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SIXTH DISTRICT MANUFACTURING INDEX
Technical Note and Statistical Supplement

FEDERAL RESERVE BANK OF ATLANTA
JUNE 1970


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SIXTH DISTRICT MANUFACTURING PRODUCTION INDEX:
Technical Note and Statistical Supplement

Federal Reserve Bank of Atlanta

Prepared by

C. S. Pyun, Economist
Research Department
June 1970

ACKNOWLEDGMENTS

It would not have been possible to complete this project without

the work of a team of competent and cooperative individuals in the
Miss Cheryl Odom and Miss Sally E. Barr have performed the ex­

Bank.

cruciating task of collecting, sorting, and verifying a large volume

They also calculated countless

of the raw input data that were used.

numbers of individual index series—both those series computed while
the work was still in an experimental stage and those final series con

tained in this note.

They carried out these important tasks with

maximum efficiency and a great deal of patience.
Miss Martha Bethea and Mrs. Sara Anderson provided indispensable

assistance and technical advice on a large volume of raw data which
needed to be processed by computers.

Mr. Robert Sexton of the Data

Processing Department also offered advice and help in programming

work.

Mrs. Lane Chason spent many hours in verifying and correcting

the electric power series used in the index construction.

Mr. Milo

Peterson, formally a staff member of the Board of Governors, Federal

Reserve System, gave his time and expertise in unraveling many trouble
some issues associated with using electric power statistics.

While the project was in progress, Mrs. Sherley Wilson typed many

pages of scribbled notes and tables and drew charts of many individual
series.

She also typed several drafts, as well as the final version

of this note with her usual efficiency.


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TABLE OF CONTENTS

Part I

Section

I

- Introduction....................................................................................................... 1

Section

II

- Concept and Coverage.................................................................................... 3

Section III

- Estimating Equations and Procedures................................................8

Section

IV

- Characteristics of the Estimating Equations.......................... 12

Section

V

- Data Sources and Limitations.............................................................. 16

Section

VI

- Empirical Validity of District ProductionIndex................... 21

APPENDIX A

Table
Table
Table
Table
Table

- Productivity Extrapolators................................................................... 26
- Industry Index Derivation..................................................................... 27
- Value Added by Manufactures, 1963.................................................. 28
- Factor Weights, 1963................................................................................. 29
- Linear Regression of Annual Man-hourProductivity,
1957-65................................................................................................................. 30
Table 6. - Relative Performance of District Production Indexes
for Selected Industries...........................................................................31
1.
2.
3.
4.
5.

Part II

APPENDIX B

- District Production Indexes, Seasonally Adjusted.............. 32

APPENDIX C

- District Production Indexes, Seasonally Unadjusted......... 43

Bibliography....................................................................................................................................... 54


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DISTRICT MANUFACTURING PRODUCTION INDEX

Technical Note and Statistical Supplement

This note consists of two major parts.

Part I describes the concepts

and methodology employed in constructing the new production index that was
developed by the Research Department of the Federal Reserve Bank of Atlanta.

Also included in Part I is a discussion of the empirical validity of the

District production index.

Part II contains, in time series form, indexes

which are seasonally adjusted and unadjusted for individual industries and

three major industrial groupings (i.e., durables, nondurables, and total
manufacturing).

Section I - Introduction
Because of their unique participation in formulating national monetary

policies, individual District Reserve Banks have been vitally interested in
the development and compilation of various economic statistics germane to
the study of their regions.

The search for various comprehensive measure­

ments that can be used as a broad foundation for regional economic analysis,
such as one that reflects an up-to-date and reliable account of the current
level of industrial and business activity, has been a perennial endeavor of
District Reserve Banks.

Currently, only the Reserve Banks of Boston and

Dallas are releasing production indexes on a regular basis for either the

District or for a state in the District.—However, attempts have been made

V ’’Electric Power - An Indicator of Industrial Activity,” New England
Business Review, Federal Reserve Bank of Boston, February 1965, pp. 8-13;
C. Howard Davis, "Improvement of Texas Industrial Production Index," Business Review, Federal Reserve Bank of Dallas, September 1968, pp. 3-7.


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by several other Banks to develop similar series.-

At the Federal Reserve Bank of Atlanta, an interest in the development
of a District production index began in the early 1960’s when, as a part of
a system-wide effort, the Bank began to collect statistics on kilowatt
hours (KWH) of electricity sold to manufacturing by utilities.

The project

has been carried out under the general direction of Mr. Charles T. Taylor,
Senior Vice President and Director of Research.

Many of those on the Re­

search staff have participated in the project, including Messrs. Phil Web­
ster, Dale 0’Bannon, William Schleicher, and Richard Long.

The greatest

momentum for the project was provided by Mr. Long, my immediate predecessor,

during the period between 1966 and 1968.
Potential benefits that may be derived from the regional production

index are substantial.

First of all, the new District indexes will add

another dimension to regional economic analysis by providing a reasonably

reliable and up-to-date account of manufacturing activity at the regional

level.

Secondly, they will provide a statistical basis for analyzing and

comparing interindustry as well as interregional manufacturing activity
over a period of time, which will shed light on various forces that are
relevant to the study of the growth process and cyclical phenomena observed

2/
— See Business Indexes Proposed for the Fifth District (mimeograph), un­
dated, Federal Reserve Bank of Richmond; "Toward an Index of Ninth District
Industrial Production," Monthly Review, June 1966, Federal Reserve Bank of
Minneapolis, pp. 3-7; "Electric Power Consumption in Manufacturing," Business
Review, Federal Reserve Bank of Philadelphia, April 1961, pp. 24-26; "Electric
Power as a Regional Economic Indicator," Economic Review, Federal Reserve Bank
of Cleveland, September 1964, pp. 10-15; L. C. Anderson, "Value Added by Manu­
facture, Central Mississippi Valley Metro Areas, 1957-64," Review, Federal Re­
serve Bank of St. Louis, June 1964, pp. 5-10; "Electric Power Consumption - An
Output Indicator in Milwaukee," Business Conditions, Federal Reserve Bank of
Chicago, April 1962, pp. 5-11.


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in a dynamic aspect of the regional economy.

Thirdly, the indexes will

satisfy, at least partially, the needs of private businesses and govern­
mental agencies for regional production data in their decision making.

It

is vitally important that planners have knowledge concerning changes in the
productivity factors, as well as in the level of physical output of individ­

ual industries—including the ensuing changes in the relative structure

of the regional industries.

For instance, an increasing number of indi­

vidual companies study their own productivity estimate on a continuing basis

in order to facilitate cost control and diversification planning, as well as

for a variety of other reasons.

The new District index will enable business

to compare and analyze changes in their own productivity and level of output

at the local level to those observed in the same industry of the District
3/
or national level.—

Section II - Concept and Coverage

The District manufacturing production index is designed to measure
monthly changes in the level of physical output of District manufacturing.
The output, which is measured in constant dollars to remove the effects of

price changes over a period of time, is statistically estimated from two
major factor inputs, _i.e^. , man-hours employed and KWH of electric power
3/
—' For methods measuring the productivity of individual companies, see
John W. Kendrick and Daniel Creamer, Measuring Company Productivity, National
Industrial Conference Board, New York, 1965. Additional discussions on the
usefulness of the production index are found in Clayton Gehman and Cornelia
Metheral, Industrial Production Measurement in the United States: Concepts,
Uses, and Compilation Practices, Board of Governors of the Federal Reserve
System, Washington, February 1964.


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4/
consumed, for 18 out of 21 two-digit SIC industries.

The estimates for

individual industries are combined to yield indexes for two major industrial

groups (i.e., durables and nondurables) and total manufacturing.

The index

covers, in its entirety, all six states wholly or partially served by the

Federal Reserve Bank of Atlanta and is based on about 90 percent coverage

of the reported universe of man-hour and electricity consumption data ger­
mane to the six states’ industries.

No attempt was made to incorporate

actual output data into the index construction.

The new index, as its title

indicates, encompasses only the manufacturing sector and does not include
utility and mining industries of the District states.

While it is ideal to make a monthly measurement of production output

by tabulating the actual quantity of goods produced in an industry, it is
neither practical nor the most efficient method to accomplish the objective.

First, there is a question whether many manufacturing concerns keep actual

and reliable production data on a monthly basis.

Even if all of them did,

there still would be the formidable problem of collecting data directly
from individual companies every month, even by sampling methods.

Aggregating

individual product data in a meaningful way would be an equally formidable
problem because products are numerous and are not homogeneous in character.

The theoretical production function provided the conceptual cornerstone

4/

For the time being, nroduction indexes for three industries (SIC 19,
Ordnance and Accessories, SIC 38, Professional, Scientific, and Controlling
Instruments? and SIC 39, Misscellaneous Manufacturing Industries) were not
estimated primarily because of incompleteness in published man-hour and
value added data and because of their relative insignificance in the overall
manufacturing endeavor of the District.


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in the development of the District’s production index.—More specifically,

the new index has been developed on the assumption that the functional rela­
tionship between the rate of change in input factors and the rate of flow of

physical output per time period can be statistically defined.

Once the rela­

tionship is defined, the change in the level of output may be estimated by
the changes in quantity of the input factors.

The independent variables em­

ployed as the input factors of production are data on man-hours employed and
industrial use of electric power; both are generally available at state

levels for 2 digit SIC industries on a relatively current basis.

Industrial

output in constant dollars was approximated by deflating the value added
data with the price index of the base year period.

Since value added data

are not available on a current basis, current outputs were estimated by

extrapolating factor productivities along with the input variables.

The out­

put estimate was then carried forward monthly until the census data became
available, at which time output estimates made by the extrapolated factor
productivities were adjusted to the new bench marks.

Estimating procedures

and the primary data employed in the derivation of the index are further
elaborated in later sections of this note.

— The input and output relationship in an aggregate production function
encompassing the entire industry designated by the two digit SIC level is
admittedly complex and poses difficult problems in the theoretical as well
as empirical frame of reference. In this context, it must be emphasized that
the theoretical production function provided only the conceptual guidance for
the methodological frame of reference. For discussions on broad problems
associated with the aggregate production function, see Franklin M. Fisher,
’’The Existence of Aggregate Production Function,’’ Econometrica, Vol. 37, 1969,
pp. 553-577; and Robert M. Solow, ’’Some Recent Developments in the Theory of
Production,” in Murray Brown, Ed., The Theory and Empirical Analysis of Pro­
duction, National Bureau of Economic Research, New York, 1967, pp. 25-53. See
also, Franklin M. Fisher, "Embodied Technology and the Existence of Labour and
Output Aggregated," Review of Economic Studies, Vol. 35, 1968, pp. 391-412.


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The use of the productivity extrapolators for this purpose, which will
be discussed further in Section V, may not be empirically valid under cer­
tain circumstances, and thus, the extrapolators may distort estimates of

current outputs.

6/

However, experience seems to indicate that the produc­

tivity extrapolator generally yielded fairly reliable estimates in the
past

7/
The use of the two factors of production as primary input variables

is based on conceptual as well as practical considerations.

Typically, the

effects that changes in the quantity of the input factors have upon volume
of output over a period of time are manifested through either ’’scale effect”

or "technological effect," or through both.

In other words, changes in

physical output are affected not only by changes in the quantity of the in­
put factors but also by changes in the technological parameters of the pro­
duction function, which in turn are affected by changes in the factor pro­
ductivities and the marginal rates of technical substitution of the two

factors.

While it is almost a formidable task to isolate empirically the

magnitude of output variations stemming from these two "effects" individually

or jointly, it was felt that a combination of the two input variables in the

~ For instance, Hultgren and Kuh showed that changes in labor produc­
tivity tend to move in the same direction as changes in firms’ output during
the business cycle period. See for instance, Thor Hultgren, Changes in Labor
Cost During Cycles in Production and Business, National Bureau of Economic
Research, New York, 1960, Chapter 2; and Edwin Kuh, Profits, Profits Markups,
and Productivity, Joint Economic Committee, 86th Congress, Government Printing
Office, 1960, pp. 61-111* Board of Governors of the Federal Reserve System,
Industrial Production, 1959 Revision, Washington, 1960, pp. 22-24.
—^Janies W. Knowles, "An Appraisal of Productivity Projections," Journal
of American Statistical Association, June 1959, as quoted in John W. Kendrick,
Productivity Trends in the United States, Princeton University Press, Prince­
ton, 1961, page 16.


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same equation would reflect interaction effects that could not be shown

through the use of either man-hour or KWH data alone.

For instance, a more

intensive use of capital is likely to be accompanied by increased use of

electricity and a decrease in demand for labor.

Over a period of time, how­

ever, the ratio between inputs of labor and KWH changes as a result of

changes in the parameters of the production function, such as, changes in
technology and work efficiency.

Our experience indicates that the direction

of change in the input ratio, as well as change in relative use of electric

power to labor (as measured by KWH used per man-hour over a period of time),
would not always show stable and predictable relationships.

Furthermore, a

number of recent studies indicated that the elasticity of factor substitu8/
tion for most U. S. manufacturing industries is close to unity.
For this
reason, in the construction of the new District index, it was assumed that the
two input factors used had unitary elasticity of substitution.

Except for the actual physical output data, which are not incorporated

in the new District index, the District production index shares a basic
affinity with the U. S. production index in its conceptual and methodological

orientation.

Like the U. S. production index, the new District index is

— See for instance, Paul Zarembka, "On the Empirical Relevance of the
CES Production Function," Review of Economics and Statistics, Vol. LII, Feb­
ruary 1970, pp. 47-53; C. A. Knox Lovell, "Biased Technical Change and Factor
Shares in the U. S. Manufacturing," Quarterly Review of Economics and Busi­
ness , Vol. 9, Autumn 1969, pp. 17-33; and Phoebus J. Dhrymes and Paul Zarembka
"Elasticities of Substitution for Two-Digit Manufacturing Industries: A
Correction," Review of Economics and Statistics, Vol. LII, February 1970, pp.
115-117. For a discussion on recent developments in the CES production func­
tion see, Marc Nerlove, "Recent Empirical Studies of the CES and Related Pro­
duction Functions" in Brown, ibid., pp. 56-112, and articles presented in a
symposium on CES production functions in Review of Economics and Statistics,
Vol. 50, 1968, pp. 443-479.


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-8-

designed on the basis of what is known as the Census ’’value added” concept.

Value added by manufactures, as it is defined by the U. S. Bureau of Census,
"is derived by subtracting the total cost of materials from the value of
shipments and other receipts and adjusting the resulting amount by the net

change in finished products and work-in-process inventories between the be-

9/
ginning and end of the year.’’-

The value added by manufactures is generally

considered to be the best empirical value measure of net output produced by

individual industries.

As such, it can be used to reflect an approximation

of the net production of individual industries, and when aggregated for the

entire District region, it can be regarded as reflecting an approximation of

gross product originating in the District manufacturing sector.—The
affinity of the concept will enhance the comparability of the U. S. data to

the regional data, or vise versa, for various economic analysis.

Section III - Estimating Equations and Procedures
After considerable experimentation with various alternative approaches
and formulas used by some Federal Reserve Banks and proposed by others,

11/

9/
— U. S. Bureau of Census, Census of Manufactures 1963, Vol. I, page 22.

—^For a detailed explanation on concepts employed in the construction
of the U. S. production index, see Gehman and Metheral, ibid. , pp. 1-2.
—^Various alternative approaches and formulas considered include:

Pub­

lications cited in footnote 2 of this note, page 2; Technical Supplement to
"Measuring New England’s Manufacturing Production" (mimeograph), and Edwin F.
Estle and Jerilyn Fair, Technical Supplement to "Electric Power - An Indicator
of Industrial Activity" (mimeograph), 1965, all of which were published by the
Federal Reserve Bank of Boston; Richard Long, Measuring Regional Production, a
proposal, undated, Federal Reserve Bank of Atlanta; Carl W. Hale, Methodology
of the Texas Industrial Production Index, 1966, revision (mimeograph), July
1966, Federal Reserve Bank of Dallas. One of the more comprehensive studies
on the development of a regional production on micro-approach may be found in
T. Y. Shen, A Regional Production Index for New England (mimeograph), Federal
Reserve Bank of Boston, Boston, 1960.

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-9-

the following formulas and approaches were employed to estimate output for

individual two-digit SIC industries in the District.

Q,t = W -f
it
i

O + W%
gt
i

O
hi

(1)

V
Where A = L.
it

B - E

Q’

it

= wa

1

it

*
L .
iy

•
E

*
iy

(—)+Wu.
8i
1

&-)
h.

(2)

V.

Where A’ = L4it

i-1966

L

*

• [1 + (u± • n)]

i.1966

Vi.l966
B’ = E.
it

*

*

[1 + (v. ‘ n) ]

E i.1966

Where Q = output index
Wa = weight for man-hour index
L = monthly man-hour input
V = value added deflated by wholesale price index

W^ = weight for KWH index
E = KWH of electric power input

L

*

annual average of man-hour input

E = annual average of KWH input
g = 1957-59 average of A series
h = 1957-59 average of B series
u = monthly increment factor of labor productivity determined
by trend


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v = monthly increment factor of KWH productivity determined by
trend
i = industry
t = month
n = number of months counted consecutively by treating January
1967 to equal one
y = year

(NOTE:

Subscripts, 1966, in A’ and B’ denote the year for which
the latest Census data are available. As more current
Census data become available, the subscript should be
changed.)

Equation (1) was used to obtain monthly production indexes of individual
industries for the period between January 1960 and December 1966, while equa­

tion (2) was employed in deriving monthly indexes for January 1967 and there­
after.

The two equations are basically the same except that A and B (i.e., out­
put estimates made by man-hour and KWH inputs independently) in equation (1)
were obtained by the respective annual productivity factors derived from the

census annual value added and man-hour data, whereas A’ and B’ in equation (2)
were obtained by the productivity factors that were extrapolated largely on
the basis of past trends.

The productivity extrapolators, i.e., u-^ and v^,

used are shown in Appendix A, Table 1.

A couple of minor modifications were necessary in the actual operations

series to a six-month or three-month moving average series for several indus­
tries before they were combined to yield an industry production index, and

A
B
A’
B’
use of only the (—) , (—) , (—), or (-—) series because of input data problems
g
h
g
h

for three particular industries.

Types of specific variables used to derive

the production index for an industry are shown in Appendix A, Table 2.


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-11-

The estimation of the production index of individual industries for
current month involves the following steps:

(1)
(2)
(3)

(4)

estimation of output by man-hour input, i.e., A’ series
estimation of output by KWH input, i.e., B’ series
transformation of A’ and B’ series into an index ex­
pressed in terms of the 1957-59 average

A’
summation of the two indexes, i.e., summation of (—)
8i

B’
a
and (—) with appropriate weights used, that is W . and
b
hi
1
W . These weights are explained in the next Section.
The monthly production index derived from step 4 above is seasonally

adjusted by the application of the Census X-ll seasonal adjustment program.

Once the individual indexes are seasonally adjusted, no further seasonal
adjustments were made in deriving the aggregate indexes of durable, nondur­

able, and total manufacturing.

The seasonally adjusted aggregate indexes

were obtained by summing the seasonally adjusted component indexes with

industry weights.

In formula:

Q” t

.................................... (3)

Where Q" denotes an aggregate index
*

represents weights to individual
indexes, which are expressed in
fractions
i and t represent industry and month, respectively

W

The industry weights used to obtain the aggregate indexes were derived from
value added data of individual industries for 1963 to reflect the relative

importance of an industry within the three specific groups.


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The industry

-12-

weights used are shown in Appendix A, Table 3.

Section IV - Characteristics of the Estimating Equations

The two basic formulas employed to derive the new District production

index meet the tests of relative simplicity and economy, of consistency, and
of uniformity.

They are also, as pointed out earlier, compatible with the

U. S. production indexes.
First, as noted in the preceeding section, the estimation of monthly
output for individual industries involves 4 relatively simple steps, which do

not require extensive clerical work in collecting and processing primary in­
put data.

Moreover, the operating procedure involved is uncomplicated so

that overall cost necessary for computing and maintaining monthly indexes on

a continuing basis will be minimal whether actual computational works are
carried out by clerks or by computers.

As long as the formulas and variables

used yield reasonably meaningful empirical measurements of regional produc­

tion, the overall cost should be balanced and optimized in the light of po­
tential benefits derived from the use of the data.

Secondly, the basic

methodological framework is sufficiently consistent, not only with the theo­
retical production function but with the empirical relationship generally

observed between certain key inputs and physical output.

As will be dis­

cussed later, the formulas are capable of yielding estimated output indexes

which are sufficiently reflective of changes in demand for input factors even
when the practice of labor hoarding is prevalent.

Finally, the estimating

equations, as well as variables used, meet the test of uniformity in that in­

dexes for 18 individual industries were derived from a single basic formula,


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i.e., equation (2), with the use of the original regional data.

All of the

raw input variables used for the index derivation are original data applicable

to the region, in contrast with data that can be derived from secondary
sources, such as, deriving regional data by statistical decomposition of the
national data.

The use of original data as raw input has its own drawbacks,

such as the occasional needs for estimating certain data at the state level,

which were withheld in Census publications to preserve the confidentiality of
individual firms.

But, as compared with the use of secondary data derived

from the national data, the use of the regional data permits ease in tracing
the probable source of errors made not only in the computational stage but

also those errors frequently made in the initial data collection and process­
ing stages.

A specific advantage of relying exclusively on the original data

is that this allows better control in processing the input variables and elim­

inates needs for revising the District indexes each time any part of the na­

tional data is revised.
In addition to these general characteristics, there are two specific

structural characteristics embodied in the estimating equations.

The first

of these characteristics is that the equations are designed to yield output
estimates which produce the least statistical distortion when the estimates

are indexed based on the 1957-59 average.

As will be pointed out later, some

of the District input variables used were partially estimated, and the esti­

mating equations were designed to keep the probable effects of the estimated
variables at a minimum; because denominators "g" and ”h" (that is, the 195759 averages for "A" and "B" series) are by design, in fact, averages of value


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-14-

added for the 1957-59 period for individual industries.

Thus, if man-hour

inputs used for 1957, 1958, or 1959 were the variables estimated, the effects

of the man-hour estimates will not affect the index series, since the man­

hour input will be cancelled out by the denominator used for the industry’s
man-hour productivity for the year.

This consideration is rather crucial in

view of the fact that as we go back to the earlier years, the regional sta­
tistics available for many industries become pregressively more scarce.
Moreover, we wanted to incorporate the industrial use of electric power, but

data for electric power consumption by industry were not available prior to
1960 for the District states and prior to 1962 for the U. S.

However, the

cancelling feature of the estimating equations described above enabled us to

arrive at the KWH index for individual industries on the basis of the appro­
priate 1957-59 average, as the yearly KWH data estimated for the 1957-59 pe­

riod were cancelled out by the same data used to obtain the annual KWH pro­
ductivity, leaving the value added data for the base year period intact.
The second specific structural characteristic of the estimating equation

is that they were designed to reflect composite effects on outputs arising

from changes in the scale as well as the technology of production over a pe­
riod of time.

It is true that the composite effects are statistically im­

pregnated in the productivity of the individual input factors, since the pro­

ductivity used for current measurements of output is derived by extrapolation.
However, as an added built-in feature to make the index series more responsive

to changes in the input mix as well as to periodic changes in relative impor­

tance of individual factors, the man-hour and KWH index series are derived


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-15-

independently, but are combined in weighted form to yield an industry index.
(Weights used are shown in Appendix A, Table 4.)

The weights used were

based on labor and capital coefficients derived from the Cobb-Douglas produc
tion functions computed for individual industries from 1963 man-hour and
12/
capital data.

In addition to its conceptual merits for a long-run consideration, con­
current use of man-hour and KWH in the same formula enhances empirical reli­
ability of the index for the short run as well, because it increases the
sensitivity of the index to reflect concurrent changes taking place in the

production activity of industries.

As discussed below, changes in KWH con­

sumption are a better barometer of changes in demand for energy in many in­
stances than changes in demand for labor reflected in man-hour data.

Thus,

use of two independent variables (i.e., man-hour and KWH indexes) in the
same formula, in addition to making the output index more responsive to

changes in demand for inputs of both factors, tend to minimize possible dis­

torting effects attributable to certain flaws residing in man-hour data used
(Some of these flaws will be discussed in the next Section.)

For one thing,

monthly KWH data represent total electric energy consumed by industry during

the entire month.

Thus, with the exception of a certain fixed amount of

— An estimation of capital stock for the District manufacturing indus­
tries has been made by this Bank as a separate staff research project which
is still in progress. The principal methodology used for the estimation
relied heavily on one developed by Gallaway. Cf. Lowell E. Gallaway, "Re­
gional Capital Estimates by Industry, 1954-57," Southern Economic Journal,
Vol. XXIX, July 1962, pp. 21-25. Weights used for individual series were
not revised for the entire time span of index coverage, but are scheduled to
be reviewed and revised when the next Census of Manufactures becomes avail­
able, at which time all index series for 1967 and onward will be bench mark
adjusted.


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electric power used by industries for such overhead operations as lighting,

space heating, or cooling, KWH consumed closely approximate the actual
amount of electric energy used for production of firms’ output.

Furthermore,

KWH data readily reflects electric energy consumed by new establishments as
well as discontinuation of power use by defunct firms.

Section V - Data Sources and Limitations
Annual value added and man-hour data by industry up to the years prior

to 1967 were obtained from the Census of Manufactures for census years and
from the Annual Survey of Manufactures for interim Census years.

Monthly

man-hour data for the years prior to 1968 were obtained from the Employment

and Earning Statistics for the U. S., 1909-68, (U. S. Bureau of Labor Sta­

tistics, Bulletin No. 1312-6, 1968) and monthly man-hour data after 1968
were obtained from individual state labor departments in cooperation with the
U. S. Bureau of Labor Statistics.

Some of the data limitations which should be recognized for man-hour
statistics are:

First, they do not possess a high degree of sensitivity in

reflecting changes in demand for labor because of a certain rigidity in down­
ward adjustment of work hours.

For instance, during the beginning phase of

business fluctuations, employers do not always lay off workers simply because

demand for their products has slackened.

This is particularly true when a

business slowdown is expected to be brief in duration.

Moreover, for certain

processing industries in which production methods are highly automated and

mechanized, such as chemical and petroleum industries, man-hour data are


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-17-

generally considered as a poor proxy for estimating physical output.-*-

More

importantly, monthly employment data, upon which man-hour data are based,
do not represent a whole month but cover only a single survey week which

includes the 12th day of the month.

Also, man-hour data represent man-hour

paid by employers rather than actual man-hours worked in plant for production
This tends to distort actual amount of labor put into production, especially
during those months when many workers are away from a plant on vacation.

Finally, it should be emphasized that monthly man-hour data used were not de­

rived from well-controlled random samples.

called "cutoff” sample method.

They were derived by the so

Under this method, tabulation of sample data

are made until reports from a certain percentage of the sample firms have
been received by the state labor departments.

Consequently, the probability

errors associated with sample procedures in data collection cannot be sta­

tistically determined and corrected.
The KWH data that were utilized came from those collected and maintained

by the Bank and the Board of Governors of the Federal Reserve System.

While,

as noted earlier, these data are fairly comprehensive and timely, they are
not entirely free of structural defects.

Wherever practical, efforts were

made to negate potential effects of the data deficiencies.

First, because of the cycle-billing method used by utility companies,
13/
— Experience of the Federal Reserve Bank of Dallas in the construction
of the Texas production index shows that man-hour data cannot be relied on
for chemical and petroleum industries, Minutes of the Workshop on Local Pro­
duction Indexes, (the conference was held at the Federal Reserve Bank of
Cleveland on April 1964), Federal Reserve System, page 2.


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-18-

monthly KWH data as reported may or may not coincide with the actual month
for which the data represent.

As an attempt to minimize this distortion,

practically all of the KWH indexes were adjusted using either a six-month
or a three-month moving average.

Secondly, the consumption of electric

power displays strong seasonal variations which are generally believed to
be caused by widespread use of electricity for space heating and cooling.
However, possible distortions arising from this source are also believed
to have been substantially corrected by the seasonal adjustments applied

B
B’
14/
to the KWH indexes, i.e., the (—) or G—) series.
n•
n.
i
l

Thirdly, it should

be recognized that for certain industries that rely heavily on energy
other than electric power, KWH data may not have reliable empirical content

as a major input factor.

situation.

No attempts were made to correct this particular

15/

There is an inherent difficulty in using regional data published in

Census data.

First, certain information was withheld from publication be­

cause of disclosure provisions.

Those data withheld which were essential

to the construction of the District index were estimated, while those that
were relatively insignificant for our purpose were ignored.

Secondly,

state data published in the Annual Survey of Manufactures are subject to

—^The KWH data used were not adjusted for working days due to a prac­
tical difficulty involved in ascertaining the correct working days for six
different states.
—/Since only KWH data and man-hour data are used as proxy measures of

output, the relative weights assigned to the two individual input series may
have been distorted for those industries that rely heavily on energy sources
other than electric power.


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-19-

sampling errors.

Firms in the sample, as well as the sample size, vary from

one year to another, and the Bureau of Census does not revise bench mark

data for states once the data are published in the Annual Survey of Manufac­
tures .

Thus, the District data compiled from the Annual Survey and certain

computations derived from the data may not have the same accuracy as the

similar data for the nation as a whole.

As shown in Appendix A, Table 5,

regression coefficients of annual man-hour productivity were lower for the
District industries than for their national counterparts while the standard
deviations were higher for the District industries than for the same indus­

tries in the U. S.

However, complete bench mark revisions in the District

index can be made when a comprehensive Census of Manufacture is made avail­

Despite incomplete nature of data published in Annual Survey of Manu­

able.

factures , an annual bench mark revision may need to be made for interim

Census years on the basis of the value added data published in the annual

publication.
Price data used to deflate value added figures were wholesale price in­
dexes applicable to two-digit or three-digit industry levels.

ciencies in the use of price information should be pointed out.

Several defi­

First,

since no regional wholesale price data were available, the deflators used

were the national data, compiled by the U. S. Bureau of Labor Statistics

(BLS).

Secondly, this deflation process differs from the so called ’’double

deflation" method, generally used when separate price data for input factors

and outputs are available.

Under the double deflation method, values of in­

puts and outputs are deflated separately to obtain value added by appropriate


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-20-

price indexes applicable to either inputs or outputs.

Thirdly, the BLS•

uses the 1958 weights beginning in 1961 and the 1954 weights for 1958 through

1960.

Since no adjustment could be made for the shifting in the BLS weight­

ing period, there is a slight possibility that some errors may have developed
during our process of price deflation.

If this were the case, the estimates

of the productivities of man-hour and KWH which had been computed from the
deflated value added might have been distorted.
As shown in Section II of this note, the input productivity factor used
for monthly indexes of January 1967 up to the present were extrapolated on the

basis of historical trends of the respective productivity factors.

It should

be pointed out that productivity factors so calculated in many cases may not

reflect an accurate picture of concomitant productivity changes in certain in­

dustries.

For instance, they tend to underestimate current productivity for

those industries where labor productivity has been rising rapidly, such as
the machinery industry.

On the other hand, they tend to overestimate the cur­

rent productivity for those industries whose productivities grow slowly or are
not growing at all.

Various empirical studies showed that changes occurring

in labor productivity were quite sensitive to the business cycle, and changes

in output per man-hour and those in the level of output in many industries
17/
were positively related.
A couple of alternative approaches to overcome

— A useful discussion on this point may be found in Paul A. David, ’’The
Deflation of Value Added," Review of Economics and Statistics, Vol. 44, 1962,
pp. 148-155.

—^See on this point, Hultgren, ibid., Chapter 2 and Kuh, ibid.

See also

Thomas A. Wilson and Otto Eckstein, "Short-run Productivity Behavior in U. S.
Manufacturing," Review of Economics and Statistics, Vol. 46, 1964, pp. 41-54,
and T. Y. Shen, "Innovation, Diffusion, and Productivity Changes," Review of
Economics and Statistics, Vol. 43, 1961, pp. 175-181. For a useful discussion
on how man-hour productivity behaved for the postwar period and on the factor
affected the productivity change, see Trend in Output Per Man-hour in the 'Pri­
vate Economy, 1909-1958, Bulletin No. 1249, U. S. Bureau of Labor Statistics,
December 1959.


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-21-

problems in using the productivity extrapolator have been suggested; however,
data problems encountered at the regional level have precluded the applica-

c ,
18/
tion of the alternative approaches in the derivation of District indexes.

In this respect, for certain industries that are vulnerable to cyclical

swings, such as the primary metals industry, use of the productivity extrapola­
tor as the current productivity factor may have a strong tendency to distort
the true picture of productivity changes during cyclical fluctuations.

Another potential source of distortion that may have affected the size of

the productivity extrapolators was the application of a single extrapolator to
broad industrial groupings designated by two-digit SIC.

There is no doubt

that the empirical reliability of the index would have been enhanced if the

productivity extrapolators had been computed and applied to a three-digit SIC

industry basis.
Another limitation inherent in the new District indexes is that they are

incapable of reflecting inventory change and shipment situation.

Therefore,

if it is assumed that no stable functional relationship existed between produc­

tion and shipment over a long period of time, the validity of the new District
index is weakened, particularly, the usefulness of the indexes as empirical

measurements to reflect business cycle phenomena.

Section VI - Empirical Validity of District Production Index
Discussion will now be focused on the attempt made to assess the empirical

— Hultgren suggested the use of man-hour and payroll indexes divided by
the index of quantity of output sold, and Shen suggested the estimation of
value added and productivity on the basis of the estimation of cross section
parameters. See Thor Hultgren, Cost, Prices, and Profits ; Their Cycle Rela­
tions , National Bureau of Economic Research, New York, 1965, pp. 13-36, and
T. Y. Shen, ibid. , (A Regional Production Index for New England), page 6.


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-22-

reliability of District production index.

Since data on actual outputs by

District industries are not available, it is impossible to apply direct tests

on the District indexes which are, in fact, the summary measures derived from

the use of the estimating formulas and statistical procedures.

Consequently,

only indirect tests can be made to determine whether the behavioral patterns
of computed District indexes have reasonably reliable empirical contents as in­

dividual component series or as an aggregate series, such as the total manufac­
turing index.

Two indirect methods were employed in the present investigation.

The first method relied on a detailed analysis of graphical, behavioral
patterns of the District’s individual industry index series.

The individual

industry series were first examined for their seasonal patterns, general trend
behavior, and obvious erratic movements.

Then, they were compared with the

comparable TJ. S. production index series to study their relative behavioral
patterns.

More specifically, the behavior of each District index and its U. S.

counterpart is analyzed to detect conformity, or lack of it, between them in
the timing of the series’ turning points, as well as in the direction and slope
of the series’ movements.

In general, except for a few isolated incidences

where divergences observed between District and U. S. indexes series could not

be satisfactorily accounted for, the District production indexes, both as in­
dividual components and as an aggregate series, appeared to be reasonably reli­

able summary measures which reflect changes in the level of physical outputs by
individual industries.

The other method employed as the indirect test was to measure quantita­
tively the relative performance of the District production indexes.


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One

-23-

possible way of accomplishing this test is by applying statistical measures
to joint distributions of two sample universes that are delineated by common
denominators.

The testing procedure that was devised, related the distri­

bution of annual production index ratios for the District and U. S. to the
distribution of annual employment index ratios for the District and U. S. for

each industry. In order to standardize the variables, the employment data
were indexed in relation to the 1957-59 average.

District variables for each

given year were then expressed in relation to the value of the U. S. variables
Consequently, since the ratio variables used for testing were ones jointly

determined by the relevant District and U. S. variables, they will reflect
changes observed both within and between time periods.

As will be seen

shortly, this simple procedure permits the formulation and testing of an

hypothesis which is more meaningful than mere descriptive measures, such as
means and standard deviations.
One important assumption underlying the testing procedure is that for

each industry in any given year, the variances observed between District and

U. S. employment are equal to the variances observed between District and U. S
production indexes.

That is, for a given industry, the parameters for the

production functions of the District and the U. S. are the same.

Another im­

portant assumption is that all variables used in computing the annual ratios

for the two sample universes are accurate and empirically reliable, except

for the District production indexes.

If these two assumptions hold true, the

variances observed in the District production index in relation to the U. S.

index will be equal to the variances observed in the District employment index


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-24-

in relation to the U. S. index for the same industry.

To illustrate the procedures used, two sets of ratio variables were ob­

tained individually for nine major industries in the District.

The combined

value added for these industries accounts for almost two-thirds of the total
value added for the District’s entire manufacturing.
covered a nine-year period from 1960 through 1968.

Each ratio variable
The first set of ratio

variables was computed by dividing the annual District production index for

an industry by the U. S. production index for the same industry.

The second

set of ratio variables was obtained by dividing the annual District employ­

ment index for an industry by the U. S. employment index for the same industry.

Then, arithmetic means and standard deviations were computed for each set, and
they were compared with each other on an industry basis.

was followed for total manufacturing.

The same procedure

Results of the computations are shown

in Appendix A, Table 6.
A close examination of the table indicates that generally the sample
means of production indexes are very similar to those of the employment indexes.

In order to tests the statistical significance of differences observed between

the two sample means, tests were made on the hypothesis that u^ = u^? that is,
there is no difference between the two means.

On the basis of this testing,

the hypothesis for all of the nine selected industries, except three (i.e.,

textiles, lumber and wood, and paper), was accepted at the 5-percent level of
significance.

At this point, it should be emphasized that the rejection of the hypothesis

for three industries does not necessarily indicate flaws in their production


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-25-

indexes.

When considering the assumption underlying the test (i.e., there

is no difference in the parameters of the production functions between the
District and U. S. for the same industry), the rejection of the hypothesis
for certain industries was not unexpected.

In this respect, the rejection

of the hypothesis for these three industries actually enhances the empirical
validity of their District indexes; because in these industries, the Dis­

trict has the relative comparative advantage over other regions in its inter­

regional trade.

As such, productivity of these industries in the District

has usually been higher than that of its U. S. counterparts.

For instance,

in 1966, the value of shipments per man-hour for the District’s paper indus­

try was $22.36, as compared with $18.98 for the U. S. paper industry as a
whole/

When considering that errors can be accumulated in the individual Dis­
trict production indexes under the methodology used in the index derivation

(i.e., continuous application of monthly productivity extrapolators used in

the District indexes), and when considering the potential problems presented
by various limitations of the regional data employed, the results of the sta­

tistical testing seem to validate the empirical contents of the new District

production indexes even more than the investigator had hoped.

19/
— See C. S. Pyun, "The Southeast’s Booming Paper Industry," Monthly Review,
Federal Reserve Bank of Atlanta, September 1969, page 111.


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APPENDIX A, Table 1.

PRODUCTIVITY EXTRAPOLATORS

KWH

Man-hour
Monthly
Increment
Factor

Productivity
1966

Monthly
Increment
Factor

Industry

Productivity
1966

Food (20)

257.34

.0020295

.804

-.0014057

Tobacco (21)

213.26

.0021665

3.260

-.0074888

Textiles (22)

202.37

.0046460

.320

.0018950

Apparel (23)

123.95

.0020077

2.970

-.0051686

Lumber and Wood (24)

127.71

.0049868

.690

-.0026000

Furniture and Fixtures (25)

165.45

.0016378

1.440

-.0065684

Paper (26)

400.08

.0024894

.127

.0001890

Printing and Publishing (27)

254.87

.0013271

2.080

-.0064099

Chemicals (28)

551.42

.0058098

.144

.0003350

.276

-.0002200

.070

.0046950

Petroleum (29)

Rubber (30)

606.45

.0052336

Leather (31)

183.15

.0012136

Stone, Clay, and Glass (32)

251.33

.0014557

Primary Metals (33)

367.84

.0036993

Fabricated Metals (34)

241.25

.0016778

Non-Electrical Machinery (35)

257.73

.0006519

1.580

-.0016623

Electrical Machinery (36)

399.50

.0064015

.730

.0045170

Transportation Equipment (37)

293.18

.0027751

1.530

.0050990


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Federal Reserve Bank of St. Louis

-27-

APPENDIX A

Table 2.

INDUSTRY INDEX DERIVATION

Indus try

Component and Type of Variable Used

Food (20)

Man-hour and KITH**

Tobacco (21)

Man-hour* only

Textiles (22)

Man-hour and KWH**

Apparel (23)

Man-hour and KWH**

Lumber and Wood (24)

Man-hour and KWH**

Furniture and Fixtures (25)

Man-hour and KWH**

Paper (26)

Man-hour and KWH**

Printing and Publishing (27)

Man-hour and KWH**

Chemicals (28)

Man-hour and KWH**

Petroleum (29)

KWH* only

Rubber (30)

Man-hour and KWH**

Leather (31)

Man-hour* only

Stone, Clay, and Glass (32)

Man-hour only

Primary Metals (33)

Man-hour and KWH*

Fabricated Metals (34)

Man-hour* only

Nonelectrical Machinery (35)

Man-hour and KWH

Electrical Machinery (36)

Man-hour and KWH

Transportation Equipment (37)

Man-hour* and KWH

NOTE:

Components with one asterisk (*) means that they were adjusted on a
three-month moving average and components with two asterisks (**) rep
resent those series adjusted on a six-month moving average. Com­
ponents with no asterisk means that they were used in their original
form with no moving average applied.


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Federal Reserve Bank of St. Louis

-28-

APPENDIX A

Table 3.

VALUE ADDED BY MANUFACTURE, 1963
District States

Value Added
($000)

Industry
Total Manufacturing

Percent
Distribution

13,871,153

100.00

1,993,253

14.37

66,703

0.48

1,070,613

7.72

Apparel (23)

952,616

6.87

Lumber and Wood (24)

571,356

4.12

Furniture and Fixtures (25)

285,504

2.06

1,122,583

8.09

516,991

3.73

Chemicals (28)

2,149,584

15.50

Petroleum (29)

330,999

2.38

Rubber (30)

291,133

2.10

Leather (31)

163,297

1.18

Stone, Clay, and Glass (32)

672,145

4.84

1,007,192

7.26

Fabricated Metals (34)

652,016

4.70

Nonelectrical Machinery (35)

422,151

3.04

Electrical Machinery (36)

546,448

3.94

1,056,569

7.62

Food (20)
Tobacco (21)

Textiles (22)

Paper (26)
Printing and Publishing (27)

Primary Metals (33)

Transportation Equipment (37)

Source:

U. S. Bureau of Census, Census of Manufactures, 1963.


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-29-

APPENDIX A

Table 4.

FACTOR WEIGHTS, 1963

Industry

Man-hour
Weight

KWH
Weight

Food (20)

.2132

.7868

Tobacco (21)

.2900*

.7100*

Textiles (22)

.4682

.5318

Apparel (23)

.4740

.5260

Lumber and Wood (24)

.4763

.5237

Furniture and Fixtures (25)

.4323

.5677

Paper (26)

.3095

.6905

Printing and Publishing (27)

.3202

.6798

Chemicals (28)

.1751

.8249

Petroleum (29)

.1867*

.8133*

Rubber (30)

.3179

.6821

Leather (31)

.4156*

.5844*

Stone, Clay, and Glass (32)

.2904*

.7096*

Primary Metals (33)

.3189

.6811

Fabricated Metals (34)

.3747*

.6253*

Nonelectrical Machinery (35)

.3685

.6315

Electrical Machinery (36)

.2673

.7327

Transportation Equipment (37)

.3603

.6397

*These weights were not used in computing production indexes for
the indicated industries because only a single input series (i. e., either
man-hour or KWH input series) was used in the index derivation for these
industries. See Appendix A, Table 2, page 27 from the specific input
series used.


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LINEAR REGRESSION OF ANNUAL MAN-HOUR PRODUCTIVITY, 1957-65

APPENDIX A, Table 5.

(y = a + bx

Industry
Food (20)
Tobacco (21)
Textiles (22)
Apparel (23)
Lumber and Wood (24)
Furniture and Fixtures (25)
Paper (26)
Printing and Publishing (27)
Chemicals (28)
Petroleum (29)
Rubber (30)
Leather (31)
Stone, Clay, and Glass (32)
Primary Metals (33)
Fabricated Metals (34)
Machinery (35)
Electrical Machinery (36)
Transportation Equipment (37)

NOTE:

y = annual man-hour productivity; x = n; xo = 1956)

Regression
Coefficient

District
Coefficient
of
Correlation

Standard
Error of
Estimate

7.73
2.92
8.93
4.72
4.84
4.07
13.39
3.82
25.00
29.53
13.27
1.32
11.52
13.02
4.63
14.19
11.10
12.35

.952
.256
.985
.889
.877
.806
.958
.728
.940
.768
.740
.307
.879
.851
.921
.890
.930
.846

6.426
28.455
4.024
6.278
6.861
7.714
10.398
9.297
23.501
63.498
31.152
10.518
16.143
20.739
5.061
18.759
11.292
20.079

Regression
Coefficient

U. S.
Coefficient
of
Correlation

Standard
Error of
Estimate

11.02
20.94
7.84
4.27
6.07
3.60
8.52
6.63
23.77
34.30
9.87
2.22
9.46
8.82
5.56
9.41
15.48
15.94

.980
.990
.990
.914
.968
.939
.989
.987
.982
.967
.989
.761
.938
.953
.971
.956
.977
.990

5.787
7.832
2.872
4.877
4.038
3.413
3.242
2.810
11.688
23.207
3.764
4.896
9.045
7.226
3.558
7.454
8.767
5.779

Value of regression coefficients for both the District and the U. S. are large because annual man-hour produc­
tivity data regressed were obtained by using annual average man-hour data.


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APPENDIX A, Table 6

Industry

RELATIVE PERFORMANCE OF DISTRICT PRODUCTION INDEXES
FOR SELECTED INDUSTRIES

Ratio of District Production
Index to U. S. Production
Index
Standard
Mean
Deviation

Ratio of District Employment
Index to U. S. .Employment
Index
Standard
Mean
Deviation

Computed
t Value*

Food (20)

1.0763

.0305

1.0920

.0397

.8870

Textiles (22)

1.2122

.1111

1.0359

.0194

4.4185

Apparel (23)

1.3242

.1707

1.2980

.1326

.3429

Lumber and Wood (24)

1.0990

.0959

.9852

.0145

3.3178

Paper (26)

1.0764

.0149

.9834

.0260

8.7736

Chemicals (28)

1.0430

.0422

1.0279

.0379

.7550

Stone, Clay, and Glass (32)

1.0561

.1389

1.0992

.0551

.8163

Fabricated Metals (34)

1.1551

.0971

1.1610

.0942

.1234

Transportation Equipment (37)

1.2984

.2945

1.3429

.2118

.3468

Total Manufacturing

1.1403

.0880

1.1108

.0578

.7930

* - t with 16 degrees of freedom at the .05 level is 2.12.


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APPENDIX B

1960
1961
1962
1963
1964
1965
1966
1967
1968
1969

PRODUCTION INDEX
SIXTH FEDERAL RESERVE DISTRICT STATES
SIC 20 - FOOD AND KINDRED PRODUCTS
(Seasonally Adjusted, 1957-59=100)

Jan.

Feb.

Mar.

Apr.

May

111.0
112.5
122.3
128.3
136.7
140.3
142.5
143.9
149.0

111.3
114.3
122.3
128.9
137.4
141.4
143.0
144.9
150.3

112.5
115.6
122.7
128.1
138.1
142.8
145.1
144.9
151.0

112.7
116.1
123.2
128.9
139.1
141.1
146.3
145.2
151.6

114.3
117.9
122.4
129.0
138.6
141.2
146.9
147.0
152.7

June

July

Aug.

Sept.

Oct.

Nov.

Dec.

110.7
115.3
119.8
122.0
130.0
138.0
140.5
150.2
149.6
155.2

112.6
114.3
121.3
121.0
131.5
137.0
140.8
150.1
149.8
158.3

111.9
113.9
120.2
121.6
133.2
137.0
140.7
149.8
151.3
158.5

111.8
113.5
120.8
124.4
133.7
136.2
140.9
149.6
152.1
158.8

111.0
113.1
121.9
125.6
133.2
137.2
140.8
148.4
153.1
160.5

110.8
112.7
122.2
126.6
135.7
138.1
141.5
147.4
153.2
161.0

111.8
113.2
121.6
129.0
137.8
139.0
142.1
146.9
153.8
161.7

i
w
ro
I

SIC 21 - TOBACCO MANUFACTURES
(Seasonally Adjusted., 1957=59=4-00)

1960
1961
1962
1963
1964
1965
1966
1967
1968
1969

Jan.

Feb.

Mar.

Apr.

May

June

July

Aus-

Sept.

Oct.

Nov.

Dec.

90.5
86.1
88.2
85.1
85.5
83.1
84.8
73.8
73.5

89.9
88.2
85.3
84.9
89.2
83.5
84.6
83.3
83.2
74.7

97.5
87.0
85.0
82.4
90.9
81.6
86.5
82.9
80.1
74.8

98.0
86.3
83.6
82.4
94.4
80.8
86.1
84.2
79.8
74.7

98.8
88.0
79.9
82.4
92.4
81.8
85.6
86.4
80.4
75.2

97.5
90.6
79.8
81.8
91.4
81.6
86.5
82.5
80.8
75.3

97.2
92.6
80.9
84.7
88.3
82.7
85.8
82.3
80.6
75.0

99.6
94.8
83.0
80.5
86.1
82.8
86.0
83.0
78.7
75.1

101.9
94.8
83.3
81.6
85.9
83.1
84.6
87.0
78.7
75.4

104.5
93.7
84.2
82.0
85.5
82.5
85.0
87.3
79.0
76.0

99.3
90.3
86.4
82.1
86.5
82.1
85.3
76.1
78.0
75.2

99.9
88.0
89.2
84.2
86.5
81.9
85.9
76.0
76.7
74.9


https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis

SIC 22 - TEXTILE MILL PRODUCTS
(Seasonally Adjusted, 1957-59=100)

1960
1961
1962
1963
1964
1965
1966
1967
1968
1969

Jan.

Feb.

Mar.

Apr.

May

June

July

Aug.

Sept.

Oct.

Nov.

Dec.

113.8
127.7
125.8
136.9
159.3
182.2
190.7
199.4
216.3

113.4
130.2
124.7
139.2
161.7
182.2
188.1
202.6
216.1

114.2
130.9
124.5
141.8
163.7
183.2
186.8
205.0
218.7

115.0
130.6
125.6
144.3
166.1
184.1
185.5
203.7
219.7

116.5
130.6
125.8
142.1
167.9
185.7
187.1
206.1
222.8

115.7
116.4
130.3
126.5
149.9
170.3
184.5
187.8
208.8
225.1

115.4
119.6
130.1
127.5
152.3
171.8
188.5
187.8
210.4
228.4

113.4
121.2
130.5
128.0
150.9
174.0
189.4
188.5
212.3
229.8

112.1
123.1
129.3
129.3
150.3
174.7
190.9
190.8
212.9
231.4

110.7
124.2
128.4
131.2
154.4
176.5
190.4
193.0
213.6
229.4

110.8
125.0
128.3
132.4
155.6
178.6
190.2
195.0
215.3
229.3

110.5
126.2
127.3
134.0
156.9
180.6
190.3
197.4
215.9
228.9

SIC 23 - APPAREL AND OTHER FINISHED PRODUCTS
(Seasonally Adjusted, 1957-59=100)

1960
1961
1962
1963
1964
1965
1966
1967
1968
1969

Jan.

Feb.

Mar.

APr-

May

June

July

Aug.

Sept.

Oct.

Nov.

Dec.

118.9
128.4
153.1
182.3
196.0
209.7
216.7
216.8
240.5

122.8
136.6
156.4
182.8
192.9
208.9
216.1
225.2
243.0

119.1
138.4
163.1
182.3
194.0
208.2
216.9
230.1
244.6

119.6
137.6
167.7
180.8
194.7
210.5
219.3
230.6
244.1

118.8
138.0
174.6
178.8
195.5
204.3
221.0
233.8
244.0

114.8
119.7
139.5
179.4
180.5
197.3
206.9
227.1
239.3
249.9

115.2
121.9
140.7
180.8
182.9
197.4
206.6
223.4
237.1
250.6

115.1
124.4
142.0
182.7
184.2
202.1
209.8
219.5
237.7
248.4

115.9
126.6
144.8
183.1
184.2
204.6
211.6
219.3
238.5
254.1

114.8
128.4
146.6
182.3
186.6
206.9
213.2
218.2
239.2
254.0

115.1
131.1
147.9
182.6
188.9
207.7
213.2
219.1
240.6
257.2

114.0
133.3
148.6
183.3
189.9
208.8
215.4
219.8
240.9
255.8


https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis

SIC 24 - LUMBER AND WOOD PRODUCTS
(Seasonally Adjusted, 1957-59=100)

1960
1961
1962
1963
1964
1965
1966
1967
1968
1969

Jan.

Feb.

Mar.

Apr.

May

June

July

Aug-

Sept.

Oct.

Nov.

Dec

95.5
97.6
114.2
126.0
128.9
137.2
144.2
133.5
159.0

94.0
103.7
116.0
128.3
126.7
137.1
140.6
142.7
161.8

93.3
104.2
117.8
128.1
128.3
137.6
139.3
144.0
156.1

93.8
104.5
120.2
127.4
129.5
139.2
137.4
145.4
163.1

95.2
105.9
122.1
127.7
129.5
140.8
134.9
149.3
163.5

100.6
97.2
104.3
125.3
128.2
128.5
141.3
134.3
153.2
167.2

100.8
98.2
105.4
126.1
128.3
130.1
141.9
130.6
156.7
166.6

99.0
100.5
105.1
127.7
127.3
131.3
143.2
133.8
156.9
168.0

98.7
101.7
107.3
127.9
125.6
130.8
144.6
135.2
156.9
167.8

96.8
101.8
108.0
128.9
126.0
133.4
144.2
135.2
156.4
167.5

96.7
101.9
108.9
129.2
128.7
134.7
143.4
135.2
157.2
166.6

94.
101.1
108.1
128.
127.1
136.1
144.1
136.1
157.
166 •

SIC 25 - FURNITURE AND FIXTURES
(Seasonally Adjusted, 1957-59=100)

1960
1961
1962
1963
1964
1965
1966
1967
1968
1969

Jan.

Feb.

Mar.

Apr.

May

June

July

Au.g,-

Sept.

Oct.

Nov.

Dec.

101.4
105.8
126.3
145.8
161.1
178.3
184.1
179.1
197.2

99.4
112.5
127.7
146.7
162.6
179.0
182.9
182.9
198.1

98.1
114.5
129.6
146.2
165.1
179.5
182.1
185.2
198.3

97.9
115.5
131.2
146.8
167.1
180.4
181.0
184.6
200.6

97.1
117.7
133.0
147.3
169.1
179.4
181.6
189.2
196.6

103.1
97.7
120.3
135.0
146.8
170.0
181.4
181.7
192.6
197.7

104.6
100.7
121.5
136.6
146.4
172.2
181.9
183.5
193.0
192.7

105.3
102.7
122.5
138.7
148.6
173.4
183.5
179.4
194.1
195.6

104.7
105.0
124.6
139.7
150.6
174.0
184.2
178.9
194.3
194.4

104.7
106.0
124.5
141.6
153.5
175.1
184.8
177.3
194.9
192.4

102.9
108.0
125.1
142.6
154.9
177.0
185.2
178.7
194.6
190.3

102.0
109.9
124.6
142.9
157.8
178.4
183.8
181.0
196.6
185.9


https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis

SIC 24 - LUMBER AND WOOD PRODUCTS
(Seasonally Adjusted, 1957-59=100)

1960
1961
1962
1963
1964
1965
1966
1967
1968
1969

Jan.

Feb.

Mar.

Apr.

May

June

July

Aug.

Sept.

Oct.

Nov.

Dec.

95.5
97.6
114.2
126.0
128.9
137.2
144.2
133.5
159.0

94.0
103.7
116.0
128.3
126.7
137.1
140.6
142.7
161.8

93.3
104.2
117.8
128.1
128.3
137.6
139.3
144.0
156.1

93.8
104.5
120.2
127.4
129.5
139.2
137.4
145.4
163.1

95.2
105.9
122.1
127.7
129.5
140.8
134.9
149.3
163.5

100.6
97.2
104.3
125.3
128.2
128.5
141.3
134.3
153.2
167.2

100.8
98.2
105.4
126.1
128.3
130.1
141.9
130.6
156.7
166.6

99.0
100.5
105.1
127.7
127.3
131.3
143.2
133.8
156.9
168.0

98.7
101.7
107.3
127.9
125.6
130.8
144.6
135.2
156.9
167.8

96.8
101.8
108.0
128.9
126.0
133.4
144.2
135.2
156.4
167.5

96.7
101.9
108.9
129.2
128.7
134.7
143.4
135.2
157.2
166.6

94.2
101.0
108.0
128.6
127.0
136.0
144.0
136.0
157.3
16$. 3

SIC 25 - FURNITURE AND FIXTURES
(Seasonally Adjusted, 1957-59=100)

1960
1961
1962
1963
1964
1965
1966
1967
1968
1969

Jan.

Feb.

Mar.

Apr.

May

June

July

Aug.

Sept.

Oct.

Nov.

Dec.

101.4
105.8
126.3
145.8
161.1
178.3
184.1
179.1
197.2

99.4
112.5
127.7
146.7
162.6
179.0
182.9
182.9
198.1

98.1
114.5
129.6
146.2
165.1
179.5
182.1
185.2
198.3

97.9
115.5
131.2
146.8
167.1
180.4
181.0
184.6
200.6

97.1
117.7
133.0
147.3
169.1
179.4
181.6
189.2
196.6

103.1
97.7
120.3
135.0
146.8
170.0
181.4
181.7
192.6
197.7

104.6
100.7
121.5
136.6
146.4
172.2
181.9
183.5
193.0
192.7

105.3
102.7
122.5
138.7
148.6
173.4
183.5
179.4
194.1
195.6

104.7
105.0
124.6
139.7
150.6
174.0
184.2
178.9
194.3
194.4

104.7
106.0
124.5
141.6
153.5
175.1
184.8
177.3
194.9
192.4

102.9
108.0
125.1
142.6
154.9
177.0
185.2
178.7
194.6
190.3

102.0
109.9
124.6
142.9
157.8
178.4
183.8
181.0
196.6
185.9


https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis

SIC 26 - PAPER AND ALLIED PRODUCTS
(Seasonally Adjusted, 1957-59=100)

1960
1961
1962
1963
1964
1965
1966
1967
1968
1969

Jan.

Feb.

Mar.

Apr.

May

June

July

Aug.

Sept.

Oct.

Nov.

Dec.

120.8
124.5
128.9
130.1
144.2
159.4
172.5
175.5
182.9

119.5
125.0
129.6
132.5
145.0
160.8
172.9
176.1
185.1

120.4
125.3
128.8
133.8
146.1
163.7
173.8
175.8
186.0

121.3
127.4
126.2
135.8
146.9
167.5
171.6
176.7
189.8

122.0
127.8
125.5
137.3
147.9
168.1
170.8
177.5
193.6

119.6
122.8
129.4
123.8
138.3
149.2
170.1
171.2
176.0
194.8

119.2
123.6
129.3
123.8
139.7
149.8
172.0
171.6
177.2
196.7

120.1
124.8
130.7
124.0
140.0
150.5
172.1
172.0
178.3
197.4

119.6
125.0
131.1
121.1
141.1
152.2
172.7
173.1
178.3
199.5

119.9
125.4
131.5
125.5
141.4
153.2
173.7
173.4
178.4
200.6

118.9
125.9
131.8
126.2
142.0
154.9
174.7
174.2
179.5
200.6

118.4
126.2
132.6
126.6
143.1
156.9
172.9
174.9
181.0
202.9

SIC 27 - PRINTING, PUBLISHING, AND ALLIED INDUSTRIES
(Seasonally Adjusted, 1957-59=100)

1960
1961
1962
1963
1964
1965
1966
1967
1968
1969

Jan.

Feb.

Mar.

Apr.

May

June

July

Aug.

Sept.

Oct.

Nov.

Dec.

114.2
113.2
112.0
125.8
131.4
149.8
163.2
163.2
165.5

113.0
114.5
111.6
125.8
134.1
150.9
163.8
163.8
166.3

113.3
114.1
111.1
125.9
135.2
153.4
164.5
164.9
165.9

109.7
114.1
114.0
126.0
137.0
152.8
165.2
165.3
165.0

107.3
113.7
116.5
124.6
138.6
153.4
166.3
165.7
163.9

111.7
107.6
113.7
117.8
125.6
140.3
155.0
164.9
167.2
165.6

113.2
107.6
114.9
118.6
126.9
140.7
156.5
164.9
166.1
166.7

113.6
108.4
116.1
119.8
127.8
141.7
157.6
163.3
167.4
168.0

113.7
109.0
115.2
121.9
128.1
143.7
158.2
161.9
167.3
168.5

115.4
110.4
114.3
122.3
128.9
145.8
160.3
161.9
166.9
168.8

116.2
111.4
113.3
123.4
130.0
147.0
162.0
161.5
167.1
170.5

115.0
114.2
112.7
124.2
131.2
148.0
162.8
162.5
167.0
170.6


https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis

SIC 28 - CHEMICALS AND ALLIED PRODUCTS
(Seasonally Adjusted, 1957-59=100)

1960
1961
1962
1963
1964
1965
1966
1967
1968
1969

Jan.

Feb.

Mar.

Apr.

May

June

July

Aug.

Sept.

Oct.

Nov.

Dec.

121.1
130.0
144.4
168.4
168.9
194.9
214.1
230.7
249.8

123.2
128.0
145.1
169.7
173.6
196.0
217.0
233.3
251.0

112.4
124.0
125.2
148.9
169.4
178.0
195.5
219.5
234.8
251.4

114.8
124.9
127.4
151.0
171.3
182.1
198.7
219.2
237.3
254.7

113.0
126.6
129.1
152.8
170.7
182.0
201.8
219.8
237.0
256.0

111.9
128.6
130.0
151.8
171.6
184.3
203.4
222.6
237.8
254.6

110.4
126.7
132.9
154.1
169.8
185.9
205.3
226.5
238.0
255.8

111.7
124.9
134.9
155.0
169.7
188.5
207.6
228.8
239.5
255.7

112.4
122.8
138.3
155.7
169.9
189.0
209.1
229.3
245.3
261.0

116.3
124.8
141.8
157.2
169.7
190.8
208.9
230.6
249.9
263.4

117.1
127.1
143.6
162.1
168.4
191.2
209.7
232.6
252.5
265.0

119.5
131.8
144.0
166.2
166.7
193.1
209.2
231.8
250.7
261.2

SIC 29 - PETROLEUM REFINING AND RELATED INDUSTRIES
(Seasonally Adjusted, 1957-59=100)

1960
1961
1962
1963
1964
1965
1966
1967
1968
1969

Jan.

Feb.

Mar.

Apr.

May

June

July

Aug^

Sept.

Oct.

Nov.

Dec.

106.0
103.6
104.6
125.3
125.4
135.4
138.3
151.1
147.1

125.0
109.9
107.7
119.4
125.1
139.7
135.5
153.0
157.9

108.4
139.3
112.5
109.3
111.0
122.6
141.4
129.9
152.9
175.3

114.7
146.8
115.7
111.4
115.1
123.2
144.4
136.3
152.4
176.1

113.3
134.7
116.4
112.9
116.8
122.7
143.0
141.2
151.0
178.1

102.0
117.5
116.3
113.9
120.3
122.9
140.9
152.8
151.3
174.2

96.4
100.8
116.3
116.0
121.9
125.8
140.2
155.0
148.6
177.9

90.8
97.7
118.6
116.3
124.5
129.6
139.3
146.5
144.6
171.6

93.8
98.6
112.8
119.6
126.3
128.8
142.7
135.2
145.6
165.5

89.6
98.7
107.4
126.0
125.5
127.7
143.5
131.7
147.7
161.7

89.2
98.1
100.5
131.4
125.3
126.1
145.5
145.3
146.9
159.8

90.2
99.5
102.5
135.3
126.2
130.5
144.8
155.4
140.1
159.7


https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis

SIC 30 - RUBBER AND MISCELLANEOUS PLASTIC PRODUCTS
(Seasonally Adjusted, 1957-59=100)

1960
1961
1962
1963
1964
1965
1966
1967
1968
1969

Jan.

Feb.

Mar.

Apr.

Mav

June

July

Aug.

Sept.

Oct.

Nov.

Dec.

112.6
131.8
139.3
159.4
179.8
229.4
249.4
273.2
318.0

115.0
132.1
146.7
156.6
186.7
232.2
249.3
274.6
326.5

116.2
131.5
151.7
157.7
192.7
233.3
246.0
281.0
326.3

118.5
130.5
155.1
159.2
199.9
236.8
247.1
283.8
336.8

122.5
130.5
154.5
161.5
208.7
237.7
227.8
288.6
340.5

116.3
125.8
131.2
156.7
162.1
220.1
237.8
234.9
298.1
348.4

117.5
127.8
131.6
164.5
163.4
218.8
240.7
231.3
295.6
354.1

116.0
128.1
131.4
154.2
171.3
223.9
239.5
254.5
298.2
351.4

114.8
129.8
134.0
156.9
175.5
222.4
241.8
257.6
301.8
359.2

113.8
129.9
135.2
159.8
173.5
223.9
243.0
260.8
305.2
363.8

112.6
131.4
139.0
158.2
174.8
226.2
244.7
265.1
312.6
369.6

110.3
131.8
140.7
159.6
174.3
230.1
243.8
266.0
318.4
379.7

SIC 31 - LEATHER AND LEATHER PRODUCTS
(Seasonally Adjusted, 1957-59=100)

1960
1961
1962
1963
1964
1965
1966
1967
1968
1969

Jan.

Feb.

Mar.

Apr.

May

June

July

Aug.

Sept.

Oct.

Nov.

Dec.

98.0
105.2
108.7
128.4
139.5
146.8
155.5
160.0
167.1

99.2
105.3
109.3
128.1
141.4
150.7
151.7
156.7
162.4

101.6
100.3
105.0
111.5
128.9
140.5
153.4
154.9
158.2
162.0

101.1
100.1
104.7
114.5
128.2
139.1
154.9
154.5
161.8
163.2

99.0
99.5
104.9
118.4
131.3
136.7
155.0
155.4
163.6
163.0

98.8
98.0
103.8
123.0
134.1
133.4
156.6
154.4
165.6
160.3

101.1
96.9
104.2
124.8
136.6
134.4
158.5
153.7
165.5
153.6

102.5
97.1
104.0
127.8
137.3
136.6
159.8
153.3
164.5
148.6

101.3
98.9
105.5
125.7
137.0
141.4
158.8
153.9
162.6
145.8

99.1
101.2
106.1
126.1
136.8
144.0
157.4
155.7
163.0
147.3

98.5
103.2
107.3
124.6
136.5
144.2
157.1
158.4
164.3
151.6

98.6
104.5
107.3
127.2
138.7
145.1
155.7
161.9
167.7
159.4


https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis

SIC 32 - STONE, CLAY, GLASS, AND CONCRETE PRODUCTS
(Seasonally Adjusted, 1957-59=100)

1960
1961
1962
1963
1964
1965
1966
1967
1968
1969

Jan.

Feb.

Mar.

Apr.

May

June

July

A«g-

Sept.

Oct.

Nov.

Dec.

120.9
120.8
118.5
143.6
146.2
164.1
163.5
149.2
155.1
166.5

117.3
118.8
133.3
140.7
153.7
164.5
160.2
148.7
156.0
174.0

110.6
115.9
136.9
144.7
154.3
163.7
159.7
150.7
153.8
167.9

121.2
115.2
136.7
146.5
154.3
165.7
160.3
150.0
156.0
163.6

114.9
115.1
138.0
148.8
154.6
167.3
154.3
149.1
159.0
164.0

115.7
115.6
140.3
150.2
155.0
166.4
152.8
150.7
163.0
166.6

115.3
117.8
141.3
151.3
154.2
168.7
152.1
150.5
162.2
169.5

115.4
123.0
142.7
151.7
155.0
167.8
151.7
152.7
161.5
167.4

112.7
123.8
143.9
152.9
152.5
165.1
151.9
152.9
163.3
168.0

118.3
119.1
144.4
154.0
156.6
165.2
150.4
153.6
163.1
170.2

116.6
125.4
143.2
152.8
159.7
165.3
149.3
155.6
160.4
167.2

116.5
129.0
140.0
150.5
160.9
167.4
149.2
157.3
167.0
171.5

SIC 33 - PRIMARY METAL INDUSTRIES
(Seasonally Adjusted, 1957-59=100)

1960
1961
1962
1963
1964
1965
1966
1967
1968
1969

Jan.

Feb.

Mar.

Apr.

May

June

July

Aug.

Sept.

Oct.

Nov.

Dec.

79.0
92.7
107.6
139.3
154.3
156.6
166.6
160.6
168.0

78.2
94.0
113.3
141.7
154.5
157.7
157.8
162.2
170.7

84.7
78.1
93.5
121.4
147.6
153.8
159.1
157.2
164.7
172.8

85.0
76.8
92.8
123.1
144.6
155.2
159.8
153.6
164.8
168.9

84.6
80.6
92.5
126.0
147.0
153.5
162.6
156.4
165.0
173.4

83.4
83.7
94.6
127.6
148.9
153.8
163.9
157.2
158.1
174.9

83.4
88.4
94.1
128.5
149.4
156.8
165.0
159.2
151.1
176.2

81.8
91.1
95.3
129.6
152.0
157.2
168.2
157.9
143.6
176.6

80.7
92.3
97.5
130.4
155.4
153.4
169.1
157.8
152.0
178.2

80.7
94.1
99.7
131.1
155.9
153.5
170.9
156.4
156.7
183.5

79.9
95.2
101.0
133.2
156.4
152.0
172.7
158.7
160.9
188.9

79.2
95.6
100.4
133.9
155.1
154.1
169.8
159.7
164.9
196.7


https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis

SIC 34 - FABRICATED METAL PRODUCTS
(Seasonally Adjusted, 1957-59=100)

1960
1961
1962
1963
1964
1965
1966
1967
1968
1969

Jan.

Feb.

Mar.

Apr.

May

113.2
116.4
129.7
150.8
163.6
186.3
206.1
208.2
234.3

113.5
117.5
131.7
150.2
163.1
190.1
208.0
209.6
234.1

112.0
111.8
118.2
134.9
151.5
161.5
193.7
210.6
218.4
234.1

109.1
109.6
123.4
138.1
151.0
161.5
195.7
207.2
216.6
233.4

108.3
108.2
122.4
138.8
153.0
161.4
197.9
205.0
217.0
233.0

June

Jul^

Aug.

Sept.

Oct.

Nov.

Dec.

108.7
107.7
120.9
142.6
155.5
169.8
200.6
202.7
216.7
232.9

111.6
108.6
120.5
144.4
157.4
170.1
201.7
202.9
218.4
232.9

111.6
110.1
118.9
146.8
156.5
173.0
202.4
204.7
220.4
236.0

112.8
113.0
127.7
147.8
155.8
169.7
203.0
209.0
221.8
239.9

110.4
114.9
128.1
146.9
158.4
173.8
203.8
210.0
225.0
243.6

109.2
115.7
131.1
148.8
160.7
177.1
203.3
211.0
228.4
244.4

109.7
116.7
125.0
149.4
162.4
182.6
203.3
207.7
233.9
246.8

SIC 35 - MACHINERY, EXCEPT ELECTRICAL
(Seasonally Adjusted, 1957-59=100)

1960
1961
1962
1963
1964
1965
1966
1967
1968
1969

Jan.

Feb.

Mar.

Apr.

May

June

July

Aug.

Sept.

Oct.

Nov.

Dec.

133.7
120.7
133.1
172.1
190.6
211.1
232.7
272.3
286.6
339.7

134.9
120.6
136.5
175.9
187.8
217.7
241.3
272.2
295.9
344.0

136.4
115.0
137.7
177.3
192.1
220.9
247.2
254.9
296.6
339.4

135.8
122.6
144.8
178.0
190.0
224.6
251.3
271.3
300.5
343.6

133.1
125.0
146.2
182.4
190.1
227.6
248.7
273.2
312.9
347.1

133.6
127.7
149.1
176.5
198.2
222.6
256.4
273.8
313.1
356.2

138.1
126.6
151.2
180.1
207.1
240.3
252.5
279.4
322.0
371.5

125.6
130.8
155.5
179.4
200.9
236.0
263.5
276.9
323.4
392.8

129.5
129.9
153.3
186.3
204.7
236.7
261.5
280.4
325.3
384.0

128.3
132.1
156.7
186.1
206.1
241.2
260.1
283.2
332.6
375.6

130.2
135.7
157.0
190.2
203.9
246.9
266.5
281.6
336.8
371.1

125.7
134.2
155.3
189.0
210.7
245.0
267.8
282.6
338.2
361.0


https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis

SIC 36 - ELECTRICAL MACHINERY
(Seasonally Adjusted, 1957-59=100)

1960
1961
1962
1963
1964
1965
1966
1967
1968
1969

Jan.

Feb.

Mar.

Apr.

May

134.9
128.0
187.5
185.2
225.0
259.7
333.5
398.4
429.4
474.8

137.1
131.5
197.7
185.5
225.8
262.3
345.7
396.8
436.5
496.2

139.7
132.2
192.6
190.0
222.4
267.8
358.6
393.9
442.1
497.7

138.0
132.9
187.5
207.0
228.1
268.9
373.4
389.2
446.5
503.1

130.7
136.8
192.0
200.3
230.6
266.5
389.8
385.7
452.2
526.5

June

July

Aug-

Sept.

Oct.

Nov.

Dec.

125.7
138.3
200.3
206.8
236.3
265.2
401.7
383.5
460.3
536.2

123.9
146.4
187.8
208.7
240.5
278.3
394.8
390.1
462.9
558.6

114.5
148.6
175.2
217.9
239.7
296.1
390.1
390.3
493.0
585.1

119.3
150.0
185.3
229.3
241.9
300.7
388.1
393.6
488.1
588.5

117.3 •
158.1
204.4
227.1
245.4
309.6
389.9
401.5
482.2
582.5

111.3
155.4
190.3
231.1
245.8
316.0
391.2
409.0
470.9
571.1

113.0
160.2
184.9
231.8
251.3
325.0
395.4
419.6
476.3
558.4

SIC 37 - TRANSPORTATION EQUIPMENT
(Seasonally Adjusted, 1957-59=100)

Jan.
1960
1961
1962
1963
1964
1965
1966
1967
1968
1969

85.0
103.9
142.8
178.4
195.8
238.9
241.1
277.2
314.5


https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis

Feb.

Mar.

Apr.

May

June

July

Aug.

Sept.

Oct.

Nov.

Dec.

84.5
108.1
144.6
179.5
203.6
239.1
264.4
281.9
326.4

96.7
83.7
111.2
147.4
186.1
205.5
246.4
250.6
281.5
335.8

98.0
85.8
112.7
149.2
184.3
214.7
245.5
256.1
263.8
329.9

96.1
85.2
114.3
155.5
186.6
216.7
246.4
263.2
288.9
332.4

100.7
84.2
121.5
155.2
192.1
216.7
242.6
268.7
301.1
333.0

100.7
86.6
122.6
157.4
195.3
221.2
250.6
264.4
304.4
338.5

103.2
89.6
127.8
159.9
186.8
227.7
248.7
270.4
307.3
365.6

97.2
90.1
129.3
163.6
192.3
216.7
257.5
273.0
301.3
353.2

104.8
89.8
132.4
168.0
190.7
232.0
267.7
270.5
318.7
366.7

100.5
97.7
133.2
170.1
193.7
241.4
251.6
274.4
325.1
369.7

95.1
100.9
131.7
169.9
206.1
240.2
257.9
273.9
322.2
353.4

TOTAL NONDURABLE GOODS INDUSTRIES
(Seasonally Adjusted, 1957-59=100)

1960
1961
1962
1963
1964
1965
1966
1967
1968
1969

Jan.

Feb.

Mar.

Apr.

May

114.4
120.3
127.9
139.5
152.3
166.3
174.6
178.3
190.2

114.9
122.7
128.7
140.4
153.1
168.9
174.3
180.6
191.9

114.8
123.4
130.1
140.8
154.6
168.5
174.8
182.1
192.9

115.2
123.9
131.4
141.7
156.2
169.4
175.2
182.5
194.4

115.9
124.3
132.1
141.4
157.1
169.0
175.0
184.6
195.9

June

July

Aug.

Sept.

Oct.

Nov.

Dec.

113.6
116.6
125.5
133.0
143.7
158.4
169.6
177.2
186.8
198.7

114.4
117.5
126.4
134.9
145.4
158.4
170.9
176.6
186.9
201.0

114.0
118.3
126.5
133.9
146.6
160.0
171.6
177.0
188.3
200.8

113.7
119.1
127.2
134.7
146.9
160.7
172.5
177.5
188.8
202.8

113.3
119.7
127.6
136.4
147.9
162.3
173.0
177.6
189.6
210.7

113.0
120.4
128.3
136.9
149.6
163.5
173.5
178.0
190.7
212.0

112.9
121.5
128.2
138.6
150.9
165.1
173.8
178.8
191.8
213.0

TOTAL DURABLE GOODS INDUSTRIES
(Seasonally Adjusted, 1957-59=100)

Jan.
1960
1961
1962
1963
1964
1965
1966
1967
1968
1969

101.5
115.6
137.1
161.5
178.2
201.5
215.7
225.8
252.4


https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis

Feb.

101.0
121.4
139.1
160.4
180.5
203.8
218.3
230.0
259.3

Mar.

Apr.

99.7
122.0
143.0
165.9
181.6
207.9
214.1
232.1
260.0

100.2
122.7
146.7
165.3
184.9
210.4
214.6
229.5
259.1

May

June

July

Aug.

Sept.

Oct.

Nov.

Dec.

101.3
124.1
148.9
166.9
185.1
212.1
215.5
237.5
263.0

105.6
102.4
127.2
150.3
168.8
185.4
213.9
216.6
240.5
266.0

106.3
105.2
126.5
152.1
171.5
190.5
214.8
217.1
241.5
271.0

104.4
108.1
126.8
154.2
172.0
193.7
215.6
218.4
244.0
281.5

103.4
109.2
129.9
157.3
170.9
190.5
217.7
220.1
244.3
279.5

104.8
110.4
133.4
158.4
173.7
195.8
220.0
220.6
249.1
282.4

102.9
113.3
129.8
160.1
175.0
199.4
217.5
223.0
250.8
282.1

101.2
114.9
130.3
159.9
178.5
201.5
218.6
224.3
253.3
278.7

TOTAL MANUFACTURING
(Seasonally Adjusted, 1957-59=100)

1960
1961
1962
1963
1964
1965
1966
1967
1968
1969

Jan.

Feb.

Mar.

Apr.

May

June

July

Aug.

Sept.

Oct.

Nov.

Dec.

108.3
118.2
132.1
149.5
164.0
182.4
193.1
200.0
218.5

108.4
122.1
133.6
150.8
165.7
183.8
194.3
203.2
222.3

107.9
122.8
136.0
152.1
166.7
185.8
192.8
204.9
223.4

108.2
123.4
138.4
152.4
169.0
187.9
193.1
203.9
223.8

109.3
124.2
139.7
152.9
169.7
188.7
193.4
208.5
226.4

109.9
110.3
126.2
140.9
155.6
170.4
189.7
195.0
211.3
229.3

110.6
112.0
126.5
142.0
157.4
173.0
190.7
194.9
211.5
232.8

109.6
113.6
126.6
143.2
157.3
175.3
191.6
196.0
213.6
237.6

108.8
114.5
128.5
145.1
158.5
174.1
193.0
197.0
214.1
237.9

109.4
115.3
130.3
146.2
159.2
177.5
194.0
197.2
216.6
239.6

108.5
117.0
130.1
147.6
161.0
179.8
193.5
198.5
217.8
243.9

107.4
118.3
129.0
148.2
163.4
181.6
194.3
199.4
219.7
242.7


https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis

i
NJ

I

PRODUCTION INDEX
SIXTH FEDERAL RESERVE DISTRICT STATES
SIC 20 - FOOD AND KINDRED PRODUCTS
(Seasonally Unadjusted, 1957-59=100)

APPENDIX C

Jan.
1960
1961
1962
1963
1964
1965
1966
1967
1968
1969

111.7
113.3
123.2
129.2
137.7
141.4
143.3
144.6
149.7

Feb.

110.5
113.6
121.6
128.1
136.5
140.2
141.5
143.2
148.5

Mar.

110.1
113.1
120.0
125.1
134.7
139.2
141.2
141.0
146.9

Apr.

108.8
112.2
119.3
124.9
134.9
136.9
141.8
140.7
146.9

May

June

July

Aug.

Sept.

Oct.

Nov.

Dec.

111.3
114.8
119.2
125.6
135.0
137.6
143.2
143.4
148.9

109.3
113.8
118.2
120.3
128.1
136.0
138.6
148.3
147.8
153.5

112.0
113.7
120.7
120.4
130.9
136.6
140.7
150.2
150.1
158.6

112.0
114.0
120.3
121.8
133.6
137.7
141.7
151.1
152.7
160.1

113'7
115.4
122.8
126.5
136.0
138.7
143.8
152.8
155.5
162.3

114.7
116.8
125.8
129.6
137.1
141.0
144.6
152.3
157.0
164.0

114.6
116.5
126.3
130.9
140.1
142.4
145.8
151.6
157.4
165.5

113.2
114.7
123.2
130.9
139.8
140.9
144.1
148.9
155.8
163.8
-o
w
i

SIC 21 - TOBACCO MANUFACTURES
(Seasonally Unadjusted, 1957-59=100)

Jan.

1960
1961
1962
1963
1964
1965
1966
1967
1968
1969


https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis

105.5
100.2
102.3
98.3
98.3
95.3
96.8
84.2
83.8

Feb.
91.7
90.0
87.0
86.5
90.5
84.4
85.1
83.4
83.1
74.5

Mar.
92.7
82.7
80.9
78.6
86.7
78.0
82.8
79.4
76. 7
71.7

Apr.

90.7
79.9
77.4
76.5
87.8
75.4
80.6
78.9
74.9
70.1

May
89.1
79.4
72.3
74.9
84.4
75.1
78.8
79.6
74.0
69.3

June
86.5
80.4
71.0
73.2
82.3
74.1
79.0
75.6
74.1
69.1

July
87.8
83.6
73.2
76.9
80.6
75.9
79.2
76.2
74.8
69.6

Aug.
93.4
89.0
77.9
75.5
80.8
77.8
81.0
78.3
74.4
71.0

Sept.

Oct.

Nov.

Dec.

101.3
94.2
82.7
80.8
84.8
81.8
83.3
85.6
77.4
73.5

105.1
94.2
84.6
82.2
85.6
82.5
85.2
87.6
79.4
75.7

113.6
103.3
98.7
93.7
98.4
93.1
96.5
86.0
88.1
86.3

111.0
102.2
103.4
97.5
99.6
93.9
98.0
86.4
87.0
94.5

SIC 22 - TEXTILE MILL PRODUCTS
(Seasonally Unadjusted, 1957-59=100)

Jan.
1960
1961
1962
1963
1964
1965
1966
1967
1968
1969

113.1
127.0
125.2
136.2
158.8
181.9
190.3
199.1
215.9

Feb.

Mar.

113.3
130.2
124.7
139.2
161.9
182.6
188.5
203.3
216.5

113.6
130.3
123.8
140.8
162.5
181.7
185.0
202.9
216.5

Apr.

113.9
129.4
124.4
142.8
164.2
181.9
183.0
200.8
216.6

May

June

July

Aug.

Sept.

Oct.

Nov.

Dec.

115.6
129.5
124.7
140.6
165.9
183.2
184.3
202.9
219.2

115.9
116.6
130.6
126.8
150.2
170.5
184.6
187.6
208.5
224.7

114.0
118.2
128.5
125.8
150.1
169.0
185.1
184.2
206.2
223.8

114.0
121.8
131.1
128.5
151.3
174.2
189.4
188.4
212.1
229.6

113.1
124.2
130.5
130.5
151.6
176.2
192.7
192.7
215.1
233.9

112.4
126.1
130.3
133.2
156.7
179.1
193.3
195.9
216.8
232.8

111.9
126.3
129.7
134.0
157.7
181.2
193.5
198.6
219.3
233.7

110.3
125.9
127.2
134.3
157.8
182.3
192.9
200.6
219.5
232.8
i
-o
-P'

SIC 23 - APPAREL AND OTHER FINISHED PRODUCTS
(Seasonally Unadjusted, 1957-59=100)

1960
1961
1962
1963
1964
1965
1966
1967
1968
1969

Jan.

Feb.

Mar.

Apr.

May

June

July

Aug.

Sept.

Oct.

Nov.

Dec.

118.1
127.8
152.7
182.3
196.9
211.5
218.8
219.2
243.4

119.4
132.9
152.2
177.6
187.4
203.0
209.9
218.7
235.9

111.0
129.1
152.1
169.8
180.5
193.5
201.2
213.4
226.7

109.6
126.1
153.5
165.3
178.0
192.6
200.8
211.2
223.6

110.4
128.1
162.0
165.8
181.3
189.7
205.4
217.5
227.2

110.2
114.8
133.7
171.7
172.4
188.1
197.0
216.1
227.8
237.9

113.2
119.8
138.3
177.5
179.5
193.8
202.9
219.5
233.0
246.3

119.5
129.1
147.3
189.6
191.0
209.3
217.1
226.9
245.5
256.4

123.4
134.8
154.1
195.0
196.1
217.7
225.1
233.3
253.6
270.1

124.0
138.7
158.5
197.4
202.2
224.3
231.2
236.7
259.3
275.3

124.4
141.8
159.9
197.6
204.2
224.2
230.1
236.3
259.2
277.0

119.5
139.7
155.8
192.5
199.5
219.3
226.4
230.9
252.8
268.6


https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis

SIC 24 - LUMBER AND WOOD PRODUCTS
(Seasonally Unadjusted, 1957-59=100)

1960
1961
1962
1963
1964
1965
1966
1967
1968
1969

Jan.

Feb.

Mar.

Apr.

May

June

July

Aug.

Sept.

Oct.

Nov.

Dec

93.9
96.1
112.6
124.4
127.6
136.2
143.1
132.6
158.6

93.4
103.0
115.0
126.7
124.8
134.7
137.8
139.7
158.4

92.5
103.4
117.0
127.2
127.5
136.9
138.6
143.3
155.3

93.9
104.7
120.6
127.8
129.8
139.4
137.3
145.2
162.9

96.2
107.0
123.3
128.7
130.3
141.4
135.3
149.6
163.8

102.2
98.8
105.8
126.8
129.3
129.1
141.5
134.2
152.9
166.9

101.0
98.4
105.6
126.2
128.3
129.9
141.5
130.2
156.1
165.9

99.5
101.0
105.6
128.3
127.8
131.7
143.7
134.2
157.3
168.3

99.0
102.0
107.5
128.1
125.6
130.8
144.7
135.5
157.4
168.5

97.1
102.1
108.3
129.4
126.6
134.2
145.3
136.3
157.8
169.0

96.6
101.8
108.9
129.5
129.2
135.4
144.5
136.2
158.3
167.8

93
99
107
128
127
137
145
137
159
168

i
-P'

SIC 25 - FURNITURE AND FIXTURES
(Seasonally Unadjusted, 1957-59=100)

1960
1961
1962
1963
1964
1965
1966
1967
1968
1969

Jan.

Feb.

Mar.

APr-

May

June

July

Aug.

Sept.

Oct.

Nov.

Dec

101.8
106.3
127.0
146.5
162.1
179.7
185.3
180.3
198.6

100.4
113.7
129.3
148.5
164.8
181.5
185.2
185.1
200.5

98.7
115.2
130.5
147.2
166.4
181.0
183.5
186.7
199.9

97.5
115.0
130.7
146.2
166.5
179.7
180.1
183.7
199.6

95.9
116.4
131.6
145.8
167.6
177.9
180.0
187.5
194.8

101.9
96.5
118.8
133.4
145.0
168.0
179.4
179.7
190.6
195.7

101.9
98.1
118.3
132.9
142.3
167.2
176.7
178.4
187.7
187.5

104.3
101.7
121.3
137.3
147.1
171.7
181.8
177.9
192.5
194.0

105.3
105.6
125.2
140.1
150.6
173.6
183.7
178.4
193.7
193.8

105.8
107.1
125.8
143.0
154.7
176.2
185.7
177.9
195.4
193.0

104.0
109.2
126.5
144.3
156.6
178.9
187.2
180.6
196.6
192.2

103
111
126
145
160
181
187
185
200
189


https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis

SIC 26 - PAPER AND ALLIED PRODUCTS
(Seasonally Unadjusted, 1957-59=100)

1960
1961
1962
1963
1964
1965
1966
1967
1968
1969

Jan.

Feb.

Mar.

Apr.

May

June

July

Aug.

Sept.

Oct.

Nov.

Dec.

120.3
124.0
128.3
129.4
143.4
158.5
171.4
174.3
181.6

117.9
123.4
128.0
130.9
143.4
159.2
171.1
174.2
183.1

120.1
125.0
128.6
133.7
146.0
163.6
173.5
175.5
185.6

120.3
126.4
125.3
134.8
145.9
166.4
170.4
175.4
188.3

121.4
127.2
125.0
136.8
147.5
167.7
170.3
177.0
193.0

120.3
123.6
130.3
124.9
139.7
150.9
172.3
173.5
178.4
197.5

119.7
124.1
129.9
124.5
140.8
151.2
173.7
173.3
178.9
198.7

121.9
126.6
132.5
125.6
141.6
152.0
173.7
173.6
180.0
199.2

119.7
125.1
131.2
121.2
141.2
152.4
173.1
173.6
178.8
200.1

120.7
126.3
132.3
126.2
142.0
153.7
174.2
173.9
178.8
201.0

119.1
126.2
132.0
126.2
141.8
154.4
174.2
173.8
179.0
200.0

117.9
125.7
132.0
125.9
142.1
155.6
171.7
173.7
179.7
201.5

i
-o
SIC 27 - PRINTING, PUBLISHING, AND ALLIED INDUSTRIES
(Seasonally Unadjusted, 1957-59=100)

1960
1961
1962
1963
1964
1965
1966
1967
1968
1969

Jan.

Feb.

Mar.

Apr.

May

June

July

Aug.

Sept-

Oct.

Nov.

Dec.

115.5
114.6
113.4
127.2
133.0
151.7
165.2
165.2
167.5

109.6
111.1
108.4
122.2
130.5
147.1
159.7
159.8
162.3

106.6
107.4
104.6
118.6
127.6
145.1
155.7
156.3
157.3

101.3
105.5
105.6
117.0
127.8
143.0
154.9
155.2
154.9

101.0
107.0
109.7
117.3
130.6
144.7
156.9
156.3
154.7

106.0
102.1
107.9
112.0
119.6
133.8
148.1
157.7
160.0
158.5

111.3
105.8
113.0
116.7
124.9
138.6
154.2
162.5
163.7
164.4

116.3
111.0
118.8
122.5
130.5
144.5
160.6
166.3
170.4
171.0

120.7
115.8
122.2
129.1
135.3
151.3
166.1
169.8
175.2
176.4

123.9
118.6
122.7
131.2
137.9
155.5
170.6
172.0
177.1
179.1

123.9
118.8
120.8
131.5
138.3
156.1
172.0
171.3
177.2
180.7

121.0
120.2
118.6
130.7
137.9
155.4
171.0
170.7
175.4
179.1


https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis

SIC 28 - CHEMICALS AND ALLIED PRODUCTS
(Seasonally Unadjusted, 1957-59=100)

1960
1961
1962
1963
1964
1965
1966
1967
1968
1969

Jan.

Feb.

Mar.

Apr.

May

June

July

Aug.

Sept.

Oct.

Nov.

Dec

123.9
132.9
147.3
170.9
170.7
196.2
214.8
231.2
250.0

122.6
127.4
144.2
168.3
172.0
194.2
214.7
230.7
248.2

111.4
122.8
124.0
147.4
167.6
176.0
193.4
216.8
231.9
248.1

113.3
123.3
125.8
149.3
169.6
180.5
197.0
217.2
235.0
252.1

114.6
128.3
130.8
154.8
172.7
183.7
203.3
221.0
238.1
257.0

112.7
129.5
131.0
153.0
173.0
186.0
205.4
224.9
240.1
257.1

110.2
126.4
132.7
154.2
170.4
187.0
207.0
228.7
240.5
258.6

109.2
122.2
132.3
152.8
168.3
188.1
208.1
229.8
240.8
257.2

110,3
120.4
135.8
153.4
168.0
187.8
208.6
229.5
245.7
261.5

115.4
123.7
140.7
156.2
168.7
190.0
208.4
230.3
249.6
263.1

118.3
128.4
144.8
162.9
168.5
190.5
208.6
231.3
250.9
263.4

122
134
147
169
169
195
210
233
252
262.

i
SIC 29 - PETROLEUM REFINING AND RELATED INDUSTRIES
(Seasonally Unadjusted, 1957-59=100)

1960
1961
1962
1963
1964
1965
1966
1967
1968
1969


https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis

1

Jan.

Feb.

Mar.

Apr.

May

June

July

Aug.

Sept.

Oct.

Nov.

Dec

104.0
102.0
103.4
124.1
124.6
134.7
137.5
150.2
146.2

121.2
106.7
104.8
116.0
121.4
135.3
131.1
148.0
152.9

108.5
139.4
112.2
108.2
108.7
119.0
136.2
124.6
146.5
167.8

113.0
144.6
113.5
108.5
111.1
117.8
137.3
129.3
144.6
167.1

113.8
135.3
116.5
112.3
115.4
120.5
140.0
138.2
147.9
174.5

104.6
120.4
118.8
115.6
121.3
123.5
141.5
153.6
152.3
175.4

98.9
103.4
119.2
118.6
124.5
128.5
143.4
158.7
152.2
182.4

92.3
99.3
120.9
119.3
128.2
133.7
143.7
150.9
148.7
176.2

94.8
99.7
114.4
122.1
129.6
132.8
147.6
139.9
150.4
170.9

90.5
99.7
108.8
128.3
128.4
131.2
147.9
135.9
152.4
166.9

89.1
98.0
100.6
132.4
127.0
128.4
148.5
148.4
150.1
165.9

87
96
100
133
125
130
145
156
140
163

SIC 30 - RUBBER AND MISCELLANEOUS PLASTIC PRODUCTS
(Seasonally Unadjusted, 1957-59=100)

1960
1961
1962
1963
1964
1965
1966
1967
1968
1969

Jan.

Feb.

Mar.

Apr.

May

June

July

Aug.

Sept.

Oct.

Nov.

Dec.

113.4
132.8
140.3
160.5
181.6
232.5
253.3
277.9
323.7

114.6
131.7
146.2
156.1
186.6
232.9
250.6
276.5
329.1

116.5
131.7
151.8
157.7
192.7
233.5
246.3
281.5
326.9

118.3
130.2
154.7
158.6
198.6
234.4
243.7
279.5
331.4

122.2
130.3
154.3
161.0
207.5
235.6
224.9
284.2
335.1

116.5
126.1
131.4
156.5
161.2
217.9
234.6
231.2
293.0
342.1

116.0
126.1
129.8
162.1
160.7
214.6
235.4
225.6
288.1
344.9

115.5
127.6
131.2
154.4
171.8
224.7
240.3
255.0
298.3
351.4

114.3
129.2
133.5
156.6
175.6
223.3
243.5
260.1
305.1
363.2

115.2
131.4
136.8
161.8
175.8
226.9
246.3
264.2
309.1
368.5

112.6
131.4
139.1
158.5
175.4
227.7
247.4
268.9
317.6
375.5

110/
132/
141/
160/
175.:
231/
245/
267/
319/
381/
I

oo
I
SIC 31 - LEATHER AND LEATHER PRODUCTS
(Seasonally Unadjusted, 1957-59=100)

1960
1961
1962
1963
1964
1965
1966
1967
1968
1969

Jan.

Feb.

Mar.

Apr.

May

June

July

Aug.

Sept.

99.5
106.8
110.3
129.9
140.8
147.9
156.2
160.6
167.6

99.6
105.9
110.2
129.4
143.1
152.8
153.8
158.9
164.7

99.4
98.1
102.8
109.3
126.6
138.4
151.4
152.9
156.2
160.1

96.6
95.5
100.1
109.6
123.1
134.0
149.8
149.7
157.0
158.5

95.5
96.0
101.2
114.0
126.2
131.3
149.0
149.5
157.4
157.0

98.0
97.2
102.8
121.6
132.1
131.1
153.6
151.3
162.2
156.9

102.8
98.5
105.9
126.7
138.4
135.9
159.9
154.8
166.6
154.5

105.0
99.5
106.5
131.0
140.8
140.1
163.7
156.9
168.2
151.9

103.8
101.4
108.3
129.2
140.9
145.3
163.0
157.6
166.3
149.0


https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis

Oct.
100.5
102.6
107.6
128.0
138.9
146.1
159.8
158.0
165.2
149.2

Nov.
98.9
103.6
107.6
125.0
136.9
144.8
158.3
160.1
166.2
153.4

Dec.

99
105
107
127
138
145
156
162
168
159

SIC 32 - STONE, CLAY, GLASS, AND CONCRETE PRODUCTS
(Seasonally Unadjusted, 1957-59=100)

1960
1961
1962
1963
1964
1965
1966
1967
1968
1969

Jan.

Feb.

Mar.

Apr.

May

June

Jul^

Aug.

Sept.

Oct.

Nov.

Dec.

113.6
113.6
111.6
135.6
138.4
156.0
156.0
142.4
148.1
159.0

111.5
113.0
126.9
133.8
145.9
156.0
151.7
140.5
147.3
164.1

107.5
112.6
133.1
140.8
150.2
159.6
155.8
147.0
150.0
163.7

120.7
114.7
136.3
146.2
154.1
165.6
160.1
149.7
155.6
163.1

118.6
118.8
142.4
153.3
158.8
171.1
157.3
151.5
161.2
166.1

121.3
121.1
146.9
156.9
161.5
173.0
158.5
156.1
168.7
172.4

120.1
122.7
147.1
157.4
160.2
175.0
157.7
155.9
167.9
175.4

119.4
127.3
147.7
157.0
160.4
173.6
156.9
157.9
166.9
172.9

115.3
126.6
146.9
155.8
155.0
167.6
154.2
155.4
166.1
170.9

119.2
120.1
145.4
154.9
157.1
165.3
150.3
153.4
162.9
170.0

115.9
124.6
142.4
152.4
159.6
165.6
149.9
156.3
161.1
168.0

111.6
123.5
134.3
145.1
156.0
163.4
146.8
155.5
165.3
170.0
I

SIC 33 - PRIMARY METAL INDUSTRIES
(Seasonally Unadjusted, 1957-59=100)

1960
1961
1962
1963
1964
1965
1966
1967
1968
1969


https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis

Jan.

Feb.

Mar.

Apr.

May

June

July

Aug.

Sept.

Oct.

Nov.

Dec.

77.7
91.3
106.1
137.5
152.8
155.6
165.8
160.0
167.3

78.2
94.0
113.3
141.4
154.0
156.9
156.6
160.7
169.0

85.9
79.2
94.8
122.8
148.7
154.3
159.0
156.5
163.7
171.6

88.1
79.6
96.2
127.4
149.2
159.5
163.5
156.6
167.6
171.6

87.3
83.2
95.4
129.9
151.2
157.6
166.6
160.0
168.7
177.2

86.3
86.6
97.8
131.7
153.2
157.7
167.5
160.3
161.1
178.0

84.6
89.6
95.4
130.1
151.2
158.3
166.5
160.4
152.1
177.4

81.8
91.1
95.3
129.6
152.1
157.3
168.5
158.2
143.9
177.0

79.8
91.3
96.4
129.1
153.9
152.0
167.5
156.2
150.4
176.2

78.2
91.2
96.7
127.5
151.8
149.7
166.9
153.0
153.2
179.5

76.3
90.9
96.6
128.0
151.1
148.0
169.3
156.3
158.8
186.4

76.8
92.8
97.6
130.7
152.1
152.0
168.6
159.2
164.6
196.3

SIC 34 - FABRICATED METAL PRODUCTS
(Seasonally Unadjusted, 1957-59=100)

1960
1961
1962
1963
1964
1965
1966
1967
1968
1969

Jan.

Feb.

Mar.

Apr.

May

June

July

Aug.

Sept.

Oct.

Nov.

Dec.

110.2
113.6
127.1
148.3
161.5
184.5
204.1
206.2
232.2

109.4
113.4
127.4
145.7
159.0
186.3
204.3
206.2
230.4

107.3
107.1
113.3
129.4
145.5
155.6
187.3
204.1
212.0
227.3

106.5
106.9
120.3
134.4
146.8
157.2
191.0
202.7
212.3
229.0

108.0
107.9
122.0
138.2
152.0
160.2
196.3
203.4
215.3
231.1

111.5
110.5
124.1
146.4
159.5
173.9
204.8
206.3
220.2
236.4

113.6
110.6
123.0
147.8
161.6
174.9
207.5
208.4
224.0
238.7

114.6
113.1
122.2
151.0
161.0
178.0
208.2
210.4
226.4
242.4

113,9
114.1
128.8
148.9
156.9
170.8
204.6
210.8
223.8
242.1

112.7
117.3
130.5
149.2
160.1
175.0
204.9
211.2
226.2
244.8

110.8
117.4
132.8
150.4
161.8
177.8
203.8
211.3
228.6
244.6

110.8
117.9
126.2
150.6
163.1
182.7
203.1
207.1
232.9
245.6
i
tn
O
I

SIC 35 - MACHINERY, EXCEPT ELECTRICAL
(Seasonally Unadjusted, 1957-59=100)

1960
1961
1962
1963
1964
1965
1966
1967
1968
1969


https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis

Jan.

Feb.

Mar.

Apr.

May

June

July

Au8-

Sept.

Oct.

Nov.

Dec.

131.0
118.2
130.4
168.4
186.1
205.8
226.6
264.3
277.9
329.2

136.1
121.7
137.6
176.9
188.2
217.7
241.2
271.8
295.6
343.7

134.2
113.2
135.7
175.0
189.5
217.9
243.4
250.2
290.7
332.3

137.8
124.4
146.8
180.1
191.5
225.5
251.4
270.7
299.6
342.6

136.4
128.1
149.5
185.6
192.5
229.4
250.1
274.4
314.3
348.8

137.5
131.4
153.5
181.8
204.1
229.5
264.4
282.4
322.9
367.2

131.9
120.9
144.7
172.9
199.8
233.0
246.0
272.9
314.7
363.3

129.8
135.1
160.4
184.8
206.4
242.0
270.0
284.0
331.7
403.0

131.8
132.3
156.3
190.5
210.0
243.3
269.0
288.2
334.3
394.4

127.5
131.2
156.0
185.9
206.5
242.5
262.5
286.3
336.1
379.7

127.1
132.4
153.3
186.2
200.4
243.4
264.2
279.8
335.1
369.2

123.6
131.9
152.9
186.5
207.9
241.4
263.6
277.6
331.4
353.8

SIC 36 - ELECTRICAL MACHINERY
(Seasonally Unadjusted, 1957-59= 100)

1960
1961
1962
1963
1964
1965
1966
1967
1968
1969

Jan.

Feb.

Mar.

Apr.

May

June

JulX

Au8-

Sept.

Oct.

Nov.

Dec.

130.7
124.0
181.8
179.7
218.6
253.3
326.8
391.5
423.0
468.2

134.5
129.0
193.9
181.6
220.7
256.8
339.5
390.7
430.6
489.8

137.5
130.0
189.3
186.6
218.3
263.3
353.8
389.9
438.7
494.7

134.3
129.3
182.9
202.7
224.7
266.7
372.4
389.1
447.1
504.1

132.0
138.1
193.6
201.7
231.8
267.8
391.8
388.2
455.8
531.2

126.2
138.8
201.3
208.3
238.5
268.1
406.0
387.3
464.6
541.0

123.5
145.9
187.3
208.1
239.9
278.0
394.8
390.4
463.1
558.6

116.1
150.7
177.7
221.1
243.0
299.6
394.4
394.1
497.3
589.8

121.1
152.3
188.3
233.4
246.4
305.9
394.0
398.5
493.5
594.4

120.5
162.3
209.8
232.6
250.2
313.9
393.5
403.6
483.5
584.3

115.0
160.6
196.1
237.2
250.3
319.2
392.9
409.4
470.8
570.5

112.2
159.0
183.5
230.1
249.4
322.2
392.2
415.9
472.3
553.9
l_n

H*
I

SIC 37 - TRANSPORTATION EQUIPMENT
(Seasonally Unadjusted, 1957-59=100)

1960
1961
1962
1963
1964
1965
1966
1967
1968
1969

Jan.

Feb.

Mar.

Apr.

May

June

July

Aug.

Sept.

Oct.

Nov.

Dec.

85.5
104.3
142.4
176.3
191.9
232.3
232.8
266.9
302.2

87.6
112.0
149.4
184.5
208.2
243.5
268.3
285.5
330.3

95.1
82.2
109.2
144.4
181.1
198.5
235.7
237.9
266.1
317.0

98.8
86.5
113.6
150.2
185.0
214.8
245.1
255.0
262.3
327.6

97.2
86.2
115.6
157.1
188.6
218.5
248.1
264.1
289.7
333.4

103.5
86.6
124.8
159.4
196.9
222.2
248.7
275.6
308.9
341.7

101.7
87.5
124.0
159.7
198.7
225.8
256.4
271.0
312.1
347.0

104.2
90.5
129.1
161.4
188.7
230.3
252.6
275.4
313.4
373.3

96.7
89.7
129.1
164.6
195.2
221.7
264.6
280.9
310.3
353.5

102.7
88.0
129.8
165.1
187.9
229.4
265.8
269.5
317.9
366.0

97.7
95.0
129.8
166.5
190.6
239.0
251.1
274.9
326.0
370.8

91.4
97.0
127.0
164.7
200.7
234.8
253.0
268.9
316.0
346.7


https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis

TOTAL NONDURABLE GOODS INDUSTRIES
(Seasonally Unadjusted, 1957-59=100)

Jan.

1960
1961
1962
1963
1964
1965
1966
1967
1968
1969

116.5
122.4
130.5
141.8
154.8
169.6
184.5
178.9
191.2

Feb.

115.3
123.2
129.4
140.6
153.6
168.0
172.0
178.5
189.6

Mar.

114.2
122.3
128.7
139.1
152.5
166.7
169.8
177.1
187.6

APr-

113.1
121.4
128.5
138.5
152.8
166.3
168.8
176.1
187.6

May

June

July

Au£-

Sept.

Oct.

Nov.

Dec.

114.9
123.3
130.3
139.2
154.7
166.7
169.4
178.7
190.1

113.8
116.1
126.1
132.9
143.6
158.2
169.8
174.4
184.1
195.6

115.4
118.5
125.7
134.4
146.4
159.6
172.6
175.2
185.5
199.1

117.2
121.8
130.6
137.6
150.2
164.2
176.2
178.9
190.5
203.0

117.8
123.7
132.1
140.4
152.4
166.9
179.3
182.0
193.8
207.7

118.7
125.6
134.3
143.2
155.0
169.8
181.1
183.4
195.5
209.7

118.4
126.2
134.4
143.5
156.2
170.9
181.6
183.8
196.7
210.9

116.5
125.7
132.6
143.2
156.0
170.6
179.7
182.4
195.4
209.7

TOTAL DURABLE GOODS INDUSTRIES
(Seasonally Unadjusted, 1957-59=100)

1960
1961
1962
1963
1964
1965
1966
1967
1968
1969

Jan.

Feb.

Mar.

Apr.

May

June

July

Aug.

Sept.

Oct.

Nov.

Dec.

102.3
114.2
138.1
160.5
175.3
200.1
211.3
221.1
247.1

103.9
124.5
142.0
163.8
181.0
207.1
126.5
228.0
256.9

99.4
123.7
143.6
165.4
179.6
208.3
209.3
226.7
253.4

104.9
127.0
150.9
168.2
190.1
216.7
214.3
229.4
258.3

107.7
128.2
155.4
171.3
191.0
214.7
216.9
239.0
264.5

112.7
109.2
134.0
159.0
177.2
193.3
224.4
220.7
244.9
270.8

109.7
109.3
129.6
156.3
173.7
193.6
221.7
219.2
243.6
273.5

110.1
113.5
130.7
160.6
175.2
199.3
227.9
221.7
247.8
285.8

108.3
113.8
136.0
163.8
178.2
197.3
230.0
223.2
248.0
281.2

108.9
114.7
136.4
163.3
175.9
200.1
227.7
220.5
249.2
282.4

105.3
116.2
134.4
163.0
176.4
203.0
226.0
222.8
250.6
282.0

103.5
115.7
130.9
160.8
178.5
200.7
224.4
222.5
251.0
276.3


https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis

TOTAL MANUFACTURING
(Seasonally Unadjusted, 1957-59=100)

Jan.

Feb.

Mar.

Apr.

Maj.

June

July

Aug-

Sept.

Oct.

Nov.

Dec

110.5
119.5
134.7
150.8
165.0
184.3
191.6
198.1
247.1

110.6
124.6
135.7
151.7
166.7
186.4
192.4
201.3
256.9

108.3
123.6
136.2
151.6
165.5
186.5
187.8
199.8
253.4

110.2
124.6
139.4
152.9
170.5
190.0
189.6
200.2
258.3

112.4
126.2
142.6
154.5
171.7
189.4
191.1
206.3
264.5

113.9
113.5
130.3
145.7
159.7
175.1
195.6
195.5
211.6
270.8

113.5
115.1
129.1
145.2
159.7
176.0
195.7
195.1
211.9
273.5

114.4
118.6
131.2
148.5
162.5
180.8
200.5
198.2
216.5
285.8

113.9
119.5
134.. 5
151.8
164.9
181.4
203.3
201.2
218.4
281.2

114.8
121.4
135.7
153.0
165.2
184.6
203.1
200.3
220.8
282.4

113.0
122.2
135.1
153.2
166.2
186.5
203.0
201.6
221.8
282.0

111
121
132
151
167
185
201
200
221
276

1960
1961
1962
1963
1964
1965
1966
1967
1968
1969


https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis

i
Ln
GO
I

-54-

BIBLIOGRAPHY

Books
Dunlop, John T., and Diatchenko, Vasilii P., Labor Productivity.
McGraw-Hill Book Company, 1964.

New York,

Hultgren, Thor, Changes in Labor Cost During Cycles in Production and Busi­
ness (New York, National Bureau of Economic Research, 1960), Chapter 2.

______ , Cost, Prices, and Profits: Their Cycle Relations.
Bureau of Economic Research, 1965.

New York, National

Kendrick, John W., Productivity Trends in the United States.
Princeton University Press, 1961.

Princeton,

Kendrick, John W., and Creamer, Daniel, Measuring Company Productivity.
York, National Industrial Conference Board, 1965.

Macaulay, Frederick R., The Smoothing of the Time Series.
Bureau of Economic Research, 1931.

New

New York, National

Seasonal Adj ustment on Electronic Computers. Organization for Economic Co­
operation and Development (report and proceedings of an international
conference held in November 1960).

Articles

A symposium on CES Production Functions, Review of Economics and Statistics,
Vol. 50, 1958, pp. 443-479.

Anderson, L. C., "Value Added by Manufacture, Central Mississippi Valley
Metro Areas, 1957-64." Review, Federal Reserve Bank of St. Louis. June 1964
David, Faul A., "The Deflation of Value Added."
Statistics, Vol. 44, 1962, pp. 148-155.

Review of Economics and

Davis, C. Howard, "Improvement of Texas Industrial Production Index."
ness Review, Federal Reserve Bank of Dallas, September 1968.

Busi­

Dhrymes, Phoebus J., and Zarembka, Paul, "Elasticities of Substitution for
Two-Digit Manufacturing Industries: A Correction." Review of Economics
and Statistics, Vol. LII (February 1970).

"Electric Power - An Indicator of Industrial Activity." New England Business
Review, Federal Reserve Bank of Boston, February 1965.
"Electric Power as a Regional Economic Indicator."
Reserve Bank of Cleveland, September 1964.


https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis

Economic Review, Federal

-55-

"Electric Power Consumption - An Output Indicator in Milwaukee.”
Conditions, Federal Reserve Bank of Chicago, April 1962.
’’Electric Power Consumption in Manufacturing.”
Reserve Bank of Philadelphia, April 1961.

Business

Business Review, Federal

Fisher, Franklin M., ’’Embodied Technology and the Existence of Labour and
Output Aggregated." Review of Economic Studies, Vol. 35 (1968).
______ , "The Existence of Aggregate Production Function."
37 (1969).

Econometrica, Vol.

Gallaway, Lowell E., "Regional Capital Estimates by Industry, 1954-57."
Southern Economic Journal, Vol. XXIX (July 1962).

Kuh, Edwin, Profits, Profits Markups, and Productivity. Joint Economic
Committee, 86th Congress, Government Printing Office, 1960.

Lovell, C. A. Knox, "Biased Technical Change and Factor Shares in the U. S.
Manufacturing." Quarterly Review of Economics and Business, Vol. 9
(Autumn 1969).
Nerlove, Marc, "Recent Empirical Studies of the CES and Related Production
Functions," in Murray Brown, ed., The Theory and Empirical Analysis of
Production (New York, National Bureau of Economic Research, 1967).

Pyun, C. S., "The Southeast’s Booming Paper Industry."
eral Reserve Bank of Atlanta, September 1969.

Monthly Review, Fed­

Shen, T. Y., "Innovation, Diffusion, and Productivity Changes."
Economics and Statistics, Vol. 43 (1961).

Review of

Solow, Robert M., "Some Recent Developments in the Theory of Production," in
Murray Brown, ed., The Theory and Empirical Analysis of Production (New
York, National Bureau of Economic Research, 1967).

"Toward an Index of Ninth District Industrial Production." Monthly Review,
Federal Reserve Bank of Minneapolis, June 1966.
Wilson, Thomas A., and Eckstein, Otto, "Short-run Productivity Behavior in
U. S. Manufacturing." Review of Economics and Statistics, Vol. 46 (1964).
Zarembka, Paul, "On the Empirical Relevance of the CES Production Function."
Review of Economics and Statistics, Vol. LII (February 1970).

Government Publications

Gehman, Clayton, and Metheral, Cornelia, Industrial Production Measurement in
the United States: Concepts, Uses, and Compilation Practices. Washington,
Board of Governors of the Federal Reserve System, February 1964.


https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis

-56-

Industrial Production, 1959 Revision.
Federal Reserve System, 1960.

Washington, Board of Governors of the

U. S. Bureau of Census, Annual Survey of Manufactures.

______ , Census of Manufactures.

Various volumes.

1957 and 1963.

U. S. Bureau of Labor Statistics, Employment and Earning Statistics for the
ILSL, 1909-68. Bulletin No. 1312-6, 1968.

______ , Trend in Output Per Man-hour in the Private Economy, 1909-1958.
Bulletin No. 1249, December 1959.

Others

Business Indexes Proposed for the Fifth District (mimeograph).
serve Bank of Richmond, undated.

Federal Re­

Estle, Edwin E., and Fair, Jerilyn, "Electric Power - An Indicator of Indus­
trial Activity - Technical Supplement" (mimeograph). Federal Reserve Bank
of Boston, 1965.
Grose, Lawrence, "Derivation of Quarterly and Monthly Correction Factors of
the Bassie Method." U. S. Department of Commerce memorandum, June 11, 1942

Long, Richard, Measuring Regional Production, a proposal.
Bank of Atlanta, undated.

Federal Reserve

"Measuring New England’s Manufacturing Production - Technical Supplement"
(mimeograph). Federal Reserve Bank of Boston, October 1963.

Minutes of the Workshop on Local Production Indexes, (the conference was held
at the Federal Reserve Bank of Cleveland in April 1964). Federal Reserve
System.
Hale, Carl W., Methodology of the Texas Industrial Production Index, 1966 re­
vision (mimeograph). Federal Reserve Bank of Dallas, July 1966.
Shen, T. Y., A Regional Production Index for New England (mimeograph).
Federal Reserve Bank of Boston, 1960.


https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis

Boston