30.9)
Cochrane/Orcutt RHO = 0.523
R-squared = 0.993
Estimation period:
D.W.
- 1.365

29.

1949-79

CDACE = -10.353 + 0.051 K STK (t-l)
(-24.3)
(125.1)
where KSTK = KEF + KSF + KENF + KSNF
R-squared = 0.998
D.W.
= 0.143

30.

Estimation period:

1947-79

CDACB = -7.089 + 0.036 KSTK(t- 1 ) + 0.007 K ST K D l(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

31.

1947-79

CPTFD = 2.925 + 0.731 TRCP * (CPCDA - CDAKB)
(6.0)
(48.7)
R-squared = 0.989
D.W.
= 0.824

32.

Estimation period:

Estimation period:

1947-79

DIV = -0.424 + 1.067 O lV (t-l) + 0.106 (IFC - IFIX) * DEFI
(-1 .4 )
(57.2)
(3.6)
where IFIX = IEF + ISF + IENF + ISNF




37

R-squared = 0.993
D.W.
= 1.472
33.

Estimation period:

1947-79

IYA = 2.751 - 97.123 ((DGNPP - DGNPP(t- l))/DGNPP(t-1 )) + 0.099 IVCHG - 0.021 K IN V (t-l)
(1.6)
(-3 .3 )
(1.0)
(-1 .6 )
- 20.380 EMBGO
(-7 .5 )
R-squared = 0.890
D.W.
= 3.203

Estimation period:

1948-79

34.

IFK = CPCDA - (CPTFD + CPTST)

35.

UCP = IFK - (CDAKE - CDAKB) - IVA - DIV

36.

CCANCC = 1.787 + 0.025 K H S (t-l) + 0.0002 K H S (t-l) * TIME
(0.4)
(3.7)
(1.1)
R-squared = 0.993
D.W.
= 0.253

Estimation period:

37.

CCANCK = CCANCC * DFNCCA

38.

IBTFD = 6.134
(23.2)

1947-79

4-

0.004 GNPPK + 0.026 TRG * FU + 0.774 DMKW
(2.8)
(8.5)
(2.0)

R-squared = 0.984
D.W.
= 1.470
39.

IBTST = 4.284
(4.1)

4-

IPFD = 1.466
(9.1)

4-

Estimation period:

0.004 (I3Y5Y * DFP)
(10.0)

4-

R-squared = 0.993
Estimation period:
D.W.
= 1.127 41.

1947-79

0.710 (GDSTK 4- SERSTK + TRSTP - G A K )(t-l) - 0.527 U
(107.0)
(-2 .3 )

R-squared = 0.998
D.W.
= 1.223
40.

Estimation period:

1948-79

0.002 (I3Y5Y * D FP)(t- 1) - 0.0004 (I3Y5Y * D FP)(t-2)
(2.8)
(-0 .7 )
1952-79

SICE = 0.431 + 0.529 SICTOT
(3.4)
(167.7)
R-squared = 0.999
D.W.
= 0.376




Estimation period:

1947-79

38

42.

SICU = 0.508 + 0.392 ((CEP + GGP) - SICE) * TRU
(5.0)
(27.3)
R-squared = 0.966
D.W.
= 1.445

43.

1947-79

SICO = 1.187 + 0.900 TRO * CSIC * (CEP + GGP) - SICE) * WB/MFI
(2.2)
(49.8)
R-squared = 0.990
D.W. . = 0.808

44.

Estimation period:

Estimation period:

1947-79

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

45.

SICTOT = SICU + SICO + SICST + SICFD

46.

IPC = -2.325 + 0.019 PI + 0.419 I3M
(-8.7))
(16.3)
(2.6)
R-squared = 0.989
D.W.
= 0.429

47.

Estimation period:

1947-79

PI = GNPTK - CDAKE - CCANCK - IBTFD - IBTST - SD + SLSFD + SLSST - CPIVA
+ (CDAKE - CDAKB) - SICTOT + TRAN + DIV + IPFD + IPST + IPC

48. ln(MFI) = 6.833 + 0.865 ln(1.0 - (U/100.0)) + 1.052 In(GNPTK/(ECLF + EMBLS))
(87.5) (2.3)
(78.2)
+ 1.291 ln((PI + SICTOT - SICE)/GNPTK)
(5.2)
R-squared = 0.998
D.W.
= 1.679
49.

1947-79

PTFD = -5.865 + 0.051 PI + 0.362 PI * TRMFI
(-4 .7 )
(2.9)
(3.8)
R-squared = 0.992
D.W.
= 1.373

50.

Estimation period:

Estimation period:

1947-79

PTST = -4.431 + 0.029 PI + 0.532 P T S T (t-l) - 0.253 TIME
(-2 .5 )
(2.4)
(2.2)
(-1 .9 )
R-squared = 0.996
D.W.
= 1.705




Estimation period:

1947-79

39

51.

DPIK = PI - (PTFD + PTST)

52.

PS = -26.329 + 0.080 DPIK - 0.321 I3Y5Y + 20.070 D FD PI/D FD PI(t-1)
(-0 .8 )
(8.5)
(-0 .3 )
(0.6)
R-squared = 0.959
D.W.
= 1.947

53.

Estimation period:

1947-79

PCEK = DPIK - PS - IPC - PTR

Demand s@©t@r

54.

PCED = -80.295 + 0.190 (PCEC) + 0.293 I R ( t- l) -0.490 U + 59.916 (DPIK/DPIK(t -1 ) ) /
(-3 .3 )
(18.5)
(2.3)
(-0 .9 )
(2.5)
(DFDPI/DFDPI(t -1 )) -1098.710 IPC/DPIK
(-5 .3 )
where PCEC = PCEK/DFDPI
R-squared = 0.999
D.W.
= 1.468

55.

Estimation period:

1947-79

PCEN = 50.886 + 0.319 (PCEC) + 770.141 IPC/DPIK - 0.460 U
(26.7)
(69.5)
(6.0)
(-1 .3 )
where PCEC = PCEK/DFDPI
R-squared = 0.999
D.W.
= 0.964

56.

Estimation period:

1947-79

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

57.

Estimation period:

1947-79

IENF = -7.301 + 0.190 IFC + 0.732 IENF(t- 1 ) + 0.0002 K E N F(t-l) + 118.350 (IFC/(KENF + KSNF)/
(-1 .9 )
(2.9)
(4.2)
(0.01)
(0.8)
U )(t-1) + 0.083 (GNPNFC - G N PN FC (t-l))
(2.7)
R-squared = 0.988
D.W.
= 1.349

58.

Estimation period:

1947-79

ISNF = 0.604 + 0.017 GNPNFC + 0.618 IS N F (t-l)
(0.5)
(2.3)
(3.8)
R-squared = 0.967
D.W.
= 1.161




Estimation period:

1947-79

40

59.

IVCHG = -42.235 + 0.166 (GNPFC + GNPNFC) - 0.424KINV(t-1 ) KINV(t-1 ) + 13.182/U - 1.197 TIME
(-7.1)
(6.8)
(-7.0)
(1.2)
(-2.8)
R-squared = 0.820
D.W.
= 1.742

60.

1947-79

IR = -68.090 - 4.921 I3Y5Y + 1.448 HOUSE + 4.643 DPIC/HOUSE/HOUSE

(-7 .9 )

(-4 .1 )

R-squared = 0.945
D.W.
= 1.381
61.

Estimation period:

(5.7)

Estimation period:

(3.8)
1929-40, 1946-79

M = -6.165 + 0.027 B P IC (t-l) + 0.033 (DPIC - D P IC (t-l)) + 0.383 ((DEFM/DFDPI)

(-1 .9 )

(2.0)

(1.1)

(0.3)

- (DEFM(t- l)/DFD PI(t-!))) + 5.123 CPSQR + 0.841 M ( t- l)
(2.1)
(7.9)
R-squared = 0.996
D.W.
= 2.052

Estimation period:

1947-79

62.

PURFDC = SERFMC + SERFCC + GDFDC

63.

PUREC/POP = -0.184 + 0.071 (((GNPFC + GNPNFC)/POP)(t-1 )) + 0.513 (GAG * GPCED/POP)
(-7 .7 )
(13.3)
(1.3)
+ 0.474 SCHL/POP
(5.0)
R-squared = 0.991
D.W.
= 1.663

64.

Estimation period:

1953-79

PURNEC/POP = -0.089 + 0.085 ((GNPFC + GNPNFC)/POP)(t - 1 ) + 0.607 (GAC *
(-1 .4 )
(4.4)
(2.1) (0.9)
(1.0 - GPCED)/POP) + 0.003U
R-squared = 0.973
D.W.
= 0.538

Estimation period:

1953-79

Priee/wage s@et@r

65.

In(DGNPP) = 0.560 + 0.867 ln(ALUL(t - 1)) + 0.132 ln(WPICR) -0.039 ln(U)
(17.0)
(40.7)
(5.7)
(-2 .1 )
R-squared = 0.994
D.W.
= 1.214

66.

Estimation period:

1948-79

CEPM = 4.994 + 60.286 (((GNPFC + GNPNFC)/(MHF + MHNF)) - ((GNPFC + GNPFC)/
(MHF + MHNF))(t—1))/((GNPFC + GNPNFC)/(MHF + MHNF))(t - 1) + 119.426 ((DFDPI
- DFDPI(t —1))/OFOPI(t —1)) -0.799U
(-4 .5 )




41

(1L8)

R-squared = 0.860
D.W.
= 2.091

Estimation period:

67.

CPH = C P H (t-l) * CEPM

68.

1947-79

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
Estimation period:
D.W.
= 1.661

72.

DFIV = 0.212 + 0.810 DGNPP
(1.8)
(5.5)
Cochrane/Orcutt RHO = 0.159
R-squared = 0.611
Estimation period:
D.W.
= 1.890

73.

1948-74

DEFX = 0.003 + 0.491 DGNPP + 0.536 DEFM
(0.2)
(12.8)
(23.2)
Cochrane/Orcutt RHO = 0.953
R-squared = 0.997 Estimation period:
D.W.
= 1.991

76.

1948-74

(DFDPI - DFDPI(t - l))/DFDPI(t - 1) = 0.003 + 0.901 ((DGNPP - DGNPP(t - l))/DGNPP(t - 1))
0.7)
09.7)
Cochrane/Orcutt RHO = 0.189
R-squared = 0.947 Estimation period:
D.W.
= 1.558

75.

1948-74

DEFRI = -0.272 + 1.229 DGNPP
( - 1.6)
( 12.2)
Cochrane/Orcutt RHO = 0.968
R-squared = 0.993
Estimation period:
D.W.
= 1.836

74.

1948-74

1948-74

DFGDS = -0.584 + 1.529 DGNPP
(-6 .7 )
(23.2)
Cochrane/Orcutt RHO = 0.953
R-squared = 0.998 Estimation period:
D.W.
= 2.096




1948-74

42

77.

DFGDF = -0.016 + 1.021 DGNPP
(-0 .8 ) (38.8)
Cochrane/Orcutt RHQ = 0.260
R-squared = 0.990
Estimation period:
D.W.
= 1.651

78.

DFCCA = 0.028 + 0.818 DEFI + 0.163 DGNPP
(1.5)
(9.4)
(1.8)
Cochrane/Orcutt RHQ = 0.872
R-squared = 0.999
Estimation period:
D.W.
= 1.571

79.

1948-74

1948-74

DFNCCA = -0.014 + 0.284 DFDPI + 0.755 DGNPP
(-0 .4 )
(0.5)
(1.2)
Cochrane/Orcutt RHQ = 0.789
R-squared = 0.996
Estimation period:
D.W.
= 1.124

1948-74

80.

DEFSFC = DEFSFC(t —1) * (percent change DFDPI)

81.

DEFSFM = DEFSFM(t - 1 ) * (percent change DRDPI)

82.

DEFSS = DEFSS(t - 1) * (percent change DRDPI)

83.

DEFGA = DEFGA (t - 1) * (percent change 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 4- PUREC + PURNEC

86.

GAP = GNPTC - GNPDC




43

of variables
(* denotes an exogenous variable)

DEFX

Explanation

AAHF
AAHNF
ALUL
CCANCC
CCANCK
CDACB

CDACE
CDAKB
CDAKE

CEP
CEPM
CPCDA

CPH
CPIVA
CPSQR
CPTFD
CPTST*
CREEP2*

CSIC*
DEF*
DEFGA
DEFI
DEFM*
DEFRI
DEFSFC
DEFSFM
DEFSS

DENF*
DFCCA

Average annual private farm manhours,
establishment basis
Average annual private nonfarm man­
hours, establishment basis
Unit labor cost
Noncorporate capital consumption allow­
ances, constant dollars
Noncorporate capital consumption allow­
ances, current dollars
Corporate depreciation allowances, con­
stant dollars, book value definition,
without capital consumption adjust­
ment (CCA)
Corporate depreciation allowances, con­
stant dollars, with CCA
Corporate depreciation allowances, cur­
rent
dollars,
without
CCA
(CDACE*DFCCA)
Corporate depreciation allowances, cur­
rent
dollars,
with
CCA
(CDACE*DFCCA)
Compensation of employees, private
economy
Percent change in current dollars com­
pensation per hour in the private sector
Corporate profits plus capital depreciation
allowance minus inventory valuation
adjustment
Private compensation per hour
Corporate profits plus inventory valuation
adjustment (CPCDA+ IVA-CDAKE)
Capacity pressure, defined as (((actual
GNP/potential GNP)-0.98)*2)
Federal corporate profits taxes
State and local (S&L) corporate profits
taxes
Variable to account for unwarranted
grade enhancement during the 1947-69
period
Social security coverage as a percent of
paid employment
Discards of producer durable equipment
(PDE), farm
Deflator for Federal grants-in-aid
Fixed nonresidential investment deflator,
1972=100

DFDPI
DFGDF
DFGDS
DFIV
DFNCCA
DFP
DGNPP
DGNPT
DIV
DMKW*
DM59*
DM67*
DM72*
DPIC
DPIK
DRES*
DSF*
DSNF*
EC JOBS
ECLF
EF*
EFJBS*
EMBGO*
EMBLS*
EMIPA*

EMPE
EMPNE
ENFJBS

Imports of goods and services deflator,
1972=100
Residential structures deflator, 1972=100
Federal civilian compensation deflator
Military compensation deflator
S&L compensation deflator




EXPRT*
FLFPR*
FPOP*
FU*

44

Exports of goods and services deflator,
1972=100
Discards of PDE, nonfarm
Corporate
consumption
allowances
deflator
Disposable personal income deflator
Federal purchases less compensation de­
flator, 1972=100
S&L purchases less compensation defla­
tor, 1972=100
Change in business inventories deflator,
1972=100
Noncorporate consumption allowances
deflator
Federal debt proxy
Private GNP deflator, 1972=100
Total GNP deflator, 1972=100
Net corporate dividend payments
Korean War dummy = 1 for 1951-53
Establishment survey definitional shift =
1 from 1959
Establishment survey definitional shift =
1 from 1967
Establishment survey definitional shift =
1 from 1972
Disposable personal income, constant dol­
lars (DPIK/DFDPI)
Disposable personal income, current
dollars
Discards of residential structures
Discards of structures, farm
Discards of structures, nonfarm
Civilian employment, establishment basis
Civilian employment, labor force basis,
age 16 and over
Average number of full- and part-time
Federal
Government
general
employees
Private farm employment, establishment
basis
Oil embargo dummy = 1 in 1973-74
Level of the Armed Forces, BLS basis
Military employment including reserve
forces, national income and product ac­
counts (NIPA) basis
S&L government
employment
in
education
S&L government
employment
in
noneducation
Private nonfarm employment, establish­
ment basis
Exports of goods and services
Female labor force participation rate, age
16 and over
Total farm population
Motor fuel usage

GAC*
GAK
GAP
GDFDC*
GDSTK

GNPDC
GNPFC
GNPNFC
GNPPK
GNPTC
GNPTK
GPCED*
HOUSE*
IBTFD
IBTST
IEF*
IENF
IFC
IFK
IKF
IKADJF
IKADJNF
IKNF
IPC
IPFD
IPST*
IR
ISF*
ISNF
1VA
IVCHNG
DM*
DY5Y*
KEF
KENF
KHS
KINV
KSF
KSNF
LFC*
M

MFI
MHF

Federal grants-in-aid to S&L government,
constant dollars
Federal grants-in-aid to S&L government,
current dollars (GAC*DEFGA)
Supply GNP less demand GNP, constant
dollars
Federal purchases of goods and services
less compensation, constant dollars
S&L government purchases of goods and
services less compensation, current dol­
lars ((PUREC + PURNECMSEREDC +
SERNEC)) *OFGDS
Demand-side GNP, constant dollars
Farm GNP, constant dollars
Private nonfarm GNP, constant dollars
Private
GNP,
current
dollars
((GNPFC + GNPNFC)*DGNPP)
Total supply-side GNP, constant dollars
Total supply-side GNP, current dollars
( G NP P K + SERSTK +( SERFCC
*BEFSFC) + (SERFMC*DEFSFM))
Education’s share of Federal grants
Number of households
Federal indirect business taxes
S&L indirect business taxes
Investment in PDE, farm
Investment in equipment, nonfarm
Internal
funds,
constant
dollars
(IFK/DEFI)
Internal funds, current dollars
Index of farm capital stock, 1972=100
Farm index of capital adjusted for utiliza­
tion (IKF*(1.0-U))
Nonfarm index of capital adjusted for uti­
lization (IKNF*(1.0-U))
Index of nonfarm capital stock, 1972= 100
Interest paid by consumers
Net interest paid by Federal Government
S&L net interest payments
Investment in residential structures
Investment in nonresidential structures,
farm
Investment in nonresidential structures,
nonfarm
Inventory valuation adjustment
Change in the stock of business
Yield on 3-month Government bills
Yield on 3- and 5-year Government bonds
Stock of PDE, farm
Stock of PDE, nonfarm
Stock of residential structures
Stock of business inventories
Stock of structures, farm
Stock of structures, nonfarm
Civilian labor force, 16 years and over
Imports of goods and services




MHIF
MHINF
MHNF
PCED
PCEK
PCEN
PCES
PI
POP*
PRICE
PS
PTFD
PTR*
PTST
PUREC
PURFDC
PURNEC
SCHL*
SD*
SEMP*

SEREDC
SERFCC
SERFMC
SERNEC
SERSTK
SICE
SICFD*
SICO

SICST
SICTOT
SICU
SLSFD*

45

Median family income
Private farm manhours, establishment
basis
Index of farm manhours, 1972=100
Index of nonfarm manhours, 1972=100
Private nonfarm manhours, establishment
basis
Personal consumption expenditures, dura­
ble goods, constant dollars
Personal consumption expenditures, cur­
rent dollars
Personal consumption expenditures, non­
durable goods, constant dollars
Personal consumption expenditures, serv­
ices, constant dollars
Personal income
Total noninstitutional population includ­
ing Armed Forces stationed abroad
Labor price/cost spread, private economy
Personal savings, current dollars
Federal personal income tax payments
Personal transfers to foreigners
S&L personal income tax payments
S&L purchases, education, constant
dollars
Federal purchases of goods and services,
constant dollars
S&L government purchases, noneduca­
tion, constant dollars
Total school enrollment, ages 5-34
Statistical discrepancy
Ratio of full-time equivalent employees in
the service industries to full-time equiv­
alent private employees
S&L government education compensa­
tion, constant dollars
Federal civilian compensation, constant
dollars
Federal military compensation, constant
dollars
S&L noneducation compensation, con­
stant dollars
S&L compensation, current dollars
Employer contributions for social
insurance
Contributions for other Federal social in­
surance programs
Old Age Survival and Disability and
Health
Insurance
(OASDHI)
contributions
S&L insurance funds
Total social insurance contributions
Social insurance contributions for unem­
ployment insurance
Subsidies less current surplus of Federal
Government enterprises

SLSST*
TIME*
TRAN*
TRCP*
TRG*
TRMFI
TRO*
TRSTP*

Subsidies less current surplus of S&L gov­
ernment enterprises
Time trend, 1946=0
Total government transfer payments to
persons
Federal corporate profits tax rate
Federal tax rate on gasoline
Federal tax rate on median family income
Tax rate for OASDHI
S&L government transfers to persons




46

TRU*
T29*

u*
UCP
URBAN*
WB*
WPICR*

Average employer contribution rate for
unemployment insurance
Time trend, 1928=0
Unemployment rate of the civilian labor
force, age 16 and over
Undistributed corporate profits
Total population living in urban areas
Wage base for OASDHI
WPI for crude materials for further proc­
essing, 1972=100

Appendix C. Persona! Consumption
Model: Variables and Equations

Explanation of variables
(Consumer durable goods are designated (D), nondurable goods (N), and services (S).)

Group 1 F Food and tobaee®
(N)
(N)

(N)
(N)
(N)
(N)

1 FOP
2 FPM
3 FOO
4 FFD
5 TQB
6 ALC

Food for off-premise consumption
Purchased meals
Food furnished employees
Food produced and consumed on farms
Tobacco products
Alcoholic beverages

Group 2 CL Clothing, aeeessories, and Jewelry
(N)

(S)

(N)
(N)

(S)

(D)

(S)

7 SHU
8 SCL
9 CLO
10 MIC
11 LAU
12 JRY
13 COT

Shoes
Shoe cleaning and repair
Clothing and luggage
Military issue clothing
Laundering and drycleaning
Jewelry and watches
Other clothing maintenance services

Qroyp 3 PC PersorsaS eare
(N)

(S)

(S)
(S)
(S)
(S)
(D)
(D)
(D)
(D)

(N)
(N)
(N)

(S)

(S)
(S)
(N)

(S)

14 TLG
15 BBB

Toilet articles and preparations
Barbershops, beauty parlors, and baths

Group 4 H Housing
16 OWN
17 TEN
18 FAR
19 OHO

Owner-occupied nonfarm dwellings
Nonfarm rental expenditures
Rental value of farmhouses
Other housing

Group 5 HOP Household operation
20 FNR
21 APP
22 CHN
23 ODH
24 SDH
25 CLP
26 STY
27 ELC
28 NGS
29 WAT
30 FUL
31 TEL

Household furniture
Household appliances
China, glassware, and utensils
Other durable housefurnishings
Semidurable housefurnishings
Cleaning and lighting supplies
Stationery and writing supplies
Electricity
Natural gas
Water and sanitary services
Other fuels
Telephone and telegraph




47

(S)
(S)

32 DMS
33 OPO

Group @
(N) 34 DRG
(D) 35 OPT
(S) 36 PHY
(S) 37 DEN
(S) 38 OPS
(S) 39 PHO
(S) 40 HIN

(S)
(S)
(S)
(S)
(S)
(S)
(S)

Group 7
41 BRO
42 BNK
43 IMP
44 LIF
45 GAL
46 FUN
47 PBO

Group 8
(D) 48 CAR
(D) 49 TBA
(S) 50 REP
(N) 51 GAO
(S) 52 TOL
(S) 53 AIN
(S) 54 STR
(S) 55 TAX
(S) 56 CRR
(S) 57 IRR
(S) 58 IBU
(S) 59 IAI
(S) 60 TRO

(D)
(N)
(N)
(D)
(D)
(S)
(N)
(S)
(S)
(S)
(S)
(S)
(S)
(S)

Group ©
61 BKS
62 MAG
63 TOY
64 WHG
65 RAD
66 RTV
67 FLO
68 MOV
69 LEG
70 SPE
71 CLU
72 COM
73 PAR
74 REO

Domestic service
Other household services
MBB Mediieal ear® expenses
Drug preparations and sundries
Ophthalmic and orthopedic products
Physicians
Dentists
Other professional services
Private hospitals and sanitariums
Health insurance
PB Personal business
Brokerage charges and investment counselling
Bank service charges
Imputed bank and credit union services
Expense of handling life insurance
Legal services
Funeral and burial expenses
Other business services
TR Transportation
Motor vehicles
Auto parts
Automobile repair
Gasoline and oil
Road tolls
Automobile insurance less claims paid
Bus and trolley car transportation
Taxicabs
Commuter rail transportation
Railway transportation
Intercity bus
Airline transportation
Other intercity transportation
REG Reereatlon
Books and maps
Magazines, newspapers, and sheet music
Nondurable toys and sporting goods
Wheel goods, durable toys, and sports equipment
Radio and television receivers, records, and musical instruments
Radio and television repair
Flowers, seeds, and potted plants
Motion picture admissions
Legitimate theater admissions
Admissions to sports events
Clubs and fraternal organizations
Commercial participant amusements
Parimutuel net receipts
Other recreation services




48

Group 10

(S)
(S)
(S)

75 HED
76 EED
77 OED

(S)

78 REL

Group 11

Group 12

(S) 79 FTV
(N) 80 ABD
(S) 81 EXF
(N) 82 REM

FED Private education and research
Private higher education
Private elementary and secondary education
Other private education and research
REL Religious and welfare activities
Religious and welfare activities
FTR Foreign travel and other, net
Foreign travel by U.S. residents
Expenditures abroad by Government personnel
Expenditures in the United States by foreigners
Personal remittances to foreigners

Other
1
2
3
4
5
6
7
8
9
10
11
12
13
14

variables used in consumption model equations:
DPI
Disposable personal income, 1972 constant dollars
PPCE
Implicit price deflators for personal consumption expenditures
POP
Total population
POP16& Population aged 16 and over
POP 1834 Population between the ages of 18 and 34
STKAPP Gross stocks of household appliances, 1972 constant dollars
STKCAR Gross stocks of motor vehicles, 1972 constant dollars
STKCHN Gross stocks of china, glassware, and utensils, 1972 constant dollars
STKFNR Gross stocks of household furniture, 1972 constant dollars
STKHOP Gross stocks of household operation, 1972 constant dollars
STKJRY Gross stocks of jewelry and watches, 1972 constant dollars
STKODH Gross stocks of other durable housefurnishings, 1972 constant dollars
STKOPT Gross stocks of ophthalmic and orthopedic products, 1972 constant dollars
STKREC Gross stocks of recreation, 1972 constant dollars

Other
1
2
3

variables used in price model equations:
TIME
Time trend, 1945 = 1
ULC
Unit labor costs, private economy
ENGY
Producer price index of fuels and related products, and power, 1967 = 100

Personal Consumption Model Equations
12 S^ajor product groups

1.

F/POP = 532.742 + 0.297(F( - l)/POP( -1)) + 0.052(DPI/POP - DPI( - l)/POP( -1)) + 0.054{DPI( - l)/POP( -1))
(5.128)
(2.057)
(6.009)
(5.319)
—3.171 (PF/PPCE —
PF(—1)/PPCE(—1)) - 3.343(PF(- 1)/P P C E (-1)) + 417.778(POP 1834/POP16&)
(-3.301)
(-3.316)
(2.346)
R-squared = 0.978
D.W.
= 1.392

2.

CL/POP = -5.444 + 0.904<CL(- l)/POP(-l)) + 0.074(DPI/POP-DPI(-1)/POP(-1)) + 0.009(DPI(- l)/POP(-l))
(-0 .5 5 0 ) (10.980)
(5.278)
(2.064)
- 1.435(PCL/PPCE - PCL( - 1)/PPCE( - 1))
(-2.321)




49

Cochrane/Orcutt RHO = -0.006
R-squared - 0.988
D.W.
= 2.300
3.

PC/POP = 14.519 + 0.962(PC(- 1)/PQP( —1)) + 0.009(DPI/POP - O P I ( - l)/P O P (- 1))
(4.578)
(52.167)
(2.865)
- 0.301(PPC/PPCE - PPC( - 1)/PPCE( - 1)) - 36.361(POP1834/POP16&)
(-2 .1 1 2 )
(-3.954)
Cochrane/Orcutt RHO = -0.055
R-squared = 0.992
D.W.
= 1.565

4.

H/POP = 0.988(H( - l)/POP( - 1)) + 0.007(DPI/POP - DPI( - l)/POP( - 1)) + 0 .0 1 1 (D P I(-l)/P O P (-1))
(36.509)
(1.356)
(2.232)
- 0.082(PH/PPCE - PH( - 1)/PPCE( - 1)) - 0.13 5 (P H (-1 )/P P C E (-1))
(-1 .4 1 8 )
(-2.873)
R-squared = 0.999
D.W. ■ = 1.135

5.

HOP/POP = 84.049 + 0 .0 7 9 (H O P (-l)/P O P (-1)) + 0 .1 4 0 (D P I/P O P -D P I(-l)/P O P (-1)) + 0.143
(0.900) (0.657)
(8.030)
(7.492)
(DPI( - l)/PO P( - 1)) - 1.477(PHOP/PPCE - PHOP( - 1)/PPCE( - 1)) - 1.516(PH O P(-1)/
(-1.463)
(-1.503)
P P C E (-l)) - 0.041(STKHOP(-l)/POP16&( —1)) + 154.485(POP1834/POP16&)
(-1.356)
(1.163)
R-squared = 0.997
D.W.
= 1.630

6.

MED/POP = -1.230 + 1.0 3 9 (M E D (-l)/P O P (-1)) + 0 .0 2 5 (D P I/P O P -D P I(-l)/P O P (-!))
(-0.570) (92.353)
(2.451)
- 0.936(PMED/PPCE - PMED( - 1)/PPCE( - 1))
(-2.025)
Cochrane/Orcutt RHO = 0.020
R-squared = 0.998
D.W.
= 1.835

7.

PB/POP = 0.858(PB( - l)/POP( -1 )) + 0.020(DPI/POP - DPI( - l)/POP( -1 )) + 0.008(DPI(- l)/P O P (-1))
(7.411)
(2.232)
(1.455)
- 1 . 194(PPB/PPCE - PPB( - 1)/PPCE(-1))
(-3.562)

Cochrane/Orcutt RHO = -0.015
R-squared = 0.992
D.W.
= 1.746



50

8.

TR/POP = 0.320(TR(- 1 )/P Q P (-1)) + 0.226(DPI/POP - DPI( - l)/P O P (-1)) + 0.085(D PI(-l)/PO P(-1))
(1.849)
(5.650)
(3.698)
- 68,428(POP 1834/POP16&)
(-1.415)
Cochrane/Orcutt RHO = 0.056
R-squared = 0.977
D.W.
= 1.884

9.

REC/POP = 90.604 + G.422(REC( - l)/POP( -1)) + 0.060(DPI/POP - DPI( - l)/POP( - ! ) ) + 0.061(DPI( - 1 ) /
(2.869) (3.045)
(4.937)
(4.950)
PQP( -1)) - 1 .626(PREC/PPCE - PREC( - 1)/PPCE( -1)) - 1 .645(PREC( - 1)/PPCE( -1))
(-3.897)
(-3.887)
—
0.028(STKREC( —l)/POP16&( -1))
(-1.260)
R-squared = 0.997
D.W.
= 1.598

10. PED/POP = 8.525 + 1.007(PED (-l)/PO P(-1)) + 0.006(DPI/PQP - DPI( - l)/POP( -1))
(3.044) (66.645)
(2.614)
- 23.128(POPl 834/POP 16&)
(-2.731)
Cochrane/Orcutt RHO = 0.092
R-squared = 0.996
D.W.
= 1.846
11.

REL/POP = 1.764 + 0.970(REL( - l)/PO P( - 1)) + 0.004(DPI/POP - DPI( - l)/PO P( - 1))
(1.560) (31.342)
(1.456)
- 0.525(PREL/PPCE - PREL( - 1)/PPCE( - 1))
(-3.655)
Cochrane/Orcutt RHO = -0.019
R-squared = 0.978
D.W.
= 2.651

12. FTR/POP = 13.080 + 0 .7 0 6 (F T R (-l)/P O P (-1)) - 0.182(PFTR/PPCE-PFTR(- 1)/PPC E(- 1))
(3.073) (14.220)
(-5.600)
- 0.197(PFTR( - 1)/PPCE( - 1)) + 37.604(POP1834/POP16&)
(-5.386)
(2.091)
Cochrane/Orcutt RHO = 0.080
R-squared = 0.967
D.W.
= 2.296
82 Detailed produet eategories

1.

FOP/POP = 276.855 + 0 .3 6 5 (F O P (-l)/P O P (-1)) + 0.430(F/POP - F( - l)/P O P (- 1)) + 0.401(F(-1)/
(3.890)
(4.296)
(7.290)
(7.201)




51

P O P (-l)) - 3.024(PFOP/PF- PFOP(- 1)/PF(- 1)) - 2.821(P F O P (-1)/P F (-1))

(-4.799)

(-4.575)

R-squared = 0.983
D.W.
= 0.591
2.

FPM/POP = -17.348 + 0.770(FPM( - l)/POP( -1)) + 0.224(F/POP - F( - l)/POP( -)) + 0.065(F(-l)/POP(-l))
(-1.223) (5.319)
(6.299)
(1.662)
- 0.104(PFPM/PF - PFPM( - 1)/PF( -1 ))
(-1.976)
Cochrane/Orcutt RHO = 0.564
R-squared = 0.977
D.W.
= 1.859

3.

FOO/POP = 0.873(FOO( - l)/POP( - 1)) + 0 .0 0 2 (F /P O P -F (- l)/P O P (- 1)) + 0 .0 0 2 (F (- l) /P O P ( - 1))
(9.361)
(1.378)
(1.378)
Cochrane/Orcutt RHO = 0.289
R-squared = 0.743
D.W.
= 1.607

4.

FFD/POP = - 2.061 + 0.953(FFD( - l)/POP( -1)) + 0.003(F/POP - F( - 1)/PQP( -1)) + 0.003(F( - l)/POP( -1))
(-1.087) (46.802)
(1.114)
(1.114)
Cochrane/Orcutt RHO = -0.006
R-squared = 0.997
D.W.
= 1.862

5.

TOB/POP = 21.853 + 0.627(TOB(- l)/P O P (- 1)) + 0 .0 5 0 (F /P O P -F (-l)/P O P (-1))
(2.669) (4.523)
(2.282)
- 0.213(PTOB/PF - PTOB( - 1)/PF( - 1))
(-2.604)
Cochrane/Orcutt RHO = 0.088
R-squared = 0.575
D.W.
= 1.979

6.

ALC/POP = 39.663 + 0.503(ALC( - l)/(POP( -1)) + 0.040(F/POP - F( - l)/POP( -1)) + 0.049(F( - l)/POP( -1))
(2.330) (4.892)
(4.773)
(4.416)
—
0.252(PALC/PF - PALC( - 1)/PF( - 1)) - 0.306(P A L C (-1)/P F (-1))
(-3.187)
(-3.320)
R-squared = 0.957
D.W.
= 1.593

7.

SHU/POP = 17.625 + 0 .3 8 5 (S H U (-l)/P O P (-1)) + 0 .0 8 4 (C L /P O P -C L (-l)/P O P (-1)) +
(3.129) (2.792)
(5.025)




52

Q.079(CL( - l)/POP( -1)) - 0.171 (PSHU/PCL - PSHU( - 1)/PCL( - 1)) - 0.161(PSHU( - 1 ) /
(4.719)
(-2.928)
(-2.793)
P C L (-l))
R-squared = 0.916
B.W.
= 1.749
8. SCL/POP = 0.096 + 0.911(SCL(- l)/POP( - ! )) - 0.003(PSCL/PCL - PSCL(- 1)/PCL( - ! ))
(0.979) (15.631)
(-1.351)
Cochrane/Orcutt RHO = 0.425
R-squared = 0.973
B.W.
= 1.943
9. CLO/POP = 100.411 + 0.173(CLO(—
l)/POP(— + 0.686(CL/POP - CL( - l)/POP( -1)) + 0.666{CL(-1)/POP(-1))
1))
(4.241) (2.014)
(11.570)
(10.895)
- 1 .275(PCLO/PCL - PCLO( - 1)/PCL( - 1)) - 1.238(PCLO( - 1)/PCL( - 1))
(-6.122)
(-5.665)
R-squared = 0.997
B.W.
= 0.630
10. MIC/POP = 0.193 + 0.714(MIC(—l)/PO P(—1)) - 0.004(PM IC /PC L -PM IC (-l)-PC L (-l))
(1.333) (5.395)
(-0.687)
Cochrane/Orcutt RHO = 0.422
R-squared = 0.792
B.W.
= 1.816
11. LAU/POP = 0.965(LAU( - l)/POP( -1)) + 0.032(CL/POP - CL( - l)/POP( - 1))
(132.814)
(3.532)
Cochrane/Orcutt RHO = 0.532
R-squared = 0.994
B.W.
= 2.003
12. JRY/POP = -1.301 + 0.392(JRY( - l)/POP( -1)) + 0.096(CL/POP - CL( - 1)/POP( - 1)) + 0.094
(-0.600) (4.141)
(9.320)
(8.593)
(CL( - l)/POP( -1)) - 0.102(PJRY/PCL - PJRY( - 1)/PCL( - 1)) - 0.100(PJRY( - 1)/
(-5.550)
(-5.101)
PC L(- 1))-0.013(STKJRY(- l)/POP16& (-1))
(-1.690)
R-squared = 0.966
B.W.
= 1.292
13. COT/POP = 0.066 + 1.0Q9(CQT( - l)/POP( -! )) + 0.017(CL/POP-CL(-1)/POP(-1))
(0.807) (46.608)
(4.643)




53

- 0.037(PCOT/PCL - PCOT( - 1)/PCL( - 1))
(-2.985)
Cochrane/Orcutt RHO = -0.081
K-squared = 0.992
D.W.
= 2.289
14. TLG/POP = -2.196 + 0.900(TLG(- l)/P O P (- 1)) + 0.500(PC/PGP- PC (- 1)/PQP(- 1)) +
' (-3.749) (23.108)
(8.285)
0.115(PC( - 1)/PQP( - 1)) - 0.161(PTLG/PPC - PTLG( - 1>/PPC( - 1))
(3.324)
(-2.759)
Cochrane/Orcutt RHO = 0.008
R-squared = 0.999
D.W.
= 2.292
15

BBB/POP = 2.305 + 0.859(BBB( —l)POP ( - 1)) + 0 .5 6 3 (P C /P O P -P C (-l)/P O P (-1))
(4.332) (29.648)
(10.387)
- 0.206(PBBB/PPC - PBBB( - 1)/PPC( - 1))
(-3.718)
Cochrane/Orcutt RHO = -0.008
R-squared = 0.980
D.W.
= 2.051

16. OWN/POP = —11.009 + 0.764(0W N (- l)/POP( —1)) + 0.710(H/POP —H( —l)/PO P( —1)) + 0.180(H( —1)/
(-1.993) (6.764)
(9.674)
(2.119)
P O P (-l))
Cochrane/Orcutt RHO = 0.540
R-squared = 0.999
D.W.
= 2.260
17. TEN/POP = 3.551 + 0.741 (T E N (-l)/PO P ( - 1)) + 0 .2 3 6 (H /P O P -H (-l)/P O P ( - 1))+ 0.063(H (-1)/
(1.396) (6.068)
(4.766)
(2.137)
P Q P (-l))
Cochrane/Orcutt RHO = 0.724
R-squared = 0.999
D.W.
= 2.165
18.

FAR/POP = Q.963(FAR(- l)/P O P (- 1)) - 0.001(PFAR/PH - PFAR( - 1)/PH( - 1))
(67.042)
(-0.699)
Cochrane/Orcutt RHO = 0.920
R-squared = 0.999
D.W.
= 2.455

19.

OHO/'POP = 7.385 + 0 .6 5 1 (O H O (-l)/P O P (-1)) + 0 .0 2 0 (H (-l)/P O P (-1))
(1.896) (5.357)
(3.217)




54

- 0.113(POHO( - 1)/PH( - 1))
(-2.032)
Cochrane/Orcutt RHO = —
0.030
R-squared = 0.986
D.W.
= 1.947
20.

FNR/POP = 36.214 + 0.229(FNR( - l)/POP( - 1)) 4- O.OB4(HOP/POP - HOP( - l)/POP( -1 )) + 0.080
(3.755) (1.718)
(5.735)
(6.000)
(HOP( - l)/POP( -1)) - 0.278(PFNR/PHOP - PFNR( - l)/PHOP( -1)) - 0.263(PFNR( - 1 ) /
(-3.509)
(-3.361)
P H O P (-l)) - 0.018(STKFNR( - l)/POP16&( - 1))
(-1.746)
R-squared = 0.981
D.W.
= 0.933

21.

APP/POP = - 6.678 + 0.649(APP(- l)/POP( -1 )) + 0.106(HOP/POP - HOP( - l)/PO P( -1 )) + 0.047
(-4.852) (5.621)
(9.094)
(3.924)
(HOP( - l)/POP( -1)) - 0.31 l(PAPP/PHOP - PAPP(- l)/PHOP(-1)) - O.GQ7(STKAPP( - 1 )/
(-6.085)
(-2.355)
POP16&(- 1))
Cochrane/Orcutt RHO = 0.007
R-squared = 0.996
D.W.
=2.120

22.

CHN/POP = 25.757 + 0.476(CHN(- l)/POP( - !)) + 0.041 (HOP/POP - HOP( - l)/P O P (- ! ) ) + 0.041
(9.5333) (7.632)
(9.493)
(9.278)
(HOP( - l)/POP( -1)) - 0.295(PCHN/PHOP - PCHN( - l)/PHOP( -1)) - 0.296(PCHN( - 1 ) /
(-7.810)
(-7.689)
P H O P (-l)) - 0.023(STKCHN(- l)/POP16&(-1 ))
(-4.272)
R-squared = 0.979
D.W.
= 1.268

23.

ODH/POP = 27.423 + 0.764 (ODH(- l)/P O P (- 1)) + 0.125(HOP/POP - HOP(- l)/PO P( - 1)) + 0.053
(3.106) (8.500)
(9.943)
(4.367)
(HOP( - l)/POP( -1)) - 0.257(PODH( - l)/PHOP( -1)) - 0.027(STKODH( - l)/POP16&( -!))
(-3.468)
(-4.046)
Cochrane/Orcutt RHO = -0.070
R-squared = 0.998
D.W.
= 2.237




55

24.

SDH/POP = - 0.109 + 0.983(SDH( - l)/POP( - 1)) + 0.093(HOP/POP - HOP( - l)/PO P( - 1))
(-0.214) (49.067)
(9.719)
- 0.098(PSDH/PHOP - PSDH( - l)/PHOP( - 1))
(-3 .5 2 6 )
Cochrane/Orcutt RHO = 0.052
R-squared = 0.992
D.W.
= 1.410

25.

CLP/POP = 2.028 + 0 .9 2 3 (C L P (-l)/P O P (-1)) + 0 .109(HOP/POP - HOP( - l)/P O P (- 1))
(1.527) (23.196)
(6.607)
Cochrane/Orcutt RHO = 0.532
R-squared = 0.990
D.W.
= 1.980

26.

STY/POP = 0.723 + 0.921(STY( - l)/POP( - 1)) + 0.025(HOP/POP - HOP( - l)/PO P( - 1))
(2.189) (23.775)
(4.271)
- 0.100(PSTY/PHOP - PSTY( - l)/PHOP( -1 ))
(-3.302)
Cochrane/Orcutt RHO = -0.059
R-squared = 0.964
D.W.
= 1.975

27.

ELC/POP = - 1.540 + 0.960(ELC( - l)/P O P (-1 )) + 0.028(HOP/POP - HOP( - l)/POP( - 1)) + 0.013
(-1 .9 1 3 ) (40.566)
(3.556)
(2.880)
L

(HOP( —l)/POP( —1))
Cochrane/Orcutt RHO = -0.655
R-squared = 0.999
D.W.
= 1.717
28.

NGS/POP = 1.583 + 0 .9 6 4 (N G S (-l)/P O P (-1)) - 0.067(PNGS/PHOP - PNGS( - l)/P H O P (- 1))
(6.231) (90.286)
(-3.553)
Cochrane/Orcutt RHO = -0.085
R-squared = 0.996
D.W.
= 1.715

29.

WAT/POP = 0.372 + 0.995(WAT( - l)/POP( -1 )) + 0.014(HOP/POP - HOP( - l)/POP( - 1))
(1.135) (42.650)
(2.348)
- 0.096(P WAT/PHOP - PWAT( - l)/PHOP( -1 ))
(-3.262)

Cochrane/Orcutt RHO = -0.030
R-squared = 0.987
D.W.
= 1.302




56

30.

FUL/POP = 2.493 + 0.880(FUL(- l)/P O P (- 1)) + 0.087(H O P/PO P-H O P(- l)/P O P (- 1))
(1.189) (12.797)
(5.072)
- 0.115(PFUL/PHOP - PFUL( - l)/PHOP( - 1))
(-4.879)
Cochrane/Orcutt RHO = 0.134
R-squared = 0.898
D.W.
= 2.073

31.

TEL/POP = 7.127 + 0 .9 5 3 (T E L (-l)/P O P (-1)) + 0 .0 1 8 (H O P /P O P -H O P (-l)/P O P (-1)) + 0.016
(1.325) (17.333)
(2.007)
(1.985)
(HOP( - l)/POP( - 1)) - 0.098(PTEL/PHOP - PTEL( - l)/PHOP( - 1)) - 0.088(PT E L (-1)/
(-1.946)
(-1.924)
P H O P (-l))
R-squared = 0.999
D.W.
= 2.215

32.

DMS/POP = 39.027 + 0 .4 4 0 (D M S (-l)/P O P (-1)) + 0 .0 3 1 (H O P /P O P -H O P (-l)/P O P (-1)) +
(4.174) (3.125)
(1.690)
0.035(HOP( - l)/POP( -1)) - 0.377 (PDMS/PHOP-PDMS(- l)/PH O P(- 1)) - 0.432(PDMS( - 1 ) /
(1.741)
(-3.304)
(-3.608)
P H O P (-l))
R-squared = 0.968
D.W.
= 1.671

33.

OPO/POP = 0.570 + Q.817(QPO( - l)/P O P (- 1)) + 0.056(HOP/POP - HOP( - l)/PO P( - 1)) + 0.010
(0.958) (7.222)
(6.046)
(1.601)
(HOP( - l)/POP( - 1)) - 0.020(POPO/PHOP - POPO( —l)/PHOP( - 1)) - 0.003(PO PO (-1)/
(-1.640)
(-1.205)
P H O P (-l))
R-squared = 0.987
D.W.
= 1.121

34.

DRG/POP = 20.534 + 0 .6 8 6 (D R G (-l)/P O P (-1)) + 0.065(MED/POP - MED( - l)/P O P (- 1))
(2.015)
(4.417)
(2.072)
- 0.080(PDRG/PMED - PDRG( - 1)/PMED( -1 )) - 0.088 (PDRG( - 1 ) / PMED( -1))
(-1.798)
(-1.933)

Cochrane/Orcutt RHO = 0.333
R-squared = 0.996
D.W.
= 1.863



57

35.

OPT/POP = 1.290 + 0.958(OPT(- l)/P O P (-1 )) + 0.037 (M E D /P O P -M E D (-l)/P O P (-1))
(2.334) (5.879)
(1.937)
- 0.041 (POPT/PMED - POPT( - 1)/PMED( -1)) - 0.024<STKOPT( - l)/POP16&( -1))
(-1.432)
(-1.208)
Cochrane/Orcutt RHO = -0.075
R-squared = 0.796
D.W.
= 1.839

36.

PHY/POP = 6.168 + 0.619(PHY( - l)/PO P( - !)) + 0.276(MED/POP - MEB( - l)/PO P( - !)) + 0.073
(2.544) (4.096)
(5.316)
(2.331)
(MED( - l)/POP( - 1)) - 0.388(PPHY/PMED - PPHY( - 1)/PMED( - 1))
(-2.681)
Cochrane/Orcutt RHO = 0.050
R-squared = 0.995
B.W.
= 2.043

37.

BEN/POP = 17.210 + 0.637(DEN( - l)/PO P( -1 )) + 0.035(MED/POP - MED( - l)/PO P( - 1)) + 0.032
(1.586) (4.520)
(3.259)
(3.073)
(MED( - l)/POP( -1)) - 0.175(PDEN/PMED - PDEN( - 1)/PMED( -1)) - 0.162(PDEN( -1 )
(-1.657)
(-1.588)
/P M E B (-l))
R-squared = 0.984
B.W.
= 1.928

38.

OPS/POP = 1.529 + 0.815(OPS(- l)/PO P( —1)) + 0.089(MEB/POP - MEB( - l)/PO P( - 1))
(1.315) (7.984)
(2.402)
Cochrane/Orcutt RHO = 0.443
R-squared = 0.891
B.W.
= 2.135

39.

PHO/POP = 15.837 + 0 .7 4 7 (P H O (-l)/P O P (-1)) + 0.183(MEB/POP - MEB(- l)/P O P (- 1)) + 0.166
(1.138) (8.193)
(3.742)
(3.396)
(MEB( - l)/POP( —1)) - 0.364(PPHO/PMEB - PPHQ( - 1)/PMEB( —1)) - 0.330
(-1.727)
(-1.703)
(PPHQ( - 1)/PMEB( -1 ))
R-squared = 0.998
B.W.
= 1.098

40. HIN/POP = 7.020 + 0.430(HIN( - l)/PO P( - 1)) + 0.043(MEB/POP - MEB( - 1)/PQP( - 1)) + 0.050
(4.018) (4.579)
(4.463)
(6.075)




(MEB( - l)/POP( -1 )) - 0.046(PHIN/PMEB - PHIN( - 1)/
(-3.024)
PMEB( -1 )) - 0.053(PHIN( - 1)/PMED( - 1))
(-3.187)

58

R-squared = 0.991
D.W.
= 1.447

41. BRO/POP' = 5.083 + 0.8Q1(BRO(- l)/P O P (- !)) + 0.796(P B /P O P-P B (-l)/P O P(-1))
(5.133) (15.472)
(16.812)
- 0.056(PBRO( - 1)/PPB( - 1))
(-5.207)
Cochrane/Orcutt RHO = 0.009
R-squared = Q.94'9
D.W.
= 2.146
42. BNK/POP = 4.223 + 0.460(BNK( - l)/POP( - 1)) + 0.034(PB/POP - PB( - l)/POP( - 1)) + 0.030
(3.160) (4.086)
(4.802)
(4.576)
(PB( - l)/POP( -1)) - 0.040(PBNK/PPB - PBNK( - 1)/PPB( -1)) - 0.035(PBNK( -1 )/PPB( -1))
(-4.638)
(-4.178)
R-squared = 0.994
D.W.
= 1.563
43.

IMP/POP = -6.134 + Q.888(IMP( - 1)/PQP( -1 )) + 0 .0 6 5 (P B /P O P -P B (-l)/P O P (-!)) + 0.086
(-3.474) (12.011)
(1.472)
(2.516)
(PB( —l)/POP( —1))
Cochrane/Orcutt RHO = 0.090
R-squared = 0.997
D.W.
= 1.788

44.

1)/
LIF/POP = 39.262 + 0.367(LIF(- l)/POP( -1)) + 0.051(PB/POP - P B ( - l)/PO P(—!)) + 0.054(PB( —
(2.339)
(2.476)
(4.253) (2.067)
PLIF( - 1)/PPB( — - Q.244(PLIF(—1)/PPB(—!))
1))
P O P (-l)) - 0.232(PLIF/PPB —
(-4.040)
(-3.695)
R-squared = 0.961
D.W.
= 1.841

45.

GAL/POP = 3.359 + 0 .6 5 9 (G A L (-l)/P O P (-1)) + Q.Q80(PB/PQP- PB(- l)/P O P (- 1» + 0.065
(1.480) (5.307)
(1.998)
(3.000)
(PB( - l)/POP( - 1)) - 0.060(PGAL( - 1)/PPB( -1 ))
(-1.740)
Cochrane/Orcutt RHO = -0.161
R-squared = 0.973
D.W.
= 1.898

46.

FUN/POP = Q.981(FUN( - 1)/P0P( - 1)) + O.Q54(PB/POP - PB( - l)/PO P( - 1))
(74.740)
(2.546)
- 0.060(PFUN/PPB - PFUN( - 1)/PPB( - 1))
(-2.310)




59

Cochrane/Orcutt RHO = -0.031
R-squared = 0.845
D.W.
= 1.445
47.

PBO/POP = 1.703 + 0.652(PBO( - l)/POP( -1)) + 0 .0 2 0 (P B /P O P -P B (-l)/P O P (-1)) + 0.021(PB(-1)/
(2.074) (6.936)
(3.800)
(3.431)
POP( - 1)) -0.01 l(PPBO/PPB - PPBO( - 1)/PPB( -1 )) - 0.012(PPBO( - 1)/PPB( - 1))
(-2.988)
(-2.851)
R-squared = 0.988
D.W.
= 1.683

48.

CAR/POP = -2.276 + 0 .7 1 2 (C A R (-l)/P O P (-1)) + 0 .8 6 2 (T R /P O P -T R (-l)/P O P (-1)) + 0.141
(-0.688) (12.919)
(38.215)
(3.514)
(TR( - l)/POP( -1 )) - 0.077(PCAR/PTR - PCAR( - 1)/PTR( - 1)) - 0.013(PCAR( - 1 ) /
(-2.313)
(-1.561)
PTR( -1 )) - 0.006(STKCAR( - l)/POP16&( - 1))
(-1.497)
R-squared = 0.998
D.W.
= 1.685

49.

TBA/POP = 4.948 + 0.6 6 5 (T B A (-l)/P O P (-1)) + 0.019(TR/POP - TR( - l)/PO P( - 1)) + 0.024
(1.534) (7.721)
(4.383)
(3.843)
(TR( - l)/PO P( - 1)) - 0.046(PTBA/PTR - PTBA( - 1)/PTR( -1 )) - 0.057(PTBA( - 1)/
(-2.656)
(-2.785)
PTR( - ) )
R-squared = 0.988
D.W.
= 1.919

50.

REP/POP = 0.657 + 0 .9 9 4 (R E P (-l)/P O P (-1)) + 0 .0 2 1 (T R /P O P -T R (-l)/P O P (-1)) + 0.012
(0.505) (26.961)
(3.939)
(1.905)
(TR( - l)/POP( -1 )) - 0.035(PREP(- 1)/PTR (- 1))
(-1.741)

< Cochrane/Orcutt RHO = -0.400
R-squared = 0.999
D.W.
= 2.011
51.

GAO/POP = 20.286 + 0.8 1 5 (G A O (-l)/P O P (-1)) + 0.047(TR/POP - TR( - l)/PO P( - 1)) + 0.047
(3.771) (18.376)
(4.145)
(4.046)




(TR( - l)/POP( - 1)) - 0.169(PGAO/PTR - PGAO( - 1)/PTR( - 1)) - 0.167(PGAO(-1)/
(-4.105)
(-3.762)
P T R (-l))

60

R-squared = 0.997
D.W.
= 1.475
52.

TOL/POP = 0.397 + 0 .9 6 2 (T O L (-l)/P O P (-1)) + 0.002(TR/POP - TR( —l)/POP( -1 ))
(2.122) (31.523)
(3.238)
- 0.002(PTOL( - 1)/PTR( -1 ))
(-1.704)
Cochrane/Orcutt RHO = 0.054
R-squared = 0.998
D.W.
= 1.806

53. AIN/POP = -0.810 + 0.500(A IN (-1)/POP(-1)) + 0.010(TR/PGP - TR( - l)/POP( -1 )) + 0.029
(-1.498) (6.958)
(1.713)
(6.852)
(TR( - l)/PO P( -1 )) - 0.059(PAIN/PTR - PAIN( - 1)/PTR( - 1))
(-5.044)
Cochrane/Orcutt RHO = -0.033
R-squared = 0.985
D.W.
= 1.658
54.

STR/POP = 3.967 + 0.8 1 3 (S T R (-l)/P O P (-1)) - 0.097(PSTR/PTR- PSTR(- 1)/PTR (- 1))
(3.364) (44.424)
(-5.892)
- 0.028(PSTR( - 1)/PTR( - 1))
(-2.262)
Cochrane/Orcutt RHO = 0.331
R-squared = 0.999
D.W.
= 1.947

55.

TAX/POP = 3.966 + 0 .6 8 6 (T A X (-l)/P O P (-1)) - 0.078(PTAX/PTR- PTAX(- 1)/PTR (- 1))
(3.056) (10.250)
(-4.042)
- 0.028(PTAX( - 1)/PTR( - 1))
(-2.492)
Cochrane/Orcutt RHO = 0.095
R-squared = 0.973
D.W.
= 1.712

56.

CRR/POP = 0.555 + Q.760(CRR(- l) /P O P ( - 1)) - 0.008(PCRR/PTR - PCRR( - 1)/PTR (- 1))
(3.219) (14.168)
(-4.314)
- 0.004(PCRR( - 1)/PTR( - 1))
( - 2 .668)

Cochrane/Orcutt RHO = 0.250
R-squared = 0.992
D.W.
= 1.740




61

57.

IRR/POP = 0.166 + 0 .8 5 2 (IR R (-l)/P O P (-1)) - 0.007(PIRR/PTR - PIRR( - 1)/PT R (- 1))
(1.357)(17.266)
(-0.866)
Cochrane/Orcutt RHO = 0.283
R-squared = 0.973
D.W.
= 1.623

58.

1BU/POP = 2.641 + 0 .7 0 3 (IB U (-l)/P O P (-1)) + 0 .0 0 2 (T R (-l)/P O P (-1))
(2.891) (6.445)
(1.592)
- 0.034(PIBU/PTR - PIBU( - 1)/PTR( - 1)) - 0.029(PIBU( - 1)/PTR( - 1))
(-3.474)
(-2.894)

Cochrane/Orcutt RHO = 0.639
R-squared = 0.976
D.W.
= 1.933
59.

IAI/POP = 0.533 + 0 .8 0 3 (IA I(-l)/P O P (-1)) + 0 .0 1 0 (T R /P O P -T R (-l)/P O P (-1)) + 0.011
(0.392) (11.778)
(3.457)
(3.097)
(TR( —l)/PO P( -1 )) - 0.025(PIAI/PTR —
PIAI( —1)/PTR( —1)) - 0.027(PIAI ( - 1)/
(-2.292)
(-2.251)
P T R (-l))
R-squared = 0.994
D.W.
= 1.436

60.

TRO/POP = 0.137 + 0 .9 8 2 (T R O (-l)/P O P (-1)) - 0.001(PTRO(- 1 )/P T R (-1))
(1.555)(16.641)
(-1.385)
Cochrane/Orcutt RHO = 0.216
R-squared = 0.942
D.W.
= 1.985

61.

BKS/POP = 0.812(BKS(—l)/P O P (- 1)) + 0.019(REC/POP - REC( - l)/PO P( - 1)) + 0.013
(9.438)
(1.040)
(2.342)
(REC( - l)/POP( - 1)) - 0.140(PBKS/PREC - PBKS( - 1)/PREC( - 1))
(-1.501)
Cochrane/Orcutt RHO = 0.011
R-squared = 0.952
D.W.
= 1.930

62.

MAG/POP =




18.155 + 0 .8 0 8 (M A G (-l)/P O P (-1)) + 0.089(R E C /P O P -R E C (-l)/P O P (-!))
(4.604) (10.350)
(4.768)

+ 0.089 (REC( - l)/POP( - 1)) 0.336(PMAG/PREC - PMAG( - 1)/PREC( - 1)) - 0.334
(4.971)
(-4.148)
(-4.330)
(PMAG( - 1)/PREC( - 1))

62

R-squared = 0.903
D.W.
= 1.851
63.

TOY/POP = 0.552 + 0.781(TGY(- l)/P O P (- 1)) + 0.149(REC/POP - REC(- l)/P O P (- !•)) + 0.025
(1.476) (14.905)
(9.605)
(3.419)
(REC( - l)/POP( - ! ) )
Cochrane/Orcutt RHO = 0.173
R-squared = 0.988
D.W.
= 1.940

64.

WHG/POP = 2.069 + 0.38 6 (W H G (-l)/P O P (-1)) + 0.111(REC/POP - R E C (- l)/P O P (- !))
(0.661) (2.997)
(5.774)
+ 0=120 (REC(- l)/P O P (-1 )) - 0.086(PWHG/PREC- PWHG(- 1)/PREC(- 1))
(5.322)
(-3.760)
- 0.093 (PWHG( - 1)/PREC( -1 ))
(-3.466)
R-squared = 0.993
D.W.
= 1.306

65.

RAD/POP = -12.276 + 0.6 1 4 (R A D (-l)/P O P (-!)) + 0.240(R EC/PQ P-REC(- 1 )/P Q P (-1))
(-4.637) (5.906)
(7.011)

+ 0.148 (REC( - l)/PO P( - ) ) - 0.018(PRAD/PREC - PRAD( - 1)/PREC( - 1)) - 0.011
(4.222)
(-2.280)
(-1.587)
(PRAD( - 1)/PREC( —1))
R-sqiiared = 0.999
D.W.
= 1.650
66.

RTY/PGP = 0.503 + 0.805(RTV(- l)/P O P (- !)) + 0.014(R E C /P Q P-R E C (- l)/P O P (- 1)) + 0.002
(3.727) (15.640)
(2.291)
(2.254)
(REC( —1)/PQP( —1))
Cochrane/Orcutt RHO = -0.106
R-squared = 0.982
D.W.
= 2.105

67.

FLO/POP = 0.210 + 0.9S1(FLO(- l) /P O P ( - !)) + 0.055(REC/PGP - REC( - l)/P O P (- !))
(1.865) (51.531)
(5.480)
- 0.007(PFLG/PREC - PFLO( - 1)/PREC( - 1))
(-2.082)
Cochrane/Orcutt RHO = -0.631
R-squared = 0.993
D.W.
= 1.944




63

68.

MOV/POP = 0.905(M OV(-1)/POP(-1)) + 0.031(REC/POP - R E C ( - l)/P O P (- 1)) + 0.021
(50.771)
(3.029)
(2.073)
(REC( - l)/POP( —1)) - 0.059(PMOV/PREC - PMOV( - 1)/PREC( -1 )) - 0.040
(-2.066)
(-1.600)
(PMOV( —1)/PREC( —
1))
R-squared = 0.985
D.W.
= 1.989

69.

LEG/POP = 1.200 + 0 .7 9 2 (L E G (-l)/P O P (-1)) + 0.007(REC/POP -R E C ( - l)/P O P (- 1)) + 0.008
(1.856) (6.556)
(4.680)
(5.206)
(REC( - l)/POP( - 1)) - 0.021 (PLEG/PREC - PLEG( - 1)/PREC( - 1)) - 0.024
(-3.623)
(-3.885)
(PLEG( - 1)/PREC( -1 ))
R-squared = 0.902
D.W.
= 1.754

70.

SPE/POP = 2.576 + 0 .9 7 9 (S P E (-l)/P O P (-1)) - 0.029(PSPE/PREC - PSPE(- 1)/PREC(- 1))
(3.150) (37.683)
(-2.821)
- 0.029(PSPE/PREC - PSPE( - 1)/PREC( - 1))
(-3.089)
Cochrane/Orcutt RHO = 0.218
R-squared = 0.992
D.W.
= 2.333

71.

CLU/POP = 4.796 + 0.555(CLU( - l)/PO P( - 1)) + 0.002(REC/PGP - REC( - l)/POP( - 1)) + 0.002
(3.251) (3.852)
(2.301)
(2.144)
(REC( - l)/POP( -1 )) - 0.027(PCLU/PREC - PCLU( - 1)/PREC( - 1)) - 0.026
(-2.968)
(-2.711)
(PCLU( —1)/PREC( —1))
R-squared = 0.694
D.W.
= 1.771

72.

COM/POP = 1.181 + 0.889(COM(- l)/P O P (- 1)) + 0.032(REC/POP - REC( - l)/P O P (- 1))
(1.623) (13.644)
(3.627)
Cochrane/Orcutt RHO = 0.733
R-squared = 0.989
D.W.
= 1.961

73.

PAR/POP = 3.029 + 0.903(PAR(- l) /P O P ( - 1)) + 0 .0 0 8 (R E C /P O P -R E C (-l)/P O P (-1)) + 0.007
(3.907) (13.060)
(3.635)
(3.142)




64

(REC( - 1)/P0P( - 1)) - 0.047(PPAR/PREC - PPAR( - 1)/PREC( - 1)) - 0.040
(-4.685)
(-3.884)
PPAR( - 1)/PREC( - 1))
R-squared = 0.970
D.W.
= 1.579
74.

REO/POP = 6.673 + 0.9 8 5 (R E O (-l)/P O P (-1)) + 0.050(REC/POP - REC( - l)/P O P (- 1))
(1.581) (40.134)
(3.093)
- 0.060(PREO/PREC - PREO( - 1)/PREC( -1)) - 0.063(PREO( - 1)/PREC( -1))
(-1.198)
(-1.429)
Cochrane/Orcutt RHO = 0.340
R-squared = 0.996
D.W.
= 1.839

75.

HED/POP = 1.175 + 0.294(HED( - l)/POP( - 1)) + 0.305(PED/POP - PED( - 1)/PQP( - 1)) + 0.290
(2.230) (1.641)
(4.844)
(3.926)
(PED( - l)/POP( - 1))
Cochrane/Orcutt RHO = 0.548
R-squared = 0.996
D.W.
= 1.585

76.

EED/POP = 0.859 + 0 .9 4 5 (E E D (-l)/P O P (-1)) + 0 .1 5 6 (P E D /P O P -P E D (-l)/P O P (-1))
(1.929) (27.461)
(4.593)
Cochrane/Orcutt RHO = 0.720
R-squared = 0.997
D.W.
= 1.761

77.

OED/POP = 0.976(OED( - l)/PO P( —1)) + 0 .6 2 2 (P E D /P O P -P E D (-l)/P O P (-1))
(49.851)
(9.818)
- 0.01 l(POED/PPED - POED( - 1)/PPED( -1 ))
(-2.566)
Cochrane/Orcutt RHO = 0.700
R-squared = 0.993
D.W.
= 1.959

78.

REL/POP = 1.764 + Q .970(R E L (-l)/P O P(-1)) + 0.004(DIP/POP - DPI( - l)/P O P (- 1))
(1.560) (31.342)
(1.456)
- 0.525(PREL/PPCE - PREL( - 1)/PPCE( -1 ))
(-3.655)
Cochrane/Orcutt RHO = -0.019
R-squared = 0.978
D.W.
= 2.651




65

79.

FTV/POP = -0.548 + 1.058(FTV( - l)/P O P (- 1)) + 0.539(FTR/POP - FTR(- l)/PO P( - 1))
(-1.607) (68.651)
(7.774)
Cochrane/Orcutt RHO = -0.308
R-squared = 0.993
D.W.
= 2.223

80. ABD/POP = 0.774 + 0.89!(ABO(- l)/P O P (- 1)) + 0.375(FTR/POP - FTR( - 1)/PQP( - 1))
(1.868) (17.674)
(6.220)
- 0.022(PABB/PFTR - PABD( - 1)/PFTR( -1 ))
(-1.847)
Cochrane/Orcutt RHO = 0.085
R-squared = 0.947
D.W.
= 2.012

81. EXF/POP = 0.358 + 1.074(EXF(- 1)/PQ P(- 1)) - 0 .0 0 8 (F T R (-l)/P O P (-1))
(1.374) (47.302)
(-0.526)
Cochrane/Orcutt RHO = -0.082
R-squared = 0.989
D.W.
= 1.962

82.

KEM /POP = -0 .4 4 2 + 0.290(REM( - l)/P O P ( - 1)) - 0.024(FTR/POP - FTR( - l)/P O P ( - 1))
(-3.451)
(6.364)
(-1.772)
- 0.014 (FTR( - l)/PO P( - 1))
(-2.456)
Cochrane/Orcutt RHO = 0.336
R-squared = 0.897
D.W.
= 2.399

Priee H@d©l Eqyations
12 i3aj@r product groups

1.

PF = -0.053 - 0.002(TIME) + 2.141(ULC(-1))
(-1.163) (-0.556)
(9.958)
Cochrane/Orcutt RHO = 0.629
R-squared = 0.989
D.W.
= 1.415

2.

PCL = 0.159 + 0.018(TIME) + 0.589(ULC(-1))
(1.434) (2.866)
(2.882)
Cochrane/Orcutt RHO = 0.909
R-squared = 0.993
D.W.
= 2.075




66

3.

PPC = 0.125 + 0.006(TIME) + 1.057(ULC(- 1)) + 0.00130(ENGY(-1))
(5.288) (3.394)
(5.612)
(5.270)
Cochrane/Orcutt RHO = 0.244
R-squared = 0.997
D.W.
= 2.060

4.

PH = 0.192 + 0.005(TIME) + 1.213(ULC(-1))+ 0.00016(ENGY(- 1))
(6.254) (1.961)
(5.088)
(0.569)
Cochrane/Orcutt RHO = 0.616
R-squared = 0.997
D.W.
= 1.427

5.

PHOP = 0.165 + 0.0001 (TIME) + 1.339(ULC(-1)) + 0.00110(ENGY( -1 ))
(6.059) (0.067)
(6.155)
(3.835)
Cochrane/Orcutt RHO = 0.160
R-squared = 0.995
D.W.
= 1.902

6.

PMED = -0.171 + 0.006(TIME) + 1.671(ULC(-1)) + 0.00089(ENGY( -1 ))
(-4.791) (2.037)
(6.016)
(2.653)
Cochrane/Orcutt RHO = 0.594
R-squared = 0.998
D.W.
= 1.873

7.

PPB = -0.174 + 0.012(TIME) + 1.519(ULC(-1))
(-8.123) (6.768)
(14.794)
Cochrane/Orcutt RHO = 0.512
R-squared = 0.997
D.W.
= 1.738

8.

PTR = 0.126 + 0.009(TIME) + 0.925(UCL(- I)) + 0.00132(ENGY(-1))
(6.522) (5.870)
(5.994)
(6.336)
Cochrane/Orcutt RHO = -0.158
R-squared = 0.996
D.W.
= 2.113

9.

PREC = 0.237 + 0.012(TIME) + 0.777(ULC(-1)) + 0.00008(ENGY( -1 ))
(18.126) (11.496)
(7.508)
(0.647)
Cochrane/Orcutt RHO = 0.404
R-squared = 0.999
D.W.
= 1.763

10. PPED = -0.301 + 0.023(TIME) + 1.174(ULC(-1)) + 0.00055(ENGY(-1))
(-3.070) (3.011)
(2.528)
(1.163)




67

Cochrane/Orcutt RHQ = 0.896
R-squared = 0.997
D.W.
= 1.875
11. PREL = -0.059 - 0.0002(TIME) + 1.866(ULC((-1.545) (-0.059)
(6.119)

+ 0.00069(ENGY(- 1))
(1.732)

Cochrane/Orcutt RHQ = 0.217
R-squared = 0.994
D.W.
= 1.817
12.

PFTR = -0.219 - 0.009(TIME) + 2.828(ULC(-1)) + 0.00040(ENGY(—1))
(-1.087) (-0.517)
(1.775)
(0.215)
Cochrane/Orcutt RHO = 0.605
R-squared = 0.956
D.W.
= 1.544

82

1.

Detailed product categories

PFOP = -0.075 - 0.006(TIME) + 2.444(ULC(- 1))
(-1.289) (-1.275)
(8.934)
Cochrane/Orcutt RHO = 0.576
R-squared = 0.981
D.W.
= 1.311

2.

PFPM = -0.564 + 0.032(TIME) + 1.210(ULC(-1)) + 0.00032(ENGY(- 1))
(0.594)
(-3.455) (3.033)
(2.231)
Cochrane/Orcutt RHO = 0.917
R-squared = 0.996
D.W.
= 1.734

3.

PFOO = -0.595 + 0.031 (TIME) + 1.128(ULC(-1)) + 0.00062(ENGY(—1))
(0.652)
(-1.490X1.453)
(1.148)
Cochrane/Orcutt RHO = 0.933
R-squared = 0.985
D.W.
= 1.162

4.

PFFD = 0.033 - 0.012(TIME) + 2.434(ULC(-1))
(0.372) (-1.639)
(5.791)
Cochrane/Orcutt RHO = 0.522
R-squared = 0.930
D.W.
= 1.701

5.

PTOB = -0.094 + 0.021 (TIME) + 0.866(ULC(-1))
(-1.767) (6.631)
(7.935)




68

Cochrane/Orcutt RHO - 0.898
R-squared = 0.999
D.W.
= 1.680
6.

PALC = 0.201 + .0.003(TIME) + 1.268(ULC(-1))
(13.051) (2.497)
(17.414)
Cochrane/Orcutt RHO = 0.542
R-squared = 0.997
D.W.
'= 1.862

7.

PSHU = 0.031 + 0.Q23(TIME) + 0.603(ULC(-1))
(0.338) (4.140)
(3.149)
Cochrane/Orcutt RHO = 0.895
R-squared = 0.995
D.W.
= 2.031

8.

PSCL = 0.201 + 0.011 (TIME) + 0.817(UCLC(-1)) + 0.00078(ENGY( -1 ))
(3.553) (2.205)
(1.904)
(1.578)
Cochrane/Orcutt RHO = 0.703
R-squared = 0.993
D.W.
= 1.478

9.

PCLO = 0.209 + 0.016(TIME) + 0.575(ULC(-1))
(1.987) (2.653)
(2.749)
Cochrane/Orcutt RHO = 0.901
R-squared = 0.989
D.W.
= 2.058

10.

PMIC = 0.424 - 0.005(TIME) + 1.306(ULC(-1))
(15.184) (-1.994)
(9.770)
C o c h ra n e /O rc u tt R H O = 0.459

R-squared = 0.975
D.W.
= 1.995
11.

PLAU = 0.030 + 0.007(TIME) + 1.258(ULC(-1)) + 0.00089(ENGY(-1))
(0.954) (2.983)
(4.997)
(2.757)
Cochrane/Orcutt RHO — 0.367
R-squared = 0.997
D.W.
= 1.815

12.

PJRY = 0.547 - O.OIO(TIME) + 1.312(ULC(-1)) + 0.00007(ENGY(-1 ))
(10.036) (-2.114)
(3.080)
(0.138)
Cochrane/Orcutt RHO = 0.572
R-squared = 0.966
D.W.
= 1.741




69

13.

PCOT = 0.124 + O.OOB(TIME) + 1.415(ULC(-1)) + 0.00040(ENGY( -1))
(1.338)
(4.290) (1.191)
(6.156)
Cochrane/Orcutt RHO = 0.305
R-squared = 0.996
D.W.
= 1.806

14.

PTLG = 0.327 - 0.00Q4(TIME) + 1.019(ULC(-1)) + 0.00129(ENGY(—1))
(3.670)
(9.560) (-0.157)
(3.748)
Cochrane/Orcutt RHO = 0.272
R-squared = 0.991
D.W.
= 2.006

15.

PBBB = -0.143 + 0.008(TIME) + 1.500(ULC((-3.260) (2.277)
(4.324)

+ 0.00128(ENGY( -1 ))
(2.896)

Cochrane/Orcutt RHO = 0.373
R-squared = 0.996
D.W.
= 1.714
16.

POWN = 0.243 + 0.004(TIME) + 1.220(ULC(- 1)) + Q.00002(ENGY(—1))
(0.074)
(7.229) (1.271)
(4.815)
Cochrane/Orcutt RHO = 0.719
R-squared = 0.997
D.W.
= 1.386

17.

PTEN = 0.244 + 0.004(TIME) + 1.216(UCL(-1)) + 0.G0002(ENGY(-1))
(7.278) (1.290)
(4.823)
(0.075)
Cochrane/Orcutt RHO = 0.721
R-squared = 0.997
D.W.
= 1.387

18. PFAR = -0.931 - 0.009(TIME) + 3.373(ULC((-5.769) (-0.704)
(2.657)

+ 0.00387(ENGY(- 1))
(2.456)

Cochrane/Orcutt RHO = 0.500
R-squared = 0.986
D.W.
= 1.752
19.

POHO = -0.008 + 0.005(TIME) + 1.550(ULC((-0.214) (1.753)
(5.208)
Cochrane/Orcutt RHO = 0.423
R-squared = 0.996
D.W.
= 1.320

20.

PFNR = 0.246. - 0.002(TIME) + 1.497(ULC(-1))
(9.546) (-0.931)
(12.192)




70

+ 0.00021(ENGY(-1))
(0.562)

Cochrane/Orcutt RHO = 0.554
K-squared = 0.991
D.W.
= 1.741
21.

PAPP = 0.797 - Q.030(TIME) + 1.862(ULC(-1)) + 0.00025(ENGY( -1 ))
(15.075) (-6.899)
(4.511)
(0.503)
Cochrane/Orcutt RHO = 0.569
R-squared = 0.965
D.W.
= 1.784

22.

PCHN = -0.008 + 0.012(TIME) + 0.918(ULC(- 1)) + 0.00178(ENGY(-1))
(-0.220) (4.215)
(3.263)
(4.987)
Cochrane/Orcutt RHO = 0.404
R-squared = 0.997
D.W.
= 1.387

23.

PODH = 0.603 + O.Oll(TIME) + 0.00115(ENGY( - 1))
(37.140) (10.753)
(8.632)
Cochrane/Orcutt RHO = 0.467
R-squared = 0.985
D.W.
= 1.783

24.

PSDH = 0.391 - 0.007(TIME) + 1.452(ULC(-!)) + 0.00039(ENGY( -1 ))
(4.381) (-0.979)
(2.092)
(0.472)
Cochrane/Orcutt RHO = 0.604
R-squared = 0.959
D.W.
= 2.319

25.

PCLP = 0.115 + O.OOl(TIME) + 0.933(ULC(-!)) + 0.00351 (ENGY( - 1))
(2.660) (0.137)
(2.698)
(7.770)
Cochrane/Orcutt RHO = 0.199
R-squared = 0.993
D.W.
= 2.120

26.

PSTY = 0.023 + 0.004(TIME) + 1.489(ULC(-1)) + 0.00089(ENGY(-1))
(0.418) (1.010)
(3.373)
(1.570)
Cochrane/Orcutt RHO = 0.333
R-squared = 0.990
D.W.
= 1.702

27.

PELC = 0.171 - 0.009(TIME) + 1.741(ULC(-1)) + 0.00155(ENGY(- 1))
(3.093) (-2.096)
(4.000)
(2.851)
Cochrane/Orcutt RHO = 0.464
R-squared = 0.990
D.W.
= 1.767




71

28.

PNGS = -0.044 + 0.006(TIME) + 0.727(ULC(-1))
(-0.522) (0.895)
(1.150)

0.00443(ENGY (-l))
(5.530)

Cochrane/Orcutt RHO = 0.399
R-squared = 0.989
D.W.
= 1.691
29.

PWAT = -0.270 + 0.009(TIME) + 1.698(ULC(-1)) + 0.00075(ENGY(- 1))
(1.741)
(-6.231) (2.640)
((4.963)
Cochrane/Orcutt RHO = 0.419
R-squared = 0.996
D.W.
'' = 1.277

30.

PFUL = -0.525 - 0.018(TIME) + 3.395(ULC(-1))
(-3.350) (-1.486)
(2.720)

0.00335(ENGY( —1))
(2.054)

Cochrane/Orcutt RHO = 0.203
R-squared = 0.967
D.W.
= 1.878
31.

PTEL = 0.620 + 0.0004(TIME) + 0.670(ULC(-1))
(16.491) (0.125)
(4.493)
Cochrane/Orcutt RHO = 0.782
R-squared = 0.984
D.W.
= 1.297

32.

PDMS = -0.542 + 0.024(TIME) + 1.612(ULC(-1))
(-4.753) (2.528)
(2.697)

0.00049(ENGY(- 1))
(0.794)

Cochrane/Orcutt RHO = 0.876
R-squared = 0.996
D.W.
= 1.896
33.

POPO = -0.231 + 0.0001 (TIME) + 2.242(ULC(-1)) + 0.00005(ENGY( —1))
(0.167)
(-7.720) (0.044)
(9.412)
Cochrane/Orcutt RHO = 0.150
R-squared = 0.996
D.W.
= 2.089

34.

PDRG = 0.700 - 0.006(TIME) + 0.708(ULC(-1)) + 0.00088(ENGY(-1))
(11.360) (-1.061)
(2.013)
(2.428)
Cochrane/Orcutt RHO = 0.861
R-squared = 0.987
D.W.
= 1.104

35.

POPT = -0.099 + 0.018(TIME) + 1.003(ULC(- 1))
(-1.085) (3.239)
(3.577)




72

0.00020(ENGY(- 1))
(0.735)

Cochrane/Orcutt RHO = 0.922
R-squared = 0.998
D.W.
= 1.593
36.

PPHY = -0.302 + 0.009(TIME) + 1.815(ULC(-1)) + 0.00058(ENGY( -1 ))
(-6.889) (2.388)
(5.499)
(1.555)
Cochrane/Orcutt RHO = 0.722
R-squared = 0.998
D.W.
= 1.876

37.

PDEN = -0.264 + 0.022(TIME) + 1.081(ULC(-1)) + 0.00042(EMGY( -1 ))
(-3.454) (4.237)
(3.898)
(1.518)
Cochrane/Orcutt RHO = 0.911
R-squared = 0.999
D.W.
= 2.046

38.

POPS = -0.302 + 0.009(TIME) + 1.836(ULC(-1)) + 0.00058(ENGY(-1))
(-7.032) (2.334)
(5.651)
(1.554)
Cochrane/Orcutt RHO = 0.716
R-squared = 0.998
D.W.
= 1.890

39.

PPHO = -0.362 + 0.007(TIME) + 1.960(ULC(-1)) + 0.00115(ENGY( -1))
(-7.406) (1.667)
(5.181)
(2.570)
.
i
Cochrane/Orcutt RHO = 0.634
R-squared = 0.998
D.W.
= 1.863

40.

PHIN = -0.324 - 0.002(TIME) + 2.408(ULC(- 1)) + 0.00029(ENGY(- 1))
(-2.314) (-0.159)
(2.179)
(0.211)
Cochrane/Orcutt RHO = 0.461
R-squared = 0.964
D.W.
= 2.171

41.

PBRO = -0.071 + 0.031 (TIME)
(-0.697) (7.148)
Cochrane/Orcutt RHO = 0.760
R-squared = 0.972
D.W.
= 1.522

42.

PBNK = 0.693 + 0.0001 (TIME) + 0.370(ULC(-1)) + 0.00130(ENGY(- 1))
(2.654) (0.008)
(0.634)
(2.299)
Cochrane/Orcutt RHO = 0.937
R-squared = 0.990
D.W.
= 0.991




43.

PIMP = -0.341 + 0.008(TIME) + 2.039(ULC((-10.117) (3.126)
(12.497)
Cochrane/Orcutt RHO = 0.396
R-squared = 0.993
D.W.
= 1.523

44.

PLIF = -0.095 + 0.012(TIME) + 1.334(ULC((-2.958) (4.429)
(5.319)

+ 0.00Q41(ENGY( —1))
(1.345)

Cochrane/Orcutt RHO - 0.587
R-squared = 0.998
D.W.
= 1.684
45.

PGAL = -0.734 + 0.038(TIME) + 1.164(ULC((-4.680) (4.838)
(5.313)
Cochrane/Orcutt RHO = 0.927
R-squared = 0.998
D.W.
= 0.943

46.

PFUN = 0.007 + 0.025(TIME) + 0.450(ULC(-1)) + 0.00042(ENGY(—1))
(1.472)
(0.106) (5.168)
(1.579)
Cochrane/Orcutt RHO = 0.896
R-squared = 0.998
D.W.
= 1.911

47.

PPBO = -0.018 - 0.001 (TIME) + 1.902(ULC((-0.634) (-0.639)
(8.272)

+ 0.00036(ENGY( -1 ))
(1.198)

Cochrane/Orcutt RHO = 0.206
R-squared = 0.996
D.W.
= 1.840
48.

PCAR = 0.270 + O.Oll(TIME) + 0.471(ULC(-1)) + 0.00142(ENGY(- 1))
(6.845) (3.620)
(1.505)
(3.556)
Cochrane/Orcutt RHO = 0.379
R-squared = 0.993
D.W.
= 2.160

49.

PTBA = 0.449 - Q.0Q2(TIME) + 0.992(ULC(-1)) + 0.00041 (EN G Y(-l))
(6.511) (-0.364)
(1.906)
(0.683)
Cochrane/Orcutt RHO = 0.717
R-squared = 0.976
D.W.
= 1.620

50.

PREP = -0.186 - O.OOl(TIME) + 2.175(ULC((-9.592) (-0.804)
(14.055)




74

+ 0.00036(ENGY(- 1))
(1.787)

Cochrane/Orcutt RHO = 0.129
R-squared = 0.998
D.W.
= 1.831
51.

PGAO = 0.036 - 0.003(TIME) + 1.909(ULC(-1)) + 0.00134(ENGY(-1))
(0.340) (-0.391)
(2.240)
(1.235)
Cochrane/Orcutt RHO = 0.371
R-squared = 0.971
D.W.
= 1.738

52.

PTOL = 1.000

53.

PAIN = 0.038 + 0.004(TIME) + 1.343(ULC(- 1))
(0.317) (0.439)
(2.329)
Cochrane/Orcutt RHO = 0.477
R-squared = 0.843
D.W.
= 1.462

54.

PSTR = -0.087 + 0.019(TIME) + 0.835(ULC(-1))
(-1.498) (3.888)
(3.586)
Cochrane/Orcutt RHO = 0.777
R-squared = 0.933
D.W.
= 1.340

55.

PTAX = 0.026(TIME) + 0.180(ULC(- 1)) + 0.00142(ENGY(-1))
(3.239)
(0.364)
(2.831)
Cochrane/Orcutt RHO = 0.858
R-squared = 0.995
D.W.
= 1.748

56.

PCRR = -0.104 + 0.019(TIME) + 0.854(ULC(-1))
(-1.881) (4.081)
(3.744)
Cochrane/Orcutt RHO = 0.767
R-squared = 0.993
D.W.
= 1.306

57.

PIRR = 0.130 - 0.007(TIME) + 1.880(ULC(-1)) + 0.00050(ENGY(-1 ))
(2.552) (-1.677)
(4.710)
(1.013)
Cochrane/Orcutt RHO = 0.541
R-squared = 0.992
D.W.
= 1.656

58.

PIBU = -0.301 - 0.002(TIME) + 2.367(ULC(-1)) + 0.00055(ENGY(- 1))
(-6.237) (-0.528)
(6.207)
(1.157)




75

Cochrane/Orcutt RHQ = 0.441
R-squared = 0.996
D.W.
= 1.930
59.

PIA1 = 0.081 - 0.003(TIME) + 1.838(ULC(-1))
(1.688) (-0.681)
(8.837)
Cochrane/Orcutt RHO = 0.736
R-squared = 0.991
D.W.
= 1.559

60.

PTRO = -0.417 + Q.022(TIME) + 1.405(ULC((-3.414) (2.708)
(3.342)

+ 0.00023(ENGY(- 1))
(0.546)

Cochrane/Orcutt RHO = 0.915
R-squared = 0.997
D.W.
= 1.799
61.

PBKS = 0.136 + O.OIQ(TIME) + 1.026(ULC(-1))
(9.196) (8.646)
(8.837)

0.00013(ENGY(- 1))
(0.926)

Cochrane/Orcutt RHO = 0.531
R-squared = 0.999
D.W.
= 1.725
62.

PMAG =

+
-0.238 +
0.018(TIME) + 1.170(ULC(- 0.00087(ENGY(- 1))
(-4.700) (4.178)
(4.224)
(3.064)

Cochrane/Orcutt RHO =0.870
R-squared = 0.999
D.W.
= 1.949
63.

PTOY = 0.318 + 0.004(TIME) + 1.015(ULC(-1))
(16.161) (2.462)
(10.869)
Cochrane/Orcutt RHO = 0.575
R-squared = 0.994
D.W.
= 1.668

64.

PWHG = 0.425 + 0.003(TIME) + 0.798(ULC(-1)) + 0.00049(ENGY(- 1))
(12.557) (1.254)
(3.004)
(1.510)
Cochrane/Orcutt RHO = 0.525
R-squared = 0.992
D.W.
= 2.014

65.

PRAD = 1.252 - 0.026(TIME) + 0.810(ULC(-1)) + 0.00025(ENGY(-1))
(14.013) (-3.402)
(1.189)
(0.321)
Cochrane/Orcutt RHO = 0.682
R-squared = 0.939
D.W.
= 0.827




76

66.

PRTV = 1.271 - 0.006(TIME) + 0.00056(ENGY( -1 ))
(5.351) (-0.726)
(2.034)
Cochrane/Orcutt RHO = 0.933
R-squared = 0.981
D.W.
= 0.628

67.

PFLO = 0.244 - 0.006(TIME) + 1.654(ULC(-1))
(4.346) (-1.280)
(6.319).
Cochrane/Orcutt RHO = 0.634
R-squared = 0.965
D.W.
= 2.022

68.

PMOY = -0.508 + 0.037(TIME) + 0.774(ULC(-1))
(-8.125) (9.291)
(5.551)
Cochrane/Orcutt RHO = 0.893
R-squared = 0.999
D.W.
= 1.123

69.

PLEG = -0.407 + 0.036(TIME) + 0.622(ULC( -1 ))
(-5.598) (7.701)
(3.766)
Cochrane/Orcutt RHO = 0.891
R-squared = 0.998
D.W.
= 1.141

70.

PSPE = 0.237 + 0.009(TIME) + 0.924(ULC( -1 )) + 0.00025(ENGY( -1 ))
(6.555) (2.693)
(3.384)
(0.802)
Cochrane/Orcutt RHO = 0.713
R-squared = 0.996
D.W.
= 1.686

71.

PCLU = -0.024 + 0.003(TIME) + 1.750(ULC(-1)) + 0.00009(ENGY(-1))
(-0.878) (1.306)
(7.995)
(0.323)
Cochrane/Orcutt RHO = 0.222
R-squared = 0.996
D.W.
= 1.850

72.

PCOM = -0.060 + 0.014(TIME) + 1.180(ULC(-1)) + 0.00027(ENGY(-1))
(-2.802) (8.208)
(6.936)
(1.290)
Cochrane/Orcutt RHO = 0.461
R-squared = 0.999
D.W.
= 1.811

73.

PPAR = -0.079 + 0.012(TIME) + 1.279(UCL(-1))
(-0.980) (2.323)
(6.618)




77

Cochrane/Orcutt RHO = 0.884
R~squared = 0.996
D.W.
= 1.395
74.

PREO = 0.148 + 0.014(TIME) + 0.819(ULC(-1)) + 0.00003(ENGY (- 1))
(2.753) (3.292)
(3.125)
(0.104)
Cochrane/Orcutt RHO = 0.884
R-squared = 0.998
D.W.
= 1.754

75.

PHED = -0.572 + 0.038(TIME) + 0.778(ULC(-1)) 4- 0.00046(ENGY(-1))
(-5.406) (5.687)
(2.295)
(1.391)
Cochrane/Orcutt RHO = 0.919
R-squared = 0.998
D.W.
= 1.714

76.

PEED =• -0.254 - 0.001 (TIME) + 2.337(ULC(-1)) + 0.00041 (ENGY(- 1))
(-4.928) (-0.128)
(5.758)
(0.817)
Cochrane/Orcutt RHO = 0.479
R-squared = 0.996
D.W.
= 1.602

77.

POED = 0.003 + Q.006(TIME) + 1.338(ULC(-1)) + 0.00117(ENGY( -1 ))
(0.061) (1.828)
(3.872)
(2.648)
Cochrane/Orcutt RHO = 0.346
R-squared = 0.994
D.W.
= 1.847

78.

PREL - -0.059 - 0.0002(TIME) + 1.866(ULC(-1)) + 0.00069(ENGY(-1 ))
(-1.545) (-0.059)
(6.119)
(1.732)
Cochrane/Orcutt RHO = 0.217
R-squared = 0.994
D.W.
= 1.817

79.

PFTV = -0.052 - 0.002(TIME) + 2.115(ULC(-1)) + 0.00007(ENGY(-1 ))
(-0.470) (-0.181)
(2.511)
(0.074)
Cochrane/Orcutt RHO = 0.666
R-squared = 0.982
D.W.
= 1.518

80.

PABD = -0.230 - Q.019(TIME) + 3.121(ULC(- 1)) + 0.00111(ENGY(-1 ))
(-1.923) (-1.951)
(3.325)
(0.962)
Cochrane/Orcutt RHO = 0.520
R-squared = 0.979
D.W.
= 1.399




78

81.

PEXF = -0.010 - 0.003(TIME) + 2.001 (ULC(- 1)) + 0.00016(ENGY(-1))
(-0.300) (-1.021)
(7.737)
(0.496)
Cochrane/Orcutt RHO = 0.380
R-squared = 0.996
D.W.
= 1.668

82.

PREM = 0.106 - 0.006(TIME) + 1.979(ULC(- 1)) + 0.00008(ENGY( -1))
(2.043) (-1.365)
(4.839)
(0.158)
Cochrane/Orcutt RHO = 0.450
R-squared = 0.990
D.W.
= 1.586




79

Appendix 0. Federal
Government Equations

Regression equations were used to derive the levels of
defense purchases and defense compensation, using
variables supplied from the macro model. Since only
total civilian compensation and total Federal purchases
were available, they had to be allocated to the defense

and nondefense sectors. Regression equations were also
used for estimating defense and nondefense new con­
struction. Equations used in the Federal Government
sector are given below:

1. Defense civilian compensaton = 122.3 + 0.4093 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 civilian employment
+ 0.0232 nondefense other purchases - 69.01 time

4.

Nondefense nonresidential construction = -1731 + 3.30013 nondefense civilian employment
- 0.013 nondefense other purchases - 35.981 time
R-squared = 0.4515

5.

Nondefense highway construction

- 116.344 + 0.261 nondefense civilian employment
- 0.0032 nondefense other purchases + 8.298 time

R-squared = 0.9462
6.

Nondefense industrial construction

- 1977.4 + 4.284 nondefense civilian 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




80

9.

10.

Defense nonresidential construction = 641.2 - 0.270 military employment
+ 0.0182 defense other purchases - 1.716 time
R-squared = 0.7723
Defense industry construction = 2794.7 - 0755 military employment
+ 0.0392 defense other purchases - 64.986 time
R-squared = 0.8468




81

Appendix E. Labor
Demand Equation®

1. Livestock and livestock products (EG !, 2)
Hours = 13.6008 - 0.0034 UR - 0.2729 0 + 0.0288 E + 0.0319 P - 0.0444 L -0.3969 CD - 1.9584 LD
(6.91231) (-0.128739) (-1.43117) (8.46595) (9.37601)
( - 13.0415)(-26.0707) (-128.648)
R-squared = 0.9997
2. Other agricultural products (EG 3-5)
Hours = 14.3160 + 0.0787 UR - 0.3692 O + 0.0338 E + 0.0369 P - 0.0262 L - 0.3969 CD - 1.8690 LD
(6.47470) (1.79880)
( - 1.69568) (6.87544) (7.50514) (-5.32942) ( - 15.1853) (-71.5102)
R-squared = 0.9990
3. Forestry and fishery products (EG 6)
Hours = 10.6621 + 0.0750 UR - 0.0100 0 + 0.0260 E + 0.0291 P + 0.0012 L - 0.3969 CD -6.2216 LD
(27.7360) (1.06852)
(—
0.177016) (9.33735) (10.4496) (0.441836) ( - 11.0334) ( - 172.964)
R-squared = 0.9998
4. Agricultural, forestry, and fishery services (EG 7)
Hours = 13.3900 + 0.0638 UR - 0.3570 0 + 0.0344 E+ 0.0375 P + 0.0327 L - 0.3969 CD - 4.6109 LD
(12.4061) (1.21591)
(-2.68407) (9.40896) (10.2552) (8.94229)
( - 13.3616) ( - 155.234)
R-squared = 0.9997
5. Iron and ferroalloy ores mining (EG 8)
Hours = 4.5327 - 0.0054 UR + 0.1548 0 + 0.0807 E + 0.0810 P - 0.0136 L + 1.1977 CD - 1.3237 LD
(3.30527) (-0.058401) (0.825382) (8.07832) (8.11388) ( - 1.36613) (15.0406)
( - 16.6230)
R-squared = 0.9950
6. Nonferrous metal ores mining (EG 9, 10)
Hours = 4.2638 - 0.0689 UR + 0.2603 0 + 0.0762 E + 0.0603 P - 0*0081 L + 1.4226 CD - 1.1806 LD
(6.34762) ( - 1.63999) (2.73376) (12.3301) (9.76253) ( - 1.31604) (34.4806)
(-28.6154)
R-squared = 0.9985
7. Coal mining (EG 11)
Hours = 3.8374 + 0.1821 UR + 0.3728 0 + 0.0672 E + 0.0673 P + 0.0042 L + 0.0090 CD - 1.5497 LD
(1.37960) (2.16080)
(1.17085) (9.86153) (9.86751) (0.613626) (0.159835) (-27.3833)

R-squared = 0.9951




82

8.

Crude petroleum and natural gas (EG 12)
Hours = 8.7156 - 0.0207 UR + 0.0692 O - 0.0028 E + 0.0130 P - 0.0214 L + 1.5518 CD - 3.2333 LD
(3.36521) (-5.53421) (60.9724)
( - 127.044)
(6.40493) (-0.667125) (0.491384) (-0.713211)
R-squared = 0.9998

9.

Stone and clay mining and quarrying (EG 13)
Hours - 4.6830 + 0.0184 UR + 0.2604 0 + 0.0679 E + 0.0650 P ■ 0.0058 L - 0.2872 CD - 1.2337 LD
(3.05384) (0.523130) (1.31982) (12.1197) (11.6065) ( - 1.03041) (-9.03203) (-38.8002)
R-squared = 0.9979

10. Chemical and fertilizer mineral mining (EG 14)
Hours = 5.1830 - 0.2028 UR + 0.1620 0 + 0.0418 E + 0.0742 P - 0.0244 L - 0.2596 CD - 1.9247 LD
(6.31509) (-3.15457) (1.34253) (5.82662) (50.3392) (-3.40316)(-4.37166) (-32.4108)
R-squared - 0.9963
11. New construction (EG 152)
Hours = 6.0836 - 0.0423 UR + 0.2887 O + 0.0291 E + 0.0781 P + 0.0095 L
(4.31199) (-1.35295) (2.41042) (9.29871) (24.9696) (3.03425)

1.7520 CD - 0.5320 LD
(-62.9406) (-19.1113)

R-squared = 0.9965
12. Maintenance and repair construction (EG 15)
Hours = 5.3183 - 0.0744 UR + 0.39920 + 0.0317E + 0.0807 P + 0.0153 L - 1.7520CD - 2.1620 LD
(2.96814) (-2.86776) (2.32627) (13.0844) (33.2934) (6.33084) (-63.8638) (-78.8091)
R-squared = 0.9987
13. Ordnance and accessories (EG 16, 17)
Hours = 3.1448 + 0.0294 UR + 0.3522 O + 0.0461 E + 0.0037 P - 0.0009 L + 0.6777 CD - 0.3016 LD
(2.70101) (0.316957)
(2.93040) (6.05276) (0.488010) ( - 0 .1 13898) (6.88238)
(-3.06287)
R-squared = 0.9340
14. Food and kindred products (EG 18-27)
Hours = 8.8792 - 0.0016 UR + 0.0353 O + 0.0315 E + 0.0145 P - 0.0049 L + 0.0792 CD -1.0027 LD
(4.16032) (-0.124796) (0.186519) (6.15069) (2.83517) (-0.957202) (6.85121)
(-86.7477)
R-squared = 0.9994
15. Tobacco manufactures (EG 28)
Hours = 1.5655 - 0.0114 UR + 0.5101 O + 0.0310 E + 0.0382 P - 0.0181 L - 0.5084 CD - 0.8863 LD
(1.48673) (-0.485025) (4.37784) (19.0565) (23.4586) ( - 11.0995) (-23.0646) (-40.2107)
R-squared = 0.9976
16.

Broad and narrow fabrics, yarn and thread mills (EG 29)
Hours = 9.2822 - 0.0508 UR - 0.0893 O + 0.0193 E + 0.0283 P + 0.0010 L - 0.8725 CD - 1.1998 LD
(5.82461) (-1.42139) (-0.546087)(5.22876) (7.66117) (0.272988) (-37.5934) (-51.6932)

R-squared = 0.9973




83

17.

Miscellaneous textile goods and floor coverings (EG 30, 31)
Hours = 2.0156 + 0.1531 UR + 0.5673 O + 0.0024 E + 0.0085 P - 0.0103 L - 0.7053 CD - 1.2938 LD
(1.86091) (4.62258)
(4.14193) (0.267436) (0.944787) ( - 1.14546) (-21.3907) (-39.2407)
R-squared = 0.9951

18.

Apparel (EG 32, 33)
Hours = 0.9133 + 0.1706 UR + 0.6108 O+ 0.0309 E + 0.0322 P - 0.0076 L - 0.5044 CD + 0.5430 LD
(0.2-22410) (2.15553)
(1.50163) (2.27588) (2.36958) (-0.558559) ( - 10.8482) (11.6777)
R-squared = 0.9724

19.

Miscellaneous fabricated textile products (EG 34)
Hours = 3.7940 + 0.0743 UR + 0.1937 0 + 0.0541 E + 0.0265 P + 0.0095 L + 0.0066 CD +0.1910 LD
(2.82293) (1.24656)
(1.16044) (5.69237) (2.78834) (1.00359) (0.132210) (3.82449)
R-squared = 0.9330

20.

Lumber and wood products, except containers (EG 35-37)
Hours = 6.4703 +
0.0033 UR+0.1686 O
+0.0332 E+0.0178 P0.0021 L - 0.2081 CD - 0.8342 LD
(5.63328) (0.167066)
(1.40066) (8.16557) (4.37993) ( —
0.518689)(-9.92489) (-39.7951)
R-squared = 0.9971

21. Wood containers (EG 38)
Hours = 4.8624 - 0.0415 UR + 0.2374 O - 0.0792 E + 0.0072 P - 0.0277 L - 1.3149 CD - 1.7521 LD
(7.49817) (-0.821236) (2.77851) (-20.4344) (1.85919) (-7.15993) (-40.0025) (-53.3055)
R-squared = 0.9948
22.

Household furniture (EG 39)
Hours = 3.2963 +
0.0169 UR + 0.3565 O+ 0.0268 E +
(3.37712)(0.732097)
(3.06709) (5.68664) (7.51702)

0.0354 P +
0.0080 L 0.0667 CD - 0
(1.69677) (-2.22233) ( - 1.74979)

R-squared = 0.9698
23. Other furniture and fixtures (EG 40)
Hours = 1.8642 + 0.0655 UR + 0.4782 O + 0.0225 E + 0.0241 P - 0.0040 L + 0.2351 CD - 0.0118 LD
(0.877395)0.19511)
(1.75683) (1.81666) (1.94321) ( -0.322818)(6.95322)
(-0.347798)
R-squared = 0.9764

24. Paper and allied products, except containers (EG 41)
Hours = 11.4240 - 0.0917 UR - 0.2542 O + 0.0528 E + 0.0437 P + 0.0193 L - 0.9117 CD - 2.0606 LD
(9.47887) (-5.58110)
( - 1.99604) (9.97459)
(8.25491) (3.65087) ( —
63.5316)(-143.5
R-squared = 0.9997
25. Paperboard containers and boxes (EG 42)
Hours= 4.6944 - 0.0696 UR + 0.3210 0 + 0.0282 E + 0.0256 P + 0.0016 L - 0.5515 CD - 1.3080 LD
(2.74605) (-1.91986) (1.63550) (3.67429) (3.33732) (0.203776) (-27.5545) (-65.3491)
R-squared = 0.9985




84

26. Printing and publishing (EG 43-45)
Hours = 5.4383 + 0.0246 UR + 0.2970 O +0.0279 E + 0.0286 P + 0.0061 L + 0.1821 CD - 0.8713 LD
(1.87830) (0.485899)
(1.02668) (2.94533) (3.01958) (0.642763) (6.76459)
(-32.3730)
R-squared = 0.9964
27. Chemicals and selected chemical products (EG 46-48)
Hours - 12.2840 - 0.1323 UR - 0.3256 0 +0.0637 E + 0.0551 P + 0.0253 L - 0.6056 CD -2.3618 LD
(6.64606) (-4.10280) ( - 1.66836)(6.22081) (5.38730) (2.47368) (-26.6406) ( - 103.889)
R-squared = 0.9994
28. Plastics and synthetic materials (EG 49, 50)
Hours = 6.5891 - 0.1022 UR + 0.18800 + 0.0521 E + 0.0392 P + 0.0143 L - 0.8771 CD - 2.1187 LD
(6.01647) (-3.21263) (1.42187) (5.11852) (3.85139) (1.40439) (-34.4645) (-85.9998)
R-squared = 0.9991
29. Drugs, cleaning and toilet preparations (EG 51, 52)
Hours = 4.9239 + 0.0742 UR + 0.2692 0 + 0.0220E + 0.0319 P + 0.0125 L + 0.0276 CD - 1.4202 LD
(2.11004) (3.26408)
(1.00559) (1.16926) (1.69481) (0.665064) (1.04765)
(-53.8526)
R-squared = 0.9981
30.

Paints and allied products (EG 53)
Hours = 6.7258 - 0.0223 UR - 0.1090 O + 0.0384 E + 0.0397 P + 0.0118 L + 0.0078 CD - 0.9908 LD
(6.30485) (-0.686122) (-0.815002) (8.32502) (8.62067) (2.56928) (0.281589)
(-35.9648)
R-squared = 0.9966

31.

Petroleum refining and related industries (EG 54)
Hours = 4.5834 + 0.2197 UR + 0.3257 O +0.0177 E + 0.0051 P - 0.0136 L + 1.3573 CD - 2.0936 LD
(1.18002) (4.50709)
(0.828256) (1.22176) (0.354877) (-0.941718) (28.4878)
(-43.9415)
R-squared = 0.9984

32. Rubber and miscellaneous plastics products (EG 55-57)
Hours = 7.8685 - 0.0309 UR + 0.0133 0 + 0.0669 E + 0.0720 P + 0.0435 L - 1.0853 CD - 1.3816 LD
(5.17595) (-0.910362) (0.081024) (6.81074) (7.32732) (4.42288) (-46.5702) (-59.2870)
R-squared = 0.9983
33. Leather tanning and finishing (EG 58)
Hours = 3.6835 + 0.0087 UR + 0.1764 0 + 0.0079 E + 0.0071 P - 0.0241 L - 0.4201 CD - 0.5988 LD
(2.94074) (0.193339) (1.04962) (2.28535) (2.05912) (-6.99006) (-11.8930) (-16.9496)
R-squared = 0.9853
34. Footwear and other leather products (EG 59)
Hours - 3.5505 + 0.0426 UR + 0.2830 0 + 0.0140 E + 0.0082 P - 0.0138 L - 0.2399 CD + 0.5216 LD
(1.25535) (0.517285) (0.889554) (5.33099) (3.10942) (-5.26285) (-7.31095) (15.8967)
R-squared = 0.9699




85

35.

Glass and glass products (EG 60)
Hours = 7.0440 - 0.0375 UR +0.0163 0 + 0.0528 E + 0.0365 P + 0.0199 L - 0.3030 CD - 1,4043 LD
(9.36470) ( -2.66054) (0.178361) (14.9031) (10.2802) ( 5.62122) (-21.2361) ( -98.4292);
R -squared = 0.9994

36. Stone and clay products (EG 61-64)
Hours = 6.5720 - 0.0130UR + 0.2120 0 + 0.0172 E + 0.0156 P + 0.0033 L - 0.3079 CD - 1.6663LD
(9.51766) ( - 1.10592) (2.87121) (7.57050) (6.84357) (1.44762) ( - 21.0470) ( - 113.912)
R -squared = 0.9994
37. Primary iron and steel manufacturing (EG 65, 66)
Hours = 9.6868 - 0.0339 UR -10.0136 O + 0.0330 E + 0.0018 P + 0.0069 L + 0.0536 CD - 2.0155 LD
(6.83919) ( - 1.35926) ( -0.101250) (9.77175) (0.524092) (2.03228) (1.87778) ( -70.5423)
R-squared = 0.9987
38.

Primary nonferrous metals manufacturing (EG 67-69)
Hours =
9.1374 0.0237 UR
(5.52458) (-0.950302) (-0.518528) (7.48121)

0.0881 O
(5.99761)

+
(3.34683)

0.0484 E+ 0.0388 P
+ 0.02
( - 12.2833) (-56.6887)

R-squared = 0.9979
39.

Metal containers (EG 70)
Hours =
2.8267 +
(5.49407) (2.59985)

0.0219 UR
+
(7.32983) (10.7829)

0.4741 O
+ 0.0293 E + 0.0057 P - 0.0022 L - 0
(2.11723) (-0.824418)(-63.4256)
( - 123.100)

R-squared = 0.9996
40.

Heating, plumbing, and structural metal products (EG 71, 72)
Hours = 3.7643 + 0.0377 UR + 0.3793 O + 0.0236 E + 0.0231 P + 0.0068 L - 0.0238 CD -0.5625 LD
(3.76899) (2.40861)
(3.50391) (5.44062) (5.32441) (1.56185) ( - 1.26305) (-29.8857)
R-squared = 0.9958

41.

Screw machine products and stampings (EG 73, 74)
Hours = 6.4888 - 0.0577 UR + 0.1406 0 + 0.0199 E + 0.0255 P + 0.0157 L - 0.6740 CD - 1.3083 LD
(4.71249) ( - 1.39467) (0.955580) (4.68727) (6.01209) (3.69587) (-21.9807) (-42.6654)
R-squared = 0.9952

42. Other fabricated metal products (EG 75, 76)
Hours = 4.7401 - 0.0149 UR + 0.3194 0 + 0.0301 E + 0.0297 P + 0.0109 L - 0.4965 CD -0.9954 LD
(2.98904) (-0.479572) (1.86230) (4.36390) (4.30320) (1.57504) (-24.2211) (-48.5610)
R-squared = 0.9974
43. Engines and turbines (EG 77)
Hours = 2.4235 + 0.0707 UR + 0.4909 O + 0.0373 E + 0.0169 P - 0.0012 L - 0.2952 CD - 1.1839 LD
(3.75733) (4.39233)
(5.78988)
(6.07928) (2.75860) ( —
0.187541)( —
8.89214) (-35.6588)
R-squared = 0.9962




86

44. Farm and garden machinery (EG 78)
Hours = 4.7659 - 0.0103 UR + 0.2317 O + 0.0156 E ‘ + 0.0208 P + 0.0066 L - 0.4062 CD - 1.1012 LD
(8.67798) (-0.521196) (3.46775)
(4.12825) (5.51149) (U76264) ( - 11.1736) (-30.2937)
R-squared = 0.9918
45. Construction and mining machinery (JEG 79)
Hours = 3.7526 + 0.0517 UR + 0.3676 0 + 0.0249 E + 0.0285 P + 0.0159 L - 0.5476 CD - 1.2260 LD
(4.93452) (2.73460)
(4.11630) (5.32296) (6.07852) (3.40269) ( - 16.6734) (-37.3316)
R-squared = 0.9946
46. Materials handling machinery and equipment (EG 80)
Hours = 2.5465 + 0.0317 UR + 0.3357 0 + 0.0363 E + 0.0108 P + 0.0162 L + 0.7116 CD -0.1875 LD
(2.42657) (0.940534) (2.40149) (4.75064) (1.40991) (2.11660) (19.5749)
(-5.15835)
R-squared = 0.9869
47. Metalworking machinery and equipment (EG 81)
Hours = 2.2360 +
0.0900 UR+
0.5925 0 +
(1.18056) (1.33777)
(2.80954) (2.73540)

0.0177 E +
0.0062 P+
0.0017 L (0.962646) (0.267561) (-7.87024) (-25.8447)

0.3373

0.0325 E +
0.0411 P+
0.0074 L (7.34807) (1.31880) ( - 14.1391) (-25.3705)

0.4646

R-squared = 0.9897
48. Special industry machinery and equipment (EG 82)
Hours = 5.7346 0.0365 UR+
0.1241 O+
(4.03606) (-0.944480) (0.744430) (5.80711)
R-squared = 0.9921
49. General industrial machinery and equipment (EG 83)
Hours =
6.3487 - 0.0376 UR + 0.0842 0
+ 0.0459 E + 0.0439 P+ 0.0189 L - 0.3861 CD - 0.9124
(4.32158) (-0.934518) (0.504309) (6.94789) (6.65007)
(2.85843)
( - 12.0326)(-28.4386)
R-squared = 0.9939
50. Miscellaneous machinery, except elecrical (EG 84)
Hours =
3.1817 - 0.0407 UR + 0.3891 O
(3.81756) (-1.60017) (3.74872) (10.2121)

+0.0548 E +0.0467 P + 0.0062 L - 0.4773 CD -0.2583 LD
(8.71370) (1.15650) ( - 13.2734) (-7.18471)

R-squared = 0.9885
51. Office, computing, and accounting machines (EG 85-86)
Hours = 4.4281 + 0.0269 UR + 0.2079 0 + 0.0789 E + 0.0355 P + 0.0356 L + 0.1727 CD - 0.4681 LD
(4.95590) (1.23509)
(1.82346) (7.15927) (3.21694) (3.23206) (4.91727)
(-13.3307)
R-squared = 0.9923
52. Service industry machines (EG 87)
Hours = 2.4574 + 0.0730 UR + 0.4904 O + 0.0047 E + 0.0053 P - 0.0011 L - 0.1298 CD - 1.0844 LD
(2.69108) (3.79476)
(4.05958)
(0.388016) (0.440303) (-0.094667)(-3.39648) (-28.3829)
R-squared = 0.9925




87

53. Electric industrial equipment and apparatus (EG 88, 89)
Hours = 3.4693 + 0.0644 UR + 0.4008 O + 0.0298 E + 0.0196 P + 0.0032 L + 0.0005 CD -0.5371 LD
(1.79041) (1.32354)
(1.84710) (2.92778) (1.92703) (0.316287) (0.014774) ( - 15.4072)
R-squared = 0.9873
54. Household appliances (EG 90)
Hours - 7.1620 - 0.0049 UR - 0.0683 O + 0.0334 E + 0.0223 P + 0.0214 L - 0.0300 CD - 0.8966 LD
(4.18275) (-0.111250) (-0.332826) (3.14145) (2.09656) (2.01344) ( - 1.00173) (-29.9648)
R-squared = 0.9931
55.' Electric lighting and wiring equipment (EG 91)
Hours = 3.6073 - 0.0125 UR + 0.3478 O + 0.0360 E + 0.0342 P + 0.0207 L - 0.5277 CD - 0.7943 LD
(1.77763) (-0.318578) (1.39823)
(3.31318) (3.14128) (1.90372) ( - 15.8689) (23.8852)
R-squared = 0.9910
56. Radio, television, and communication equipment (EG 92-94)
Hours = 5.2123 - 0.0275 UR + 0.1823 0 + 0.0725 E + 0.0417 P + 0.0070 L + 0.2659 CD + 0.1425 LD
(6.90274) (-9676843) (2.29905) (12.2863) (7.07512) (1.18065) (5.97506)
(3.20241)
R-squared = 0.9760
57. Electronic components and accessories (EG 95)
Hours = 5.0243 - 0.1583 UR + 0.1863 0 + 0.1073 E + 0.0686 P + 0.0244 L - 0.1208 CD - 0.1312 LD
(4.09080) (-2.64959) (1.25091) (7.63724) (4.87907) (1.73891) (-2.56355) (-2.78474)
R-squared = 0.9897
58. Miscellaneous electrical machinery and supplies (EG 96)
Hours = -0.1909 + 0.1706 UR + 0.7548 O + 0.0171 E + 0.0138 P - 0.0188 L - 0.4495 CD - 0.4559 LD
(-0.078609X3.24880)
(2.41385)
(0.978065) (0.789043) ( - 1.07500) ( - 10.2960) ( - 10.4421)
R-squared = 0.9805
59. Motor vehicles and equipment (EG 97)
Hours = 7.6538 - 0.0127 UR + 0.111 O + 0.0268 E + 0.0309 P + 0.0180 L - 0.6323 CD - 1.5499 LD
(5.12740) (-0.473320) (0.794313) (3.93478) (4.53269) (2.64707) ( - 14.6492) (-35.9084)
R-squared = 0.9937
60. Aircraft and parts (EG 98)
Hours = 0.7045 + 0.0728 UR + 0.6786 O + 0.0488 E + 0.0182 P - 0.0194 L + 0.5444 CD - 0.1330 LD
(0.622703) (1.62612)
(6.19148) (12.8435) (4.78590)
(-5.11866) (10.2990)
(-2.51536)
R-squared = 0.9799
61. Other transportation equipment (EG 99-102)
Hours = 3.3285 + 0.1155 UR + 0.3468 O + 0.0214 E - 0.0116 P + 0.0216 L + 0.9453 CD - 0.4124 LD
(2.46187) (3.16697)
(2.17915)
(1.76423) (-0.953124) (1.78304) (16.8219)
(-7.33835)
R-squared = 0.9777




88

62. Scientific and controlling instruments (EG 103-104, 107)
Hours = 6.8865 - 0.0523 UR - 0.0432 O + 0.0511 E + 0.0678 P + 0.0316 L - 0.2551 CD - 0.5165 LD
(7.44723) (-3.34672) (-0.392407) (10.3087) (13.6724) (6.36368) ( - 8.94246) ( - 18.1056)

ss
R-squared = 0.9917
63. Optical, ophthalmic, and photographic equipment (EG 105, 106)
Hours = 3.3484 + 0.0583 UR + 0.3818 0 + 0.0389 E + 0.0376 P - 0.0116 L - 0.1798 CD - 0.6272 LD
(6.90956) (3.74925)
(5.94866) (6.59703) (6.36965) ( - 1.96511) (-5.61340) ( - 19.5838)
R-squared = 0.9945
64. Miscellaneous manufacturing (EG 108-110)
Hours = 6.9081 - 0.0209 UR -0.0289 O + 0.0529 E + 0.0529 P + 0.0105 L - 0.2012 CD + 0.0965 LD
(6.10093) ( - 1.69765) (-0.225030) (9.83592) (9.83685) (1.95074) ( - 11.6485) (5.58724)
R-squared = 0.9918
65. Transportation and warehousing (EG 111-117)
Hours .= 9.7853 - 0.0089 UR + 0.1061 O +0.0269 E - 0.0115 P - 0.0006 L + 0.2011 CD - 2.2262 LD
(6.45064) (-0.855953) (0.751633) (5.40736) (-2.31799) (-0.129051) (14.7808)
( - 163.640)
R-squared = 0.9998
66. Radio and television broadcasting (EG 118)
Hours = 6.9223 - 0.0932 UR - 0.0817 O + 0.0894 E + 0.0828 P + 0.0312 L + 0.3552 CD - 0.9647 LD
(8.23618) (-2.70448) (-0.806311) (32.0578) (29.7142) (11.1787)
(10.7664)
(-29.2446)
R-squared = 0.9976
67. Communications, except radio and television (EG 119)
Hours = 3.6459 + 0.0009 UR + 0.6067 O + 0.0506E + 0.0077 P - 0.0194 L + 0.7159 CD - 2.0151 LD
(1.98253) (0.057214) (3.03905) (3.38110) (0.513385) ( - 1.29281) (36.0664)
( - 101.519)
R-squared = 0.9997
68. Electric, gas, water, and sanitary services (EG 120-122)
Hours = 16.2056 + 0.0805 UR - 0.6404 Q + 0.0982 E + 0.0836 P + 0.0520 L + 1.3283 CD - 2.6286 LD
(6.29216) (2.87725)
(-2.51998) (6.89201) (5.86418) (3.64760) (41.8917)
(-82.8999)
R-squared = 0.9995
69. Wholesale and retail trade (EG 123-125)
Hours ■ 7.5527 - 0.0095 UR + 0.2231 O + 0.0439 E + 0.0534 P + 0.0059 L + 0.1637 CD + 0.0045 LD
=
(3.26262) (-0.379661) (1.15739) (5.62240) (6.83613) (0.761329) (9.51478)
(0.259608)
R-squared = 0.9958
70. Finance and insurance (EG 126-128)
Hours = 17.2737 - 0.2367 UR - 1.0387 0 + 0.3002 E + 0.1051 P + 0.0696 L + 3.5167 CD + 2.3514 LD
(2.57278) ( - 1.87710) (-1.64790) (12.2407) (4.28656) (2.83659) (37.2821)
(24.9283)
R-squared = 0.9878




89

71.

Real estate and rental (EG 129, 130)
Hours = 7.9091 + 0.1184 UR + 0.0515 0 + 0.0240 E + 0.0578 P + 0.0183 L + 1.2531 CD + 1.3589 LD
(1.19588) (0.469198)
(-0.875903) (0.900736) (2.09085) (1.00259) ( - 12.1084) ( - 10.1148)
R-squared = 0.9224

72. Hotels; personal and repair services except auto (EG 131-133)
Hours = -0.6222 + 0.0041 UR + 0.9247 O + 0.0064 E + 0.0098 P - 0.0272 L + 1.6454 CD +0.0859 LD
(-0.285511X0.090010)
(4.33230) (1.05156) (1.61527) (-4.47190) (73.3688)
(3.83018)
R-squared = 0.0
73. Business services (EG 134-136)
Hours = 5.0285 - 0.0634 UR + 0.3501 O +0.0801 E + 0.0732 P + 0.0302 L - 1.7523 CD -0.5648 LD
(2.09731) ( - 1.15104) (1.55362) (6.80547) (6.22051) (2.56859) (-54.1671) ( - 17.4597)
R-squared = 0.9976
74. Automobile repair and services (EG 137)
Hours = 7.8774 - 0.1020 UR + 0.0250 0 + 0.0872 E + 0.0762 P + 0.0234 L - 0.1600 CD - 1.1922 LD
(5.35361) (-3.74399) (0.163979) (16.5724) (14.4917) (4.44650) (-7.44163) (-55.4426)
R-squared = 0.9990
75. Amusements (EG 138, 139)
Hours = 8.9309 - 0.0403 UR - 0.0932 O + 0.0696 E + 0.0725 P + 0.0252 L + 0.5733 CD - L1442 LD
(10.8057) ( - 1.24950) (-0.993733) (20.4597) (21.3059)
(7.41229) (25.0105)
(-49.9158)
R-squared = 0.9990
76. Medical and educational services and nonprofit organizations (EG 140-144)
Hours = 8.3694 - 0.0679 UR + 0.0743 0 + 0.0854 E + 0.0547 P + 0.0316 L + 1.7871 CD -0.1766 LD
(2.22602) (-3.09157) (0.210561) (5.29626) (3.39493) (1.96221) (102.013)
( - 10.0821)
R-squared = 0.9995
UR =
O =
E =
P =
L =
CD =
LD =

Unemployment rate
Output
Equipment time trend
Plant time trend
Labor time trend
Dummy variable-capital
Dummy variable-labor




90

Appendix F. Economic Growth Sectoring Plan




91

Appendix F. Economic Growth Sectoring Plan
Industry sector title

Industry sector
number

Bureau of Economic Analysis
input-output sector

Standard Industrial Classification(SiC) 1972

A g ric u ltu re , f o r e s tr y , a n d fis h e rie s

Dairy and poultry products....................................
Meat animals and liv e s to c k ..................................
C o tto n ......................................................................
Food and feed g ra in s ............................................
Agricultural products, n .e .c ...................................
Forestry and fishery products ..............................
Agricultural, forestry,and fishery
service s..................................................................

pt.01, pt. 02
pt. 01, pt. 02
pt. 01, pt. 02
pt. 01, pt. 02
pt. 01, pt. 02
08 (except 085), 091, 0971

1
2
3
14
5
6

1.01— 102
1.03
2.01
2.02
2.02—20.7
3.00

7

4.00

071, 072, 075, 078, 085, 092

8
9

5.00
6.01

101, 106
102

10
11
12
13
14

6.02
7.00
8.00
9.00
10.00

15

12.01— 12.02

pt. 15, pt. 16, pt. 17, pt. 138

M in in g

Iron and ferroalloy ores m in in g ............................
Copper ore m in in g .................................................
Nonferrous metal ores mining, except
copper ....................................................................
Coal m inin g.............................................................
Crude petroleum and natural g a s ........................
Stone and clay mining and quarrying..................
Chemical and fertilizer mineral m in in g ................

10 (except 101, 102, 106, pt. 108, 109)
11, 12
13 (except pt. 138)
14 (except 147, pt. 148)
147

M a in te n a n c e a n d r e p a ir c o n s tr u c tio n

Maintenance and repair construction..................
M a n u fa c tu r in g

Ordnance ................................................................
Complete guided missiles and space
ve h ic le s ..................................................................
Meat products ........................................................
Dairy products ........................................................
Canned and frozen fo o d s .....................................
Grain mill products.................................................
Bakery p ro d u c ts.....................................................
Sugar .......................................................................
Confectionery products .........................................
Alcoholic beverages ..............................................

16

13.02— 13.07

348, 3795

17
18
19
20
21
22
23
24
25

13.01
14.01
14.02— 14.06
14.07— 14.13
14.14— 14.17
14.18
14.19
14.20
14.21

3761
201
202
203, 2091 2092
204
205
2061— 2063
2065— 2067
208 (except 2086— 2087)

Soft drinks and flavo rings.....................................
Food products, n.e.c .............................................
Tobacco manufacturing.........................................
Fabric, yarn, and thread m ills ...............................
Floor covering mills ...............................................
Textile mill products, n .e .c ....................................
Hosiery and knit goods .........................................
A p p a re l....................................................................
Fabricated textile products, n .e .c.........................
Logging....................................................................

26
27
28
29
30
31
32
33
34
35

1422— 14.23
14.24— 14.32
15.01— 15.02
16.01— 16.04
17.01
17.02— 17.10
18.01— 18.03
18.04
19.01— 19.03
20.02

2086-2087
207, 209 (except 2091— 2092)
21
221— 224, 226, 228
227
229
225
23 (exceut 239), 39996
239
241

Sawmills and planing m ills ....................................
Millwork, plywood, and wood products,
n.e.cn.e.c.................................................................
Wooden containers................................................
Household furniture ...............................................
Furniture and fixtures, except
household ..............................................................
Paper p ro d u cts.......................................................
Paperboard .............................................................
Newspaper printing and publishing .....................
Periodical and book printing,
publishing...............................................................
Printing and publishing, n.e.c ...............................

36

20.02—20.04

37
38
39

20.05—20.09
21.00
22.01—22.04

243, 2448, 245 (except 2451), 249
244 (except 2448)
251

40
41
42
43

23.01—23.07
24.01—24.07
25.00
26.01

25 (except 251)
26 (except 265)
265
271

44
45

26.02—26.04
26.05— 26.08

272— 274
275— 279

46
47
48
49
50

27.01
27.02—27.03
27.04
28.01—28.02
28.03—28.04

281 (except 28195), 2865, 2869
287
2861, 289
2821— 2822
2823— 2824

Industrial inorganic and organic
che m icals...............................................................
Agricultural chem icals............................................
Chemical products, n.e.c ......................................
Plastic materials and synthetic ru b b e r................
Synthetic fib e rs .......................................................

Drugs ..........................................................................
Cleaning and toilet preparations.............................
Paints and allied products .......................................

51
52
53

29.01
29.02—29.03
30.00

See footnotes at end of table.




92

242

293
284
285

Appendix F. Economic Growth Sectoring Plan—Continued
Industry sector title

Industry sector
number

Bureau of Economic Analysis
input-output sector

Standard Industrial Classification (SIC) 1972

Petroleum refining and related products................
Tires and inner tubes ...............................................
Rubber products, except tires and tubes ..............
Plastic products.........................................................
Leather tanning and industrial leather ...................
Leather products, including fo o tw e a r.....................
G lass...........................................................................

54
55
56
57
58
59
60

31.01—31.03
32.01
32.02—32.03,32.05
32.04
33.00
34.01—34.03
35.01—35.02

Cement and concrete products ..............................
Structural clay products ...........................................
Pottery and related products...................................
Stone and clay products, n.e.c ...............................
Blast furnaces and basic steel products ...............
Iron and steel foundries and fo rg in g s ....................
Primacy copper and copper products.....................
Primary aluminum and aluminum products............
Primary nonferrous metals and products,
n .e .c ...........................................................................
Metal containers........................................................
Heating apparatus and plumbing fix tu re s ..............
Fabricated structural metal products......................
Screw machine products .........................................
Metal stam pings........................................................
Cutlery, handtools, and general hardw are.............
Fabricated metal products, n.e.c ............................
Engines, turbines, and generators..........................
Farm machinery ........................................................
Construction, mining, and oilfield
machinery .................................................................

61
62
63
64
65
66
67
68

324, 327
36.01,36.10—36.14
325
36.02—36.05
36.06—39.09
326
328, 329
36.15—36.22
37.01
331
37.02—37.04
332, 339, 3462
38.01, 38.07, 38.10, 38.12 3331, 3351, 3357, 3362
3334, 28195, 3353-55, 3361
38.04, 38.08, 38.11

69
70
71
72
73
74
75
76
77
78

29
301
3 0 2 -3 0 6
307
311
31 (except 311)
3 2 1 -3 2 3

38.02, 38.03, 38.05, 38.06 3332, 3333, 3339, 334, 3356, 3369, 3463
39.01— 39.02
341
40.01—40.03
343
40.04—40.09
344
41.01
345
41.02
346 (except 3462— 3463)
42.01—42.03
342
42.04—42.11
347, 349
43.01—43.026
351
44.00
352

79

45.01—45.03

Material handling equipment ...................................
Metalworking machinery...........................................
Special industry m achinery......................................
General industrial m achinery...................................
Nonelectrical machinery, n .e .c ................................
Computers and peripheral equipm ent....................
Typewriters and other office eq uipm e nt................
Service industry m achines.......................................
Electric transmission equipm e nt.............................
Electrical industrial apparatus .................................

80
81
82
83
84
85
86
87
88
89

46.01—46.04
47.01—47.04
48.01—48.06
49.01—49.07
50.00
51.01
51.02—51.04
52.01— 52.05
53.01— 53.03
53,04—53.08

353 (except 3531— 3533)
354
355
356
359
3573— 3574
357 (except 3573, 3574)
358
361, 3825
362

Household appliances..............................................
Electric lighting and w irin g .......................................
Radio and television receiving s e ts ........................
Telephone and telegraph apparatus ......................
Radio and communication equipm ent....................
Electronic com ponents.............................................
Electrical machinery and equipment,
n .e .c ...........................................................................
Motor ve h ic le s ...........................................................
Aircraft ........................................................................
Ship and boat building and repair ..........................

90
91
92
93
94
95

54.01—54.07
55.01— 55.03
56.01— 56.02
56.03
56.04
57.01— 57.03

363
364
365
3661
3662
367

96
97
98
99

58.01—58.05
59.01— 59.03
60.01—60.04
61.01—61.02

369
371
372, 376 (except 3761)
373

100
101
102
103
104
105
106

61.03
61.05
61.06—61.07
62.01—62.03
62.04—62.06
63.01—63.02
63.03

374
375
379 (except 3795), 2451
381, 382 (except 3825)
384
383, 385
386

107
108
109
110

62.07
64.01
64.02—64.04
64.05—64.12

387
391, 3961
393, 394
395, 396 (except 3961), 399 (except 39996)

111

65.01
65.02
65.03
65.04
65.05
65.06
65.07

Railroad equipm ent...................................................
Motorcycles, bicycles, and p a rts .............................
Transportation equipment, n.e.c .............................
Scientific and controlling instrum ents.....................
Medical and dental instrum ents..............................
Optical and ophthalmic equipm ent.........................
Photographic equipment and s u p plies...................
Watches, clocks, and clock-operated
d e vice s......................................................................
Jewelry and silverw are.............................................
Musical instruments and sporting g o o d s ...............
Manufactured products, n.e.c...................................

3531-3533

T r a n s p o r ta tio n

Railroad transportaion...........................................
Local transit and intercity b u s e s..........................
Truck transportation...............................................
Water transportation..............................................
Air transportation....................................................
Pipeline transportation...........................................
Transportation service s.........................................

112
113
114
115
116
117

See footnotes at end of table.




93

40, 474, pt. 4789
41
42, pt. 4789
44

45
46
47 (except 474, pt. 4789)

Appendix F. Economic Growth Sectoring Plan—Continued
Industry sector title

Industry sector
number

Bureau of Economic Analysis
input-output sector

Standard Industrial Classification(SIC) 1972

C om m unication
483

118

67.00

119

66.00

120
121

68.01, 78.02, 79.02
68.02

122

68.03

49 (except 491, 492, pt. 493)

123
124

69.01
74.01

50, 51
58

125

69.02

52-57, 59, 7396, pt. 8042

126
127
128
129
130

70.01
70.02— 70.02
70.04—70.05
71.01
71.02

Hotels and lodging p la c e s ....................................
Personal and repair services................................

131
132

72.01, 77.08
72.02

Barber and beauty shops .....................................
Business services, n.e.c.........................................
Advertising ..............................................................
Professional services, n.e.c...................................
Automobile re p a ir...................................................
Motion pictures.......................................................
Amusements and recreation service s.................
Doctors” and dentists” services..........................
Hospitals .................................................................
Medical services, except ho spitals......................
Educational services..............................................
Nonprofit organizations.........................................

133
134
135
136
137
138
139
140
141
142
143
144

72.03
73.01
73.02
73.03
75.00
76.01
76.02
77.01
77.02
77.03
77.04, 77.06—77.07
77.05, 77.09

145
146
147
148

78.01
78.03
78.04
79.01

43
n.a.
n.a.
n.a.

149

79.03

n.a.

150
151
152
153
154
155
156

80.00
81.00
n.a.
82.00
83.00
84.00
85.00

n.a.
n.a.
n.a.
n.a.
n.a.
n.a.
n.a.

Radio and television broadcasting .............. !......
Communications, except radio and
television................................................................

48 (except 483)

‘ Electric, gas, sanitary services
Electric utilities, public and private ......................
Gas utilities, excluding p u b lic ...............................
Water and sanitary services, excluding
p u b lic ......................................................................

491, pt. 493
492, pt. 493

Trade
Wholesale tra d e .....................................................
Eating and drinking places ...................................
Retail trade, except eating and
drinking p la c e s ......................................................
Finance, insurance, and real estate
Banking ...................................................................
Credit agencies and financial brokers.................
Insurance ................................................................
Owner-occupied real estate .................................
Real estate .......................................... ...................

60
61, 62, 67
63, 64
n.a.
65, 66, pt. 1531

O ther services
70, 836
72 (except 723. 724), 76 (except 7692, 7694, and
pt. 7699)
723, 724
73 (except 731, 7396), 7692, 7694, pt. 7699
731
81, 89 (except 8922)
75
78
79
801-803, 8041
806
074, 8049, 805, 807— 809
82, 833, 835
832, 839, 84, 86, 8922

G overnm ent enterprises
Post o ffic e ...............................................................
Commodity Credit C orporation.............................
Federal enterprises, n.e.c.......................................
Local government passenger tra n s it...................
State and local government enterprises, n.e.c.............................................................
Special industries
Noncomparable im p o rts........................................
Scrap, used and secondhand goods ..................
Construction indu stry.............................................
Government in d u s try .............................................
Rest of the world industry ....................................
H ouseholds.............................................................
Inventory valuation ad ju stm en t............................

T

n.e.c. = not elsewhere classified.




n-3- — n0* applicable.

94

Appendix G. Occupations Included in the
Industry-Occupational Mode!




95

Appendix G. Occupations included in the industry-occupational model
Occupation title

Occupation title
Total, all occupations

Health technologists and
technicians— Continued
Surgical technicians
X-ray technicians
All other health technologists and
technicians

Professional, technical, and related workers




Engineers
Aeronautical and astronautical
engineers
Chemical engineers
Civil engineers
Electrical engineers
Industrial engineers
Mechanical engineers
Metallurgical engineers
Mining engineers
Petroleum engineers
All other engineers

Technicians, except health, science,
and engineering
Airplane pilots
Air traffic controllers
Embalmers
Flight engineers
Radio operators
Technical assistants, library
Tool programmers, numerical
control
Other technicians, except health,
science, engineering

Life and physical scientists
Agricultural scientists
Biological scientists
Chemists
Geologists
Medical scientists
Physicists
All other life and physical
scientists

Computer specialists
Computer programmers
Computer systems analysts
Social scientists
Economists
Financial analysts
Psychologists
Sociologists
Urban and regional planners
All other social scientists

Mathematical specialists
Actuaries
Mathematicians
Statisticians
All other mathematical scientists

Teachers
Adult education teachers
College and university teachers
Dance instructors
Elementary school teachers
Extension service specialists
Graduate assistants
Preschool and kindergarten
teachers
Secondary school teachers
Vocational education teachers
All other teachers

Engineering and science technicians
Broadcast technicians
Civil engineering technicians
Drafters
Electrical and electronic
technicians
Industrial engineering technicians
Mechanical engineering technicians
Surveyors
All other engineering and science
technicians
Medical workers, except technicians
Chiropractors
Dentists
Dietitians
Nurses, professional
Optometrists
Pharmacists
Physicians, medical and
osteopathic
Podiatrists
Therapists
Inhalation therapists
Manual arts, music, recreational
therapists
Occupational therapists
Physical therapists
Speech and hearing clinicians
All other therapists
Veterinarians

Selected writers, artists, and
entertainers
Actors
Athletes
Commercial artists
Dancers
Designers
Film editors
Music directors
Musicians, instrumental
Painters, artistic
Photographers
Public relations specialists
Radio and TV announcers
Announcers
Broadcast news analysts
Reporters and correspondents
Singers
Sports instructors
Writers and editors
Writers, artists, entertainers,
n.e.c.

Health technologists and
technicians
Cytotechnologists
Dental hygienists
Dietetic technicians
EKG technicians
Health records technologists
Licensed practical nurses
Medical technicians
Medical lab technologists
Pharmacy helpers
Physical therapy technicians
Radiologic and nuclear medical
technicians

Other professional and technical
workers
Accountants and auditors
Architects
Archivists and curators
Assessors
Audio visual specialists,
education
B roker's floor reps and security
traders
Buyers, retail and wholesale trade

96

Appendix G. Occupations included in the industry-occupational model—Continued
Occupation title

Occupation title

Clerical workers— Continued

Other technical and professional
workers— Continued
Claim examiners, property/casualty
insurance
Claims takers, unemployment
benefits
Clergy
Cost estimators
Credit analysts, chief
Credit analysts
Directors, religious education and
activities
Employment interviewers
Foresters
Insurace investigators
Judges
Law clerks
Lawyers
Paralegal personnel
Librarians
Magistrates
Media buyers
Personnel and labor relations
specialists
Purchasing agents and buyers
Recreation workers, group
Safety inspectors
Social workers
Caseworkers
Community organization workers
Special agents, insurance
Tax examiners, collectors, and
revenue agents
Tax preparers
Title examiners and abstractors
Underwriters
Vocational and educational
counselors
Welfare investigators
All other professional workers

Admissions evaluators
Bank tellers
New accounts tellers
Tellers
Bookkeepers and accounting clerks
Accounting clerks
Bookkeepers, hand
Brokerage clerks
Car rental clerks
Cashiers
Checking clerks
Circulation clerks
Claims adjusters
Claims clerks
Claims examiner, insurance
Clerical supervisors
Collectors, bill and account
Court clerks
Credit authorizers
Credit clerks, banking and
insurance
Credit reporters
Customer service representatives,
printing, publishing
Desk clerks, bowling floor
Desk clerks, except bowling floor
Dispatchers, police, fire, and
ambulance
Dispatchers, vehicle, service, or
work
Eligibility workers, welfare
File clerks
General clerks, office
In-file operators
Insurance checkers
Insurance clerks, except medical
Library assistants
Loan closers
Mail carriers, postal service
Mail clerks
Marking clerks, trade
Messengers
Meter readers, utilities
Mortgage closing clerks
Office machine operators
Bookkeeping and billing
operators
Bookkeeping, billing machine
operators
Proof machine operators
Transit clerks
Computer, peripheral equipment
operators
Computer operators
Peripheral EDP equipment
operators
Duplicating machine operators
Keypunch operators
Tabulating machine operators
All other office machine operators
Order clerks
Payroll and timekeeping clerks
Personnel clerks
Policy change clerks
Postal clerks
Procurement clerks

Managers, officials, and proprietors
Auto parts department managers
Auto service department managers
Construction inspectors, public
administration
Inspectors, except construction,
public administration
Postmasters and mail
superintendents
Railroad conductors
Restaurant, cafe, and bar managers
Sales managers, retail trade
Store managers
Wholesalers
All other managers
Sales workers
Broker and market operators,
commodities
Contribution solicitors
Crafting and moving estimators
Real estate appraisers
Real estate brokers
Sales agents and representatives,
real estate
Sales agents and representatives,
insurance

Production clerks
Proofreaders
Rate clerks, freight
Raters
Real estate clerks
Receptionists
Reservation agents
Safe deposit clerks
Secretaries, stenographers, and
typists
Secretaries

Sales agents and representatives,
security
Sales clerks
Travel agents and accommodations
appraisers
Vendors
All other sales workers
Clerical workers
Adjustment clerks




97

Appendix G. Occupations included in the industry-occupational mode!—Continued




Occupation title

Occupation title

Machanics, repairs, and installers— Continued
Electrical instrument and tool
repairers
Electric motor repairers
Electric powerline installers and
repairers
Cable splicers
Line installers and repairers
Trouble shooters, powerline
Engineering equipment mechanics
Farm equipment mechanics
Gas and electric appliance
repairers
Gas and electric meter installers
Household appliance installers
Hydroelectric machine mechanics
Instrument repairers
Knitting machine fixers
Laundry machine mechanics
Locksmiths
Loom fixers
Maintenance mechanics
Maintenance repairers, general
utility
Marine mechanics and repairers
Millwrights
Mine machinery mechanics
Mobile home repairers
Musical instrument repairers
Office machine and cash register
servicers
Pinsetter mechanics, automatic
Radio and television repairers
Railroad car repairers
Railroad signal and switch
maintainers
Section repairers and setters
Sewing machine mechanics
Shoe repairers
Telephone installers and repairers
Cable repairers
Cable installers
Central office repairers
Frame wirers
Installers, repairers, and
section maintainers
Station installers
Trouble locators, test desk
All other telephone installers
and repairers
Water meter installers
All other mechanics, repairers, and
installers

Clerical workers— Continued
Stenographers
Typists
Service clerks
Service representatives
Shipping and receiving clerks
Shipping packers
Statement clerks
Statistical clerks
Stock clerks, stockroom and
warehouse
Survey workers
Switchboard operators/receptionists
Teacher” s aides, except monitors
Telephone ad takers, newspapers
Telegraph operators
Telephone operators
Switchboard operators
Central office operators
Directory assistance operators
All other telephone operators
Ticket agents
Title searchers
Town clerks
Traffic agents
Traffic clerks
Transportation agents
Travel counselors, auto club
Weighers
Worksheet clerks
Yard clerks
All other clerical workers
Crafts and related workers
Construction crafts
workers
Air-hammer operators
Asbestos and insulation workers
Brickmasons
Carpenters
Carpet cutters and layers
Ceiling tile installers and floor
layers
Concrete and terrazzo finishers
Dry wall installers and lathers
Dry wall applicators
'Lathers
Tapers
Electricians
Fitters, pipelaying
Glaziers
Highway maintenance workers
Painters, construction and
maintenance
Paperhangers
Plasterers
Plumbers and pipefitters
Refractory materials repairers
Roofers
Shipwrights
Stonemasons
Structural steel workers
Tile setters
Mechanics, repairers, and installers

Metalworking crafts workers, except
mechanics
Blacksmiths
Boilermakers
Coremakers, hand, bench, and floor
Forging press operators
Header operators
Heat treaters, annealers, and
temperers
Layout markers, metal
Machine tool setters, metalworking
Machinists
Molders, metal
Molders, bench and floor
Molders, machine
All other molders, metal
Patternmakers, metal
Punch press setters, metal
Rolling mill operators and helpers
Shear and slitter setters
Sheet metal workers and tinsmiths
T ool-and-die-makers
All other metalworking crafts workers

Air-conditioning, heating, and
refrigeration mechanics
Aircraft mechanics
Auto body repairers
Auto seat cover and top installers
Automotive mechanics
Auto repair service estimators
Bicycle repairers
Coin machine servicers and
repairers
Data processing machine mechanics
Diesel mechanics

98

Appendix G. Occupations included in the industry-occupational model—Continued
Occupation title

Occupation title
Metalworking crafts workers, except
mechanics— Continued
Printing trades crafts workers
Bookbinders, hand and machine
Bindery machine setters
Compositors and typesetters
Electrotypers and stereotypers
Etchers and engravers
Photoengravers and lithographers
Camera operators, printing
Photoengravers
Strippers, printing
Press and plate printers
Letter press operators
Offset lithographic press
operators
Platemakers
Press operators and plate
printers
All other press and plate
printers

Operatives
Assemblers
Aircraft structure and surfaces
assemblers
Clock and watch assemblers
Electrical and electronic
assemblers
Electro-mechanical equipment
assemblers
Instrument makers and assemblers
Machine assemblers
All other assemblers
Bindery operatives
Bindery workers, assembly
Bindery workers, stitching
All other bindery operatives
Laundry, drycleaning, and pressing
machine operatives
Drycleaners, hand and machine
Folders, laundry
Laundry operators, small
establishment
Markers, classifiers, and
assemblers
Pressers, hand
Pressers, machine
Pressers, machine laundry
Rug cleaners, hand and machine
Shapers and pressers
Spotters, drycleaning and washable
materials
Washers, machine and starchers
All other laundry and drycleaning
operatives

Other crafts and related workers
Auxiliary equipment operators
Bakers
Blue-collar worker supervisors
Cabinetmakers
Control room operators, steam
Crane, derrick, and hoist operators
Dental lab technicians
Food shapers, hand
Furniture finishers
Furniture upholsterers
Glass installers
Heavy equipment operators
Inspectors
Jewelers and silversmiths
Lens grinders
Locomotive engineers
Locomotive engineer helpers
Log inspectors, graders, and
sclaers
Logging tractor operators
Lumber graders
Machine setters, paper goods
Machine setters, plastic materials
Machine setters, woodworking
Merchandise displayers and window
trimmers
Millers
Motion picture projectionists
Opticians
Oil pumpers
Patternmakers, wood
Patternmakers, n.e.c.
Power station operators
Pumpers, head
Pumping station operators,
waterworks
Sewage plant operators
Shipfitters
Ship engineers

Meat cutters and butchers
Boners, meat
Boners, poultry
Butchers, all-round
Carcass splitters
Fish cleaners, hand and butchers,
fish
Metalworking operatives
Dip platers, nonelectrolytic
Drill press and boring machine
operators
Electroplators
Furnace chargers
Furnace operators, cupola tenders
Grinding and abrading machine
operators, metal
Heaters, metal
Lathe machine operators, metal
Machine-tool operators, combination
Machine-tool operators, numerical
control
Machine-tool operators, toolroom
Milling and planing machine
operators
Metalworking operatives
Pourers, metal
Power brake and bending machine
operators, metal
Punch press operators, metal
Welders and flamecutters
All other metalworking operatives

Other crafts and related workers
Stationary engineers
Stonecutters and stone carvers
Tailors
T esters
Upholsterers
Upholstery cutters
Upholstery workers, n.e.c.
Veneer graders
Watchmakers
Water treatment plant operators
All other crafts and related
workers




Mine operatives, n.e.c.
Continuous mining machine operators
Derrick operators, petroleum and
gas
Gagers
Loading machine operators
Mill and grinder operators,
minerals

99




Appendix G. Occupations included in the industry-occupational model—Continued
Occupation title

Occupation title
Mine operatives, n.e.c.— Continued
Roof bolters
Roustabouts
Service unit operators, oil well
Shuttle car operators
Well pullers
All other mine operatives, n.e.c.

Textile operatives
Parking attendants
Railroad brake operators
Rental car delivery workers
Sailors and deckhands
Streetcar operators
Taxi drivers
Truckdrivers
Transport equipment operatives,

Packing and inspecting operatives
Baggers
f
Bundlers
Cloth graders
Graders, food and skins
Production packagers
Selectors, glassware
All other packing and inspecting
operatives

All other operatives
Batch plant operators
Blasters
Boring machine operators, wood
Coil finishers
Cutters, machine
Cutters, portable machine
Cutter-finisher operators, rubber
goods
Cutting maching operators, food
Die cutters and' clicking machine
operators
Dressmakers, except factory
Drillers, hand and machine
Dyers
Exterminators
Filers, grinders, buffers, and
chippers
Floor sanding machine operators
Fuel pump attendants and
lubricators
Furnace operators and tenders,
except metal
Kiln operators, minerals
Stationary boiler firers
All other furnace operators and
tenders, except metal
Furniture assemblers and installers
Lathe operators, except metal
Miscellaneous machine operatives,
meat and dairy
Miscellaneous machine operatives,
all other food
Miscellaneous machine operatives,
tobacco
Miscellaneous machine operatives,
iumber and furniture
Miscellaneous machine operatives,
paper
Miscellaneous machine operatives,
chemicals
Miscellaneous machine operatives,
petroleum and coal
Miscellaneous machine operatives,
rubber and plastics
Miscellaneous machine operatives,
leather
Miscellaneous machine operatives,
stone, clay, glass

Painters, manufactured articles
Painters, automotive
Decorators, hand
Rubbers
Painters, production
Sawyers
Cut-off-saw operators, lumber
Edgers, automatic and pony
Head sawyers
Ripsaw operators
Sawyers, metal
Trim-saw operators
Ail other sawyers
Sewers and stitchers
Garment repairers
Menders
Sewing machine operators,
equipment, garment
Sewing machine operators,
equipment, garment
Sewing machine operators,
equipment, nongarment
Sewing machine operators,
equipment,nongarment

regular
special
regular
special

Textile operatives
Battery loaders
Beam warper tenders and beamers
Boarding machine operators, hosiery
Card tenders and comber tenders
Cloth feeders and back tenders
Cloth finishing range operators and
tenders
Creelers, yarn
Doffers
Drawing frame and gill box tenders
Folders, hand
Folding machine operators
Knitting machine operators
Seamless hosiery knitters
Slubber tenders
Spinners, frame
Spooler operators, automatic
Texturizers and crimp setters
Turners
Twister tenders
Weavers
Winder operators, automatic
Yarn winders
All other textile operatives

Miscellaneous machine operatives,
primary metals
Miscellaneous machine operatives,
manufacturing, n.e.c.
Miscellaneous machine operatives,
nonmanufacturing
Miscellaneous operatives, n.e.c.,
durable goods
Miscellaneous operatives, n.e.c.,
nondurable goods
Mixing operatives
Nailing machine operators
Oilers
Photographic process workers
Power screwdriver operators
Punch and stamping press operators,
except metal
Riveters
Rotary drill operators
Rotary drill operator helpers

Transport equipment operatives
Ambulance drivers and ambulance
attendants
Bus drivers
Chauffeurs
Delivery and route workers
Industrial truck operators
Log handling equipment operators

100

Appendix G. Occupations included in the industry-occupational model—Continued
Occupation title

Occupation title
All other operatives— Continued
Sandblasters and shotblasters
Sanders, wood
Shaper and rubber operators
Shear and slitter operators, metal
Shoemaking machine operators
Surveyor helpers
Termite treaters and helpers
Tire changers and repairers
Winding operatives, n.e.c.
Coil winders
Paper reel and rewinder operators
Winders, paper machine
All other winding operatives,
n.e.c.
Wirers, electronic
Wood machinists
Operatives, n.e.c.
Service workers
Food service workers
Bakers, bread and pastry
Bartenders
Butchers and meat cutters
Cooks, except private households
Cooks, institutional
Cooks, restaurant
Cooks, short order and specialty
fast foods
Food service workers, fast food
restaurants
Hosts/hostesses, restaurant,
lounge, coffee shop
Kitchen helpers
Pantry, sandwich, and coffee makers
Waiters and waitresses
Waiters assistants
All other food service workers
Janitors and sextons
Selected health service workers
Dental assistants
Health aides, except nursing
Medical assistants
Nurses aides and orderlies
Psychiatric aides
Selected personal service workers
Barbers
Baggage handlers and porters
Bellhops, bag porters, and
doorkeepers
Checkroom and locker room
attendants
Child care attendants
Child care workers
Cosmetologists and women” s
hairstylists
Elevator operators
Flight attendants
Funeral attendants
Game and ride operators and
concession workers
Guides, sightseeing and
establishment
Housekeepers, hotel and motel
Manicurists
Masseurs and masseuses
Pin chasers
Recreation facility attendants
Reducing instructors
Scalp treatment operators
School monitors
Shampooers
Ushers, lobby attendants, and
ticket takers
Welfare service aides
Personal service workers, n.e.c.




Selected personal service workers— Continued
Protective service workers
Bailiffs
Checkers, fitting room
Correction officials and jailers
Crossing or bridge tenders
Crossing guards, school
Firefighters
Fire inspectors
Fire officers
Fish and game wardens
Guards and doorkeepers
Lifeguards
Parking enforcement officers
Police detective
Police officers
Police patrolmen/women
Sheriffs
Store detectives
All other protective service
workers
Private household workers
Child care workers, private
household
Cooks, private household
Housekeepers, private household
Laundresses, private household.
Maids and servants, private
household
Supervisors, nonworking, service
All other service workers
Laborers, except farm
Animal caretakers
Construction laborers, except
carpenter helpers
Asphalt rakers
Fence erectors
Pipelayers
Reinforcing-iron workers
All other construction laborers
Cannery workers
Chain offbearers, lumber
Cleaners, vehicle
Conveyor operators and tenders
Forest conservation workers
Furnace operators and heater
helpers
Garbage collectors
Gardeners and groundskeepers,
except farm
Helper, trades
Line service attendants
Loaders, cars and trucks
Loaders, tank cars and trucks
Off-bearers
Riggers
Septic tank servicers
Setters and drawers
Shakeout workers, foundry
Stock handlers
Order fillers
Stock clerk, sales floor
Timber cutting and logging workers
Choker setters, lumber
Fallers and buckers
All other timber cutting and
logging workers
Work distributors
All other laborers, except farm
Farmers and farm workers
Farmers and farm managers
Farmers (owners and tenants)
Farm managers
Farm supervisors and laborers
Farm supervisors
Farm laborers

101




%p©ncfe H. Industries included In the

3ndustry-0eeupatI@naS Model

102

Appendix H industries included in the Industry-Occupational Model
„
Industry title

Industry title
Durable goods manufacturing, total
— Continued
Partitions and fixtures
Miscellaneous furniture and
fixtures
Stone, clay, and glass products,
total
Flat glass
Glass and glassware, pressed or
blown
Products of purchased glass
Cement, hydraulic
Structural clay products
Pottery and related products
Concrete, gypsum, and plaster
products
Cut stone and stone products
Miscellaneous nonmetallic mineral
products
Primary metal industries, total
Blast furnaces and basic steel
products
Iron and steel foundries
Primary nonferrous metals
Secondary nonferrous metals
Nonferrous rolling and drawing
Nonferrous foundries
Miscellaneous primary metal
products
Fabricated metal products, total
Metal cans
Cutlery, handtools, and hardware
Plumbing and heating, except
electrical
Fabricated structural metal
products
Screw machine products, bolts,
nuts
Metal stampings
Metal services, n.e.c.
Ordnance and accessories, n.e.c.
Miscellaneous fabricated metal
products
Machinery, except electrical, total
Engines and turbines
Farm and garden machinery
Construction and related machinery
Metalworking machinery
Special industry machinery
General industrial machinery
Office, computing machinery
Refrigeration and service
machinery
Miscellaneous machinery, except
electrical
Electric machinery, equipment, and
supplies, total
Electric distributing equipment
Electrical industrial apparatus
Household appliances
Electric lighting and wiring
equipment
Radio and TV receiving equipment
Communication equipment
Electronic components and
accessories
Miscellaneous electrical equipment
and supplies
Transportation equipment, total
Motor vehicles and equipment
Aircraft and parts
Ship and boat building and
repairing
Railroad equipment
Motorcycles, bicycles, and parts
Guided missiles, space vehicles
Miscellaneous transportation
equipment

Total, all industries
Agriculture, forestry, and fishing,
total
Agricultural production, crops
Agricultural production, livestock
Agricultural services
Forestry
Fishing, hunting, and trapping
Mining, total
Metal mining, total
Iron ores
Copper ores
Lead and zinc ores
Gold and silver ores
Bauxite and other aluminum ores
Ferroalloy ores, except vanadium
Metal mining services
Miscellaneous metal ores
Anthracite mining, total
Bituminous coal and lignite mining,
total
Crude petroleum and natural gas,
total
Crude petroleum and natural gas
Natural gas liquids
Oil and gas field services
Nonmetallic mining and quarrying,
total
Dimension stone
Crushed and broken stone
Sand and gravel
Clay and related minerals
Chemical and fertilizer minerals
Nonmetallic minerals services
Miscellaneous nonmetallic minerals
Construction, total
General building contractors, total
Residential building construction
Operative building
Nonresidential building
construction
General contractors, except
building, total
Highway and street construction
Heavy construction, except highway
Special trade contractors, total
Plumbing, heating, air-conditioning
Painting, paper hanging, and
decorating
Electrical work
Masonry, stonework, and plaster
Carpentering and flooring
Roofing and sheet metal work
Concrete work
Water well drilling
Miscellaneous special trade
contractors
Manufacturing, total
Durable goods manufacturing, total
Lumber and wood products, total
Logging camps and logging
contractors
Sawmills and planing mills
Millwork, plywood, and structural
members
Wooden containers
Wood building and mobile homes
Miscellaneous wood products
Furniture and fixtures, total
Household furniture
Office furniture
Public building and related
furniture




103




Appendix H. Industries included in the Industry-Occupational Model—Continued
Industry title

Industry title
Durable goods manufacturing, total
—Continued
Professional, scientific
instruments, total
Engineering and scientific
instruments
Mechanical measuring and
controlling
Optical instruments and lenses
Medical instruments and supplies
Ophthalmic goods
Photographic equipment and
supplies
Watches, clocks, and watchcases
Miscellaneous manufacturing
industries, total
Jewelry, silverware, an plated
ware
Musical instruments
Toys and sporting goods
Pens, pencils, and office and art
supplies
Costume jewelry and notions
Miscellaneous manufacturing
Nondurable goods manufacturing,
total
Food and kindred products, total
Meat products
Dairy products
Preserved fruits and vegetables
Grain mill products
Bakery products
Sugar and confectionery products
Fats and oils
Beverages
Miscellaneous foods and kindred
products
Tobacco manufacturing, total
Cigarettes
Cigars
Tobacco (chewing and smoking)
Tobacco steaming and redrying
Textile mill products, total
Weaving mills, cotton
Weaving mills, synthetic fibers
Weaving and finishing mills, wool
Narrow fabrics mills
Knitting mills
Textile finishing, except wool
Floor covering mills
Yarn and thread mills
Miscellaneous textile goods
Apparel and textile products, total
Men’s and boys’ suits and coats
Men’s and boys’ furnishings
Women’s and misses’ outerwear
W omen’s and children’s
undergarments
Hats, caps, and millinery
Children” s outerwear
Fur goods
Miscellaneous apparel and
accessories
Miscellaneous fabricated textile
products
Paper and allied products, total
Pulp mills
Paper mills, except building paper
Paperboard mills
Miscellaneous converted paper .
products
Paperboard containers and boxes
Building paper and board mills
Printing and publishing industries,
total
Newspapers
Periodicals

Nondurable goods manufacturing,
total— Continued
Books
Miscellaneous publishing
Commercial printing
Manifold business forms
Greeting card publishing
Blankbooks and bookbinding
Printing trade services
Chemicals and allied products,
total
Industrial inogranic chemicals
Plastics materials and synthetics
Drugs
Soaps, cleaners, and toilet goods
Paints and allied products
Industrial organic chemicals
Agricultural chemicals
Petroleum and coal products, total
Petroleum refining
Paving and roofing materials
Miscellaneous petroleum and coal
products
Rubber and miscellaneous plastics
products, total
Tires and inner tubes
Rubber and plastics footwear
Reclaimed rubber
Rubber and plastics hose and
belting
Fabricated rubber products, n.e.c.
Miscellaneous plastics products
Leather and leather products, total
Leather tanning and finishing
Boot and shoe cut stock and
findings
Footwear, except rubber
Leather gloves and mittens
Luggage
Handbags and personal leather
goods
Leather goods, n.e.c. '

Transportation, communications, and
utilities
Transportation, total
Railroad transportation, total
Local and interurban transit, total
Local and suburban transportation
Taxicabs
Intercity highway transportation
Transportation charter service
School buses
Bus terminal and service
facilities
Trucking and warehousing, total
Trucking, local and long distance
Public warehousing
Trucking terminal facilities
U.S. postal service
Water transportation, total
Deep sea foreign transportation
Deep sea domestic transportation
Great Lakes transportation
Transportation on rivers and
canals
Local water transportation
Water transportation services
Air transportation, total
Certificated air transportation
Noncertificated air transportation
Air transportation services
Pipelines, except natural gas,
total
Transportation services, total
Freight forwarding
Arrangement of transportation

104

Appendix H. Industries included in the Industry-Occupational Model—Continued
Industry title

Industry title

Retail trade, total— Continued
Automobiles and recreational
vehicles, total
Motor vehicle dealers (new and
used)
Motor vehicle dealers (used only)
Auto and home supply stores
Gasoline service stations
Boat dealers
Recreational and utility trailer
dealers
Motorcycle dealers
Automotive dealers, n.e.c.
Apparel and accessories stores,
total
Men’s and boys’ clothing and
furnishings
W omen’s and misses’ ready-to-wear stores
W omen’s and misses’ accessory and specialty
stores
Children’s and infants' wear stores

Transportation, communications, and
utilities— Continued
Rental of railroad cars
Miscellaneous transportation
services
Communications and utilities, total
Communications, total
Telephone communication
Telegraph communication
Radio and television broadcasting
Communication services, n.e.c.
Utilities and sanitary services,
total
Electric companies and systems
Gas companies and systems
Combination companies and systems
Water supply
Sanitary services
Steam supply
Irrigation systems
Wholesale and retail trade, total
Wholesale trade, durable goods,
total
Motor vehicle and auto parts and
supplies
Furniture and home furnishings
Lumber and other construction
materials
Sporting, toy, photographic, and
hobby goods
Metals and minerals, except
petroleum
Electrical goods
Hardware, plumbing, and heating
supplies
Machinery, equipment, and supplies
Miscellaneous durable goods
Wholesale trade, nondurable goods,
total
Paper and paper products
Drugs, proprietaries, and sundries
Apparel, piece goods, and notions
Groceries and related products
Farm-product raw materials
Chemical and allied products
Petroleum and petroleum products
Beer, wine, and distilled alcholic
beverages
Miscellaneous nondurable goods
Retail trade, total
Building materials, garden supplies,
mobile homes, total
Lumber and other building
materials dealers
Paint, glass, and wallpaper stores
Hardware stores
Retail nurseries, lawn and garden
supplies
Mobile home dealers
Retail trade, general merchandise,
total
Department stores
Variety stores
Miscellaneous general merchandise
stores
Food stores, total
Grocery stores
Meat and fish (seafood) markets
Fruit stores and vegetable markets
Candy, nut, and confectionery
stores
Dairy products stores
Retail bakeries
Miscellaneous food stores




Family clothing stores
Shoe stores
Furriers and fur shops
Miscellaneous apparel and
accessories
Furniture and home furnishings
stores, total
Furniture and home furnishing,
except appliances
Household appliance stores
Radio, television, and music
stores
Eating and drinking places, total
Miscellaneous retail stores, total
Drug stores and proprietary stores
Liquor stores
Used merchandise stores
Miscellaneous shopping goods
stores
Nonstore retailers
Fuel and ice dealers
Retail stores, n.e.c.
Finance, insurance, and real estate,
total
Banking, total
Federal Reserve Banks
Commercial and stock savings banks
Mutual savings banks
Trust companies, nondeposit
Functions closely related to
banking
Credit agencies other than banks,
total
Rediscount and financing
institutions
Savings and loan associations
Agricultural credit institutions
Personal credit
Business credit institutions
Mortgage bankers and brokers
Security and commodity brokers,
dealers, total
Security brokers and dealers
Commodity contracts brokers and
dealers
Security and commodity exchanges
Security and commodity services
Insurance carriers, total
Life insurance
Medical service and health
insurance
Fire, marine, and casualty
insurance
Surety insurance

105

Appendix H. Industries included in the Industry-Occupational Eltodel—Continusd
Industry title

Finance, insurance, and real estate,
total— Continued
Title insurance
Pension, health, and welfare funds
.Insurance carriers, n.e.c.
Insurance agents, brokers, and
services, total
Real estate, total
Real estate operators and lessors
Real estate agents and managers
Title abstract offices
Subdividers and developers
Combined real estate, insurance,
loan, and law offices
Holding and other investment
offices, total
Holding offices
Investment offices
Trusts
Miscellaneous investing
Services,total
Hotels and other lodging places,
total
Hotels, motels, and tourist courts
Rooming and boarding houses
Camps and trailering parks
Organization hotels and lodging
houses
Personal services, total
Laundry, cleaning, and garment
services
Photographic studios, portrait
Beauty shops
Barber shops
Shoe repair, shoe shine, and hat
cleaning shops
Funeral service and crematories
Miscellaneous personal services
Miscellaneous business services,
total
Advertising
Consumer credit reporting and
collection
Mailing, reproduction, commercial
art, and stenography
Services to dwelling and other
buildings
News syndicates
Personal supply services
Computer and data processing
services
Miscellaneous business services
Automobile repair, services, and
garages, total
Automobile rentals, leasing,
without drivers
Automobile parking
Automobile repair shops
Automobile services, except repair
Miscellaneous repair services,
total
Electrical repair shops
Watch, clock, and jewelry repair
Reupholstery and furniture repair
Miscellaneous repair shops and
related services
Motion pictures, total




Industry title

Services,total— Continued
Motion picture production and
services
Motion picture distribution and
services
Motion picture theaters
Amusement and recreation, except
motion pictures, total
Dance halls, studios, and schools
Theatrical producers, bands, and
entertainers
Bowling alleys and billard and
pool establishments
Commercial sports
Miscellaneous amusement and
recreation services
Health services, total
' Offices of physicians
Offices of dentists
Offices of osteopathic physicians
Offices of other health
practitioners
Nursing and personal care
facilities
Hospitals
Medical and dental laboratories
Outpatient care facilities
Health and allied services, n.e.c.
Legal services, total
Educational services, total
Social services, total
Individual and family social
services
Job training and vocational
rehabilitation services
Child day care services
Residential care
Social services, n.e.c.
Museums, art gallaries, and zoos,
total
Museums and art gallaries
Arboreta, botanical, zoological
gardens
Membership organizations, total
Business associations
Professional membership
organizations
Labor unions and fraternal
associations
Political organizations
Religious organizations
Membership organizations, n.e.c.
Private households, total
Miscellaneous services, total
Engineering, architectural, and
surveying services
Noncommercial educational and
research organizations
Accounting, auditing, and
bookkeeping services
Services, n.e.c.
Government, total
Federal Government
State government, except education
and hospitals
Local government, except education
and hospitals

106

Appendix 1 Data Sources
=

Source documen s, for the most part, are continuing
publication, and all issues have been examined.

Labor fore© projections
Current Population Reports, Bureau of the Census,
U.S. Department of Commerce.
Employment and Earnings, Bureau of Labor Statis­
tics, U.S. Department of Labor.

Siasroeconosnsc projections
Aggregate Labor Force Projections, Bureau of Labor
Statistics.
Business Conditions Digest, Bureau of Economic Anal­
ysis, U.S. Department of Commerce.
Current Population Reports, Bureau of the Census.
Employment and Earnings, Bureau of Labor Statistics.
Farm Income Statistics, U.S. Department of
Agriculture.
National Income and Product Accounts, Bureau of Ec­
onomic Analysis.
Social Security Bulletin, Annual Statistical Supplement,
Social Security Administration, U.S. Department of
Health and Human Resources.
Statistical Abstract of the United States, Bureau of the
Census.
Statistics of Income Report, Internal Revenue Code, In­
ternal Revenue Service, U.S. Department of the
Treasury.
Survey of Current Business, Bureau of Economic
Analysis.

Final demand projections
Capital Stocks Data Base, Bureau of Labor Statistics.
Census of Governments, Bureau of the Census.
Census of Manufactures, 1967 and 1972, Bureau of the
Census.
Construction Review, Industry and Trade Administra­
tion, U.S. Department of Commerce.
Current Population Reports, Bureau of the Census.
Input-Output Structure of the U.S. Economy, 1958;
1963; 1967; and 1972, Bureau of Economic Analysis.
Interindustry Transactions in New Structures and
Equipment, 1963 and 1967, Bureau of Economic
Analysis.
Military Prime Contract Awards by Federal Supply
Classification, OASD-Comptroller, U.S. Department of
Defense.



107

Monthly Status o f Funds, OASD-Comptroller, U.S.
Department of Defence.
National Income and Product Accounts, Bureau of Ec­
onomic Analysis.
Public Employment, Bureau of the Census. Shipments
o f Defense Oriented Industries, MA-175, Bureau of the
Census.
Survey of Current Business, Bureau of Economic
Analysis.
U.S. Budget Appendix, 1963-78, Office of Management
and Budget, Executive Office of the President.
U.S. Exports by 8-Digit SIC FT610, Bureau of the
Census.
U.S. Exports, Commodity Schedule FT410, Bureau of
the Census.
U.S. Exports by 2-, 3-, and 4-Digit SIC EA675, un/
published data, Bureau of the Census.
U.S. Imports TSUSA, Commodity by Country, FT246,
Bureau of the Census.
U.S. Imports for Consumption and General Imports,
IA275, Bureau of the Census.

Intermediate demand projections
Annual Survey o f Manufactures, Bureau of the Census.
Census of Business, Bureau of the Census.
Census o f Manufactures, 1963 and 1967, Bureau of the
Census.
Current Industrial Reports, Bureau of the Census.
Input-Output Structure o f the U.S. Economy, 1958;
1963; and 1967,
Bureau of Economic Analysis.
Minerals Yearbook, Bureau of Mines, U.S. Depart­
ment of Interior.
Statistical Abstract of the United States, Bureau of the
Census.

Industry output and employment
Agricultural Statistics, U.S.
Department of
Agriculture.
Annual Survey of Manufactures, Bureau of the Census.
Best's Aggregates and Averages, A. M. Best Co.
Business Income Tax Receipts, Internal Revenue Serv­
ice. Census of Manufactures, Bureau of the Census.
Compendium of National Health Expenditures, U.S.
Department of Health and Human Resources.
Construction Reports, Bureau of the Census.
County Business Patterns, Bureau of the Census.

Statistics o f Privately-Owned Electric Utilities, U.S.
Federal Power Commission.
Statistics o f Publicly-Owned Electric Uilities, U.S. Fed­
eral Power Commission.
The Franchised New Car and Truck Dealer Story, Na­
tional Automobile Dealers Association.
Transport Statistics in the U.S., U.S. Interstate Com­
merce Commission.

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.
National Income and Product Accounts, Bureau of Ec­
onomic Analysis. Office of Productivity and Technology
Data Base, Bureau of Labor Statistics.
Statistical Abstract of the United States, Bureau of the
Census.
Statistics of Communications, *
Common Carriers, U.S.
Federal Communications Commission.




Occupational employment projections

Current Population Survey, Bureau of the Census.
Employment and Earnings, Bureau of Labor Statistics.
Industry Employment Projections, Bureau of Labor
Statistics.
Occupational Employment Statistics Survey, Bureau
of Labor Statistics.

■& U.S. GOVERNMENT PRINTING OFFICE : 1982

108

0 -5 2 2 -0 3 2

(6 3 4 2 )

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