Full text of Economic Review (Federal Reserve Bank of Cleveland) : October 1968

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OCTOBER 1968

IN

THIS

ISSUE

Corporate M erge r
Activity in the Fourth
Federal Reserve District,
1 9 5 0 -1 9 6 7 .............. 3

Economic Profile of
Selected Standard
Metropolitan Statistical
Areas in the
Fourth District . . . . 1 1

FEDERAL



RESERVE

BANK

OF

CLEVELAND

Additional copies of the E C O N O M IC REVIEW may
be obtained from the Research Department, Federal
Reserve Bank of Cleveland, P.O. Box 6387, Cleveland,
O hio 44101. Permission is granted to reproduce any
material in this publication.



O CTOBER 1968

CORPORATE MERGER ACTIVITY
IN THE FOURTH FEDERAL RESERVE
DISTRICT, 1950-1967*
Maurice M ann, John J. Erceg, and Benton E. G u p * *

The present wave of m ergers represents
the third major m erger movement in United
States economic history. A particular type of
m erger dominates each of these movements.1
For exam ple, during the first major period,
1898 to 1902, m ergers were largely of a
horizontal type that joined firms producing
the sam e or closely related products. During
the second major period, 1926-1930, m ergers
were primarily of a vertical type that m erged
large firms with suppliers in order to achieve
* Presented at the annual meeting of the American Statis­
tical Association, Pittsburgh, Pennsylvania, August 21,
1968.
* * The authors are Vice President and General Economist,
Senior Economist, and Economist, respectively. Federal
Reserve Bank of Cleveland. Acknowledgement is m ade
to the Federal Trade Commission for supplying the basic
d ata used in this study. The view s expressed in this paper

greater econom ies of scale. The third major
m erger movement, which b egan in 1950,
has been characterized mainly by the con­
glom erate type of m erger. Moreover, the
duration of the movement has been longer
and the movement has been m arked by a
larger number of recorded m erger trans­
actions than either of the two earlier periods.
C on glom erate m ergers acco u n ted for
about 5 9 p ercen t of re c o rd e d " l a r g e "
m ergers2 during 1948-1953, 61 percent
during 1954-1959, 71 percent during 19601964, and 78 percent during 1965-1967.3
Although limited, available data indicate
that conglom erate m ergers also increasingly
dominated the activity of firms m erging in
the Fourth Federal Reserve District, account­
ing for about two-thirds of the identified large
m ergers during the entire period under

do not necessarily reflect those of the Federal Reserve
Bank of Cleveland or the Federal Reserve System. This

2 According to the Federal Trade Commission, large merg­

paper should be considered a s a progress report since

ers are defined a s those involving acquired firms with
asse ts of $10 million or more.

the findings are preliminary and further an alysis of the
d ata is under w ay.
1 See Ralph L. Nelson, Merger Movements in American
Industry, 1895-1956 (Princeton, New Jersey: Princeton

3 U. S., Congress, Senate, Subcommittee on Antitrust and
Monopoly of the Committee on the Judiciary, Hearings,
on S. Res. 40 Economic Concentration, Part 2, 89th Cong.,

University Press for the National Bureau of Economic
Research, 1959), pp. 5-6.

1st Sess., 1965, p. 516, and U. S., Federal Trade Commis­
sion, News R elease (March 18, 1968).




3

E C O N O M IC R E V IEW

review.4Within this context, product-extension
m ergers, i.e., involving firms with com ple­
mentary products, showed a pronounced
upward trend.
A gainst the background of patterns and
trends in the United States, this paper pre­
sents some preliminary findings on the
characteristics of m erger activity in the
Fourth District during the period 1950-1967.
The analysis should be considered as tenta­
tive since further refinements are needed in
the basic data.

GENERAL PATTERNS
Table I shows that there were sizable yearto-year variations within the rising trend of
m erger activity (manufacturing and mining)
in both the United States and the Fourth
District during 1950-1967.5 Annual vari­
ations in m erger activity show a close associ­
ation with chan ges in the level of stock prices
and little conformity with the pace of business
activity (see Table II). For exam ple, the
num ber of recorded m ergers in the United
States in creased markedly in 1955, 1959,
and 1961, years when prices of common
stocks rose sharply. On the other hand, the
number of recorded m ergers in the nation
declined noticeably in

1957,

1962, and

TABLE I
Firms A cquired in M a n u fa c tu rin g a n d M in in g
United States an d Fourth District
1950-1967
United States

Fourth District*

1950

21 9

24

1951

235

46

1952

288

34

1953

295

34

1954

387

72

1955

78 2

89

1956

824

94

1957

730

89

1958

737

99

1959

93 6

101

1960

966

1961

1,117

106

1962

1,003

98

1963

985

84

1964

1,065

90

1965

1,125

96e

1966

1,106

139

19 67

1,639

165

91

NOTE: Data for 19 5 0 -1 9 5 4 not strictly comparable
to 1955-1967.
e Estimated by the Federal Reserve Bank of Cleveland.
* Based on number o f acquisitions by firms headquartered in the
Fourth District.
Sources: Federal Trade Commission and Federal Reserve Bank
of Cleveland

1966, years in which stock prices fell sharply.
The data in Table I also show that the number
of m ergers in the United States accelerated
in 1967, which was a year of rapidly rising
stock prices.

the state of Ohio, the western third of Pennsylvania, the
eastern half of Kentucky, and six counties in the northern

The pattern of m erger activity in the
United States during 1950-1967 was gen ­
erally replicated in the Fourth District.
Although data limitations preclude precise
comparisons, both trend and year-to-year

part of West Virginia.

variations in m erger activity in the Fourth

4 U. S., Federal Trade Commission, Statistical Report
Large Mergers in Manufacturing and Mining, 1948-1967
(May 1968). The Fourth Federal Reserve Dislricl includes

District conformed generally to trend and
5 D ata for 1950-1954 are not strictly com parable with
those for 1955-1967. Moreover, 1963 and 1965 d ata for the
Fourth District are probably understated b ecause of in­
complete records.

Digitized for
4 FRASER


annual variations in the nation as a whole.
Major exceptions to the national pattern were
the decline in the num ber of m ergers in the

OCTOBER 1968
TABLE II
Percent C h a n g e in Selected Data, A n n u a lly
1950-1967
Gross
National
Product

Stock
Prices

Mergers in
United States

Mergers in
Fourth District

1950

+

9 .6 2 %

+ 2 0 .8 1 %

+

7 3 .8 %

+

1 4 .3 %

1951

+

7.90

+ 21.41

+

7.3

+
—

91.7

1952

+

3.05

+

9.66

+

22.6

1953

4.47

+

0.93

+

2.4

1954

+
—

1.41

+ 2 0 .0 5

+

31.2

1955

+

7.61

+ 36.37

+ '102.1

+

1956

+

1.84

+ 15.13

1.43

—

4.81

11.4

+
—

5.3

1958

+
—

+
—

5.4

1957

1.15

+

4.19

+

1.0

+

11.2

1959

+

6.39

+ 24.09

+

27.0

1960

+

2.47

—

2.67

+

3.2

+
—

9.9

1961

+

1.94

+ 18.65

+

6.55

—

5.87

+
—

10.2

+
—

16.5

1962
1963

+

4.00

+ 12.00

—

1.8

—

14.3

1964

+

5.46

+ 16.45

+

8.1

+

7.1

1965

+

6.31

+

8.35

5.6

+

6.7

1966

+

6.36

—

3.31

+
—

1.7

+

44.8

1967

+

2.43

+

7.82

+

48.2

+

18.7

15.6

26.1
-0 -

+ 111.8
23.6
5.6

2.0

7.6

Sources: U. S. Department of Commerce; Federal Trade Commission; Standard & Poor's Corporation; Federal Reserve
Bank of Cleveland

the acquiring firms is unknown (presumed
to be under $25 million), 21 percent had
assets under $10 million, 21 percent had
assets of $10 to $25 million, and 13 percent
fell in the $25 to $50 million asset size.
Except for the $ 1 0 0 to $ 2 5 0 million size class,
the data suggest that the p ro p o rtio n of a c ­
quiring firms in each asset size class de­
creases as asset size increases. Nevertheless,
in 1966-1967, there was a sizable increase
in the n u m b e r and p ro p o rtio n of acquiring
firms in the $1 billion and over asset size
class. The asset size pattern of acquiring
firms in m erger activity in the Fourth District
during 1950-1967 was strikingly similar to
that in the nation during a com parable time
period (see Table III).

TABLE III
Distribution of C lassifie d M e rge rs by
Asse t Size of A c q u irin g Firms
United States (1955-1967) an d
Fourth District (1950-1967)

Fourth District in 1960, and the increase in
1966. In the case of the latter, the difference
from the nation was due to the heavy acq u i­
sition program s of several large firms located
in the District. As in the nation, 1967 was an
exceptionally strong year of m erger activity
in the District.

Asset Size
(Mil. of $)

Number

Percent

Under $10

2,764

2 4 .6 %

3,579

31.9

1,278

11.4

ASSET SIZE

$1 00 to $250

United States
19 5 5 -1 9 6 7

$10 to $25
$25 to $50
$50 to $100

A c q u irin g Firms. As shown in Table III,

during the 1950-1967 period, firms with
assets under $ 5 0 million (including firms
whose asset sizes are unknown) dominated
the acquiring side of m erger activity in the
Fourth District, accounting for nearly twothirds of the total. Of the 1,696 recorded
m ergers, the asset size of about 9 percent of



“

$2 50 to $499

Fourth District
19 50-1 967
Number

Percent

354

2 0 .9 %

349

20.6

220

13.0

186

11.0

251

14.8

98

5.8

42

2.5

$7 50 to $999

10

0.6

$1,000 and over

39

2.3

$5 00 to $7 49

2,549

Unknown*

1,060

Total

11,230

22.7

9.4
1 0 0 .0 %

8.7

147
1,696

1 0 0 .0 %

NOTE: Details may not ad d to totals because of rounding.
* Includes under $1 million or unknown.
Sources: Federal Trade Commission and Federal Reserve Bank of
Cleveland

5

E C O N O M IC R EV IEW
Acq uired Firms. Data on asset size are not

available for a large preponderance of firms
(931 of 1,276) that were acqu ired in the
Fourth District during 1950-1967. It is
reasonable to conclude, however, that these
firms were for the most part small, privately
held com panies with assets under $10 mil­
lion. From data that are available for acquired
firms, it is possible to make some comparisons
of m erger developments in the Fourth Dis­
trict and United States. For example, during
1950-1967, about 61 percent of the acquired
firms in the Fourth District for which asset
data are available fell in the asset size class
below $ 1 0 million and about 21 percent fell
in the $ 1 0 to $ 2 5 million size, as shown in
Table IV. Except for the $100 to $ 250 million
size class, the proportion of acquired firms
in each asset size class decreases as asset
class increases. During 1950-1967, the asset
size pattern of acquired firms in the Fourth
District for which data are available was
similar to that in the nation during a com­
parable time period. The important point
seem s to b6 that in both the District and the
nation the acquired firms were, on average,
considerably sm aller in asset size than the
acquiring firms.

INDUSTRIES 6
A c q u irin g Firms. Firms in six major in­
dustries accounted for about two-thirds of

all acquisitions by firms headquartered in
the Fourth District during 1950-1967, as
shown in Table V. The nonelectrical ma­
chinery industry, with nearly 18 percent of
6 Indusiry d a la used in this section are com parable to
the d ata used in Table I.

6 FRASER
Digitized for


the acquisitions, led the way, followed in
order by fabricated metals, transportation
equipment, primary metals, chem icals, and
electrical machinery. The dominance of these
industries in m erger activity in the District
is not surprising in view of the fact that they
account for a substantial share of the area's
economic activity (for exam ple, about 70
percent of the District's m anufacturing em­
ployment) .
Acquired Firms. During the period under

review, the heavy goods industries also
dominated the acquired side of m erger
activity in the Fourth District, with durable
goods producers representing four of the
five industries most actively involved in
m erger activity in the District. Firms in the
nonelectrical machinery industry accounted
for one-fifth of acquired firms in the Fourth
District during 1950-1967, followed in order
by fabricated metal products, primary metals,
electrical machinery, and chem icals. Taken
together, firms in these five industries a c ­
counted for nearly three-fifths of firms a c ­
quired during 1950-1967. Within the period,
fabricated metals and chem icals accounted
for an increasing proportion of firms acquired,
while electrical machinery and transportation
equipment accounted for a decreasin g pro­
portion.
In terms of industry affiliation of both a c ­
quiring and acquired firms, the pattern in the
Fourth District differed appreciably from the
United States. This is not surprising because
the industrial composition of any area, in this
case the Fourth District, should be reflected in
the nature of m erger activity in that area.
Perhaps more importantly, there is at least
presumptive evidence that firms in the Fourth

TABLE IV
Distribution of Classifie d M e rge rs b y Asse t Size of A cq uired Firms
United States (1948-1964) an d Fourth District (1950-1967)
Large M ergers in the
United States
1 9 48-1 964

Total M ergers in the
Fourth District
19 50-1 967
(Including Unknown
Asset Size Class)

Asset Size
(Mil. of $)

Number

Percent

Under $ 1 0 ................................

Number
209

(Excluding Unknown
Asset Size Class)

Percent

Number

Percent

1 6 .4 %

209

6 0 .6 %

$10 to $25

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

44 2

6 1 .4 %

74

5.8

74

21.4

$ 25 to $ 5 0

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

162

22.5

27

2.1

27

7.8

$50 to $ 1 00

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

80

12

12

0.9

12

3.5

$1 00 to $ 2 50

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

34

4.7

16

1.3

16

4.6

............................ ................2

0.3

7

0.5

7

2.0

931

73.0

O ver $ 2 50

U n k n o w n ................................
T o t a l ................................

72 0

1 0 0 .0 %

1,276

10 0 .0 %

345

1 0 0 .0 %

NOTE: Details may not a d d to totals because of rounding.
Sources: Federal Trade Commission and Federal Reserve Bank of

TABLE V
Distribution of C lassified M e rge rs by Industry
Fourth District
1950-1967
Acquiring Firms
>IC Group
10-14
19

Industry

Number

Mining

27

Ordnance and accessories

—

Percent
1 .8 %

8

0 .8 %

1

0.1

48

4.8

Food and kindred products

21

Tobacco manufactures

2

—

22

Textile mill products

1

—

23

A p p are l and other finished products
m ade from fabrics and similar materials

43

24

Lumber and wood products, except furniture

16

25

Furniture and fixtures

26

Paper and allied products

27

Printing, publishing, and allied industries

28

Chemicals and allied products

Percent

—

20

26

Acquired Firms
Number

1.7
—

—

13

1.3

2.8

8

0.8

1.1

6

0.6

18

1.2

14

1.4

81

5.3

49

4.9

35

2.3

26

2.6

138

9.1

71

7.1

29

Petroleum refining and related industries

44

2.9

2

0.2

30

Rubber and miscellaneous plastics products

80

5.3

61

6.1
0.9

31

Leather and leather products

17

1.1

9

32

Stone, clay, and glass products

78

5.1

64

6.4

33

Primary metal industries

141

9.3

92

9.2

34

Fabricated metal products, except
ordnance, machinery, and transportation equipment

167

11.0

135

13.5

35

Machinery, except electrical

272

17.9

20 0

20.0

36

Electrical machinery, equipment, and supplies

126

8.3

86

8.6

37

Transportation equipment

152

10.0

53

5.3

38

Professional, scientific, and controlling instruments;
photographic and optical goods,- watches and clocks

32

2.1

24

2.4

39

Miscellaneous manufacturing industries

21

1.4

31

3.1

Total mining and manufacturing

1,517

1 0 0 .0 %

1,001

1 0 0 .0 %

NOTE: Details may not a d d to totals because o f rounding.

Digitized Sources:
for FRASER
Federal Trade Commission


and Federal Reserve Bank of Cleveland

7

E C O N O M IC R EVIEW

T AB LE V I
D istrib u tio n of Larg e M a n u fa c tu rin g a n d M in in g A c q u isitio n s b y Type
Selected Periods, 1948-1967
19 48-1 953
United States

Number

Percent

18

19 54-1 959

19 60-1 964

Number

Percent

Number

19 6 5 -1 9 6 7

Percent

Number

Percent

1 9 4 8 -1 9 6 7
Number

Percent

Type of M erger
Horizontal
Vertical
Conglomerate

3 1 .0 %

78

2 4 .8 %

42

1 2 .0 %

40

1 1 .5 %

178

16 . 7 %

6

10.3

43

13.7

59

17.0

37

10.6

145

13.5

34

58.7

193

61.5

2 47

71.0

272

77.9

746

69.8

Product extension

27

46.6

145

46.2

184

52.9

188

53.9

544

50.9

M arket extension

4

6.9

20

6.4

24

6.9

8

2.3

56

5.2

Other

3

5.2

28

8.9

39

1 1.2

76

21.8

146

13.7

Total

58

1 0 0 .0 %

19 50-1 953
Fourth District

314

1 0 0 .0 %

19 54-1 959

Number

Percent

Number

Percent

348

10 0 .0 %

349

19 60-1 964
Number

10 0 .0 %

1 9 65-1 967

Percent

Number

Percent

1,069

10 0 . 0 %

19 5 0 -1 9 6 7
Number

Percent

17

18 . 7 %

Type of M erger
Horizontal

1

2 5 .0 %

7

2 3 .3 %

6

2 3 .1 %

3

Vertical

1

25.0

5

16.7

3

1 1.5

5

16.1

14

15.4

Conglomerate

2

50.0

18

60.0

17

65.4

23

74.2

60

65.9

1

25.0

16

61.5

21

67.7

—

—

Product extension
M arket extension
Other
Total

—
1
4

12

40.0

—

2

6.7

25.0

4

13.3

1 0 0 .0 %

30

1 0 0 .0 %

1
26

3.8
1 0 0 .0 %

—
2
31

9 .7 %

50

54.9

—

2

2.2

6.4

8

1 0 0 .0 %

91

8.8
1 0 0 .0 %

NOTE: Details may not ad d 1o totals because of rounding.
Sources: Federal Trade Commission and Federal Reserve Bank of Cleveland

District, even of the conglomerate type,
prefer, where possible, to m erge within the
sam e or complementary industries, i.e., to
extend product lines. As shown in Table VI,
55 percent of recorded large m ergers in the
District during 1950-1967 involved product
extensions, a situation reasonably similar to
that in the nation.
F IN A N C IA L A SP E C T S

To test the feasibility of analyzing the fi­
nancial aspects of m erger activity involving
firms located in the Fourth District, a pilot
study of m ergers consummated in 1967 was
undertaken. In 1967, there were 439 com­
panies involved in m erger activity in the
8 FRASER
Digitized for


Fourth District. Sufficient financial data to
permit analysis are available for only 197 of
these companies, 164 of which were acqu ir­
ing firms and 33 acquired firms.7 Most of
the 242 com panies for which data are not
available were acquired companies, which
as indicated earlier, were small, privately
owned firms.
Among major characteristics of firms an a­
lyzed, the information revealed that the a c ­
quired com panies tended to be small in com­
parison with the acquiring com panies. For
example, the m ean asset size of acquired
7 The data, which are from Moody's Industrial Manual
(June 1967) and Standard Corporation Descriptions, are
for 1966.

OCTOBER 1968

com panies was $ 5 9 .8 million, com pared
with $188.1 million for acquiring com panies.8
In addition, 85 percent of the firms analyzed
turned out to be m anufacturing firms, which
is not surprising in view of the domination of
heavy goods industries in the Fourth District.
As shown in Table VII, virtually half of the
com panies fell in five industry groups; pri­
mary metals, fabricated metals, transportation
equipment, electrical machinery, and non­
electrical machinery. The two machinery
groups accounted for nearly one-fourth of
the total.
In order to gain some insights into the
principal financial characteristics — profit­
ability, financial structure, and capitalization
rates—of the m erged companies, four rele­
vant financial ratios were computed wherever
possible.9 The ratios are: (1) rate of return on
stockholders' equity; (2) the debt-to-equity
ratio; (3) the quick-ratio test for liquidity; and
(4) the price-earnings ratio. Each ratio was
calculated for both acquiring and acquired
com panies, and the results summarized by
the following statistical m easures: the mean,
median, mode, and standard deviation, and
the coefficients of variance, relative skewness,
and relative kurtosis. Because many of the
distributions were highly skewed and quite
peaked, the midpoint of the modal class was
used to represent the data.
The statistical results are summarized in
Table VIII, from which a number of tentative

TABLE V II
M e rg e d C o m p an ie s in the Fourth District
by Stan d ard Industrial C odes
1967
Number of
Companies

SIC Group
20

Food and kindred products

6

22

Textile mill products

3

23

A p p arel and other finished products made
from fabrics and similar materials

2

24

Lumber and wood products, except
furniture

4

25

Furniture and fixtures

1

26

Paper and allied products

6

27

Printing, publishing, and allied industries

28

Chemicals and allied products

29

Petroleum refining and related industries

30

Rubber and miscellaneous plastics
products

6

31

Leather and leather products

6

32

Stone, clay, and glass products

33

Primary metal industries

34

Fabricated metal products, except
ordnance, machinery, and transportation
equipment

15

35

Machinery, except electrical

25

36

Electrical machinery, equipment, and
supplies

23

37

Transportation equipment

16

38

Professional, scientific, and controlling
instruments; photographic and optical
goods; watches and clocks

8

39

Miscellaneous manufacturing industries

2

4
13
6

7
15

Nonmanufacturing
All other M ajor Groups

29
197

Total
Source: Federal Trade Commission

TABLE V III
Selected A v e ra g e s for M e rg e d C o m p an ie s
in the Fourth District*
1967
Acquiring
Companies

Acquired
Companies

8 The midpoints of the modal c lass for acquired and
acquiring companies were $12.3 million and $127.9 mil­

Rate of return on equity

1 4 .8 6 %

10.31%

Debt-to-equity ratio

33.78

61.1 1

lion, respectively, reflecting the skew ness of the respec­
tive data.

Liquidity ratio

10.80

25.41

Price-earnings ratio

9.80 times

6.31 times

* A ve rage is the midpoint of the modal class.

9 See Appendix for formulations of the ratios.




Source: Federal Reserve Bank of Cleveland

9

E C O N O M IC R E V IEW

conclusions can be drawn: acquiring com­
panies were more profitable than acquired
com panies; acquiring com panies were not
as highly leveraged or as liquid as acquired
com panies; and investors placed a higher
capitalization rate on acquiring com panies
than on acquired companies. In the short
run, although profitability does not appear to
have been the major motive to acquire firms,
acquired firms did contribute to increased
earnings per share for acquiring firms. The
higher debt-to-equity and liquidity ratios of
the acquired com panies suggest that their
financial resources were not being m anaged
as efficiently as those of the acquiring firms.
Furthermore, the lower rate of return for
acquired com panies suggests that they were
less efficient than acquiring com panies.
Apparently, investors adopted this sam e
point of view becau se the price-earnings
ratio for acquired companies was substan­
tially lower than for acquiring com panies.
The nature of these results suggests that fur­
ther analysis of this type would be desirable,
particularly b ecau se of the industrial nature
and financial characteristics of firms involved
in m erger activity in the Fourth District.

acquiring firms. In addition, most of the m erg­
ers in the Fourth District involved business
firms in the sam e or complementary line of
activity. A vailable data provide presumptive
evidence that acquiring firms were more
profitable as well as more efficient than a c ­
quired firms. This suggests econom ies of
scale for acquiring firms and improved profit­
ability and efficiency for acqu ired firms
after absorption.

A P P E N D IX
Form ulations of Financial Ratios
7T — Net income or loss (after taxes)
T =

A = Total assets
L = Total liabilities
E =
PBT =
I =

Expansion through m ergers has becom e
an increasingly important source of growth
for business firms and appears to be closely
associated with chan ges in the level of stock
prices. More than half of the acquiring firms
in the Fourth District during 1950-1967 had
assets of less than $ 50 million. On balance,
the asset size of firms acquired through m erg­
er in the Fourth District during 1950-1967
was small in com parison with the size of
10




Stockholders' equity
Profit before taxes
Interest payments

Profits in any period

7T = ( 1 - T ) [ r + ( r - l | j ] E
where:
PBT+I
r ~

A

I
' ~
_

CO N C LU D IN G CO M M EN TS

Income tax rate

“

L
Income Tax
PBT

— =

debt-to-equity ratio

7r
— =

(1 — T) [r + (r— i) — ] = rate of return on equity

L

7T
This complex method of deriving — was used because
the equation for 7T is an identity and served to verify the data.
Other Formulations

Liquidity ratio =

Cash + Government
and marketable securities at cost
----------- —--------- —7 ---------------Current liabilities

Price-earnings ratio =

Price (balance sheet date)
---- ------------------- ------------Earnings per share

OCTOBER 1968

ECONOMIC PROFILE OF SELECTED
STANDARD METROPOLITAN STATISTICAL
AREAS IN THE FOURTH DISTRICT

This article provides an economic profile of
nine selected Standard Metropolitan Statis­
tical A reas located wholly or partially in
the Fourth Federal Reserve District. The
areas are' Erie, Pennsylvania; HamiltonMiddletown, Ohio; Huntington-Ashland, West
Virginia-Kentucky-Ohio; Johnstown, Pennsyl­
vania; Lima, Ohio; Lorain-Elyria, Ohio; M ans­
field, O hio; Springfield, O hio; an d S teu ­
benville-W eirton, Ohio-West Virginia (see
A ppendix for definition of each area).
The relatively small urban areas under
review1 are more sensitive than larger areas
to industry relocations and technological
1 In 1965, the population of the are as ranged from 270,000
in Johnstown to 126,000 in Mansfield.




changes, mainly becau se the former tend to
be dominated by individual industries. Such
sensitivity was especially apparent during
the 1950's, when most of these areas under­
went considerable economic adjustment. On
the other hand, the areas under review
generally have participated in the business
expansion that began in the nation in 1961.

EMPLOYMENT DISTRIBUTION
In each area, manufacturing is the primary
source of employment, followed by wholesale
and retail trade, an employment pattern
typical of most metropolitan centers. As su g­
gested in Table I, however, the relative
importance of the major employment cate­
gories varies widely am ong the respective
1 1

E C O N O M IC R E V IEW

T A B LE I
Percent D istrib u tio n o f C o v e r e d E m p lo y m e n t*
U n ite d State s a n d N in e Fourth D istrict S M S A s
1967
Transportation and
Public Utilities

Finance,
Insurance,
and Real Estate

Services
11.0%

Total

Mining

Manufacturing

Contract
Construction

United StatesJ

10 0 . 0 %

1 .2 %

3 8.4%

6 .3 %

6 .8 %

6 .5 %

Erief
Hamilton-Middletown

100.0

#

57.6

3.9

5.4

3.6

100.0

54.3

11.4

3.3

4.6

Huntington-AshlandJ

100.0

#
1.4

46.0

7.0

6.8

4.0

Johnstownf

100.0

8.9

46.5

3.4

6.4

3.4

9.9

21.3

0.2 **

Lima

100.0

#

52.4

5.3

5.4

3.9

6.2

25.1

1.7§

Trade

Other

25.1%

5 .6 % §

7.9

21.5

0.1**

6.1

18.8

1.5§

7.8

26.7

0 .3 **

Lorain-Elyria

100.0

#

59.2

4.3

3.4

2.8

7.8

19.2

2.9§

Mansfield

100.0

#

58.9

4.5

4.5

4.1

7.0

19.4

Springfield

100.0

#

55.5

4.4

4.9

4.1

8.5

20.6

1.6§
2.0§

Steubenville-Weirton+

100.0

2.3

63.2

5.8

5.3

1.6

5.3

15.8

0 .7 **

* Employment covered by unemployment compensation,
t Data for Pennsylvania are available for the first quarter only.

X Data

are for 1 966.

§ Includes Federal Government.

§ Included

in “Other."

* * Excludes Federal Government.
Sources: U. S. Department of Labor, Bureau of Labor Statistics; Research and Statistics Unit, Kentucky Department of Economic Security; Division of Research
and Statistics, Ohio Bureau of Employment Services; Division of Research and Statistics, Pennsylvania Bureau of Employment Security; Research
and Statistics Division, W est Virginia Department of Employment Security

SM SAs, although in each area the concentra­
tion in m anufacturing employment is con­
siderably greater than that in the United
States as a whole. For example, m anufactur­
ing employment in the different areas ranges
from 63 percent of total covered employment
in the Steuben ville-Weirton SMS A to 4 6 per­
cent in the Huntington-Ashland a re a .2 Trade
employment tends to be relatively more im­

dominant, such as in Huntington-Ashland,
Lima, and Johnstown.
The dominance of durable goods employ­
ment is a characteristic of nearly all Fourth
District SM SAs. In fact, durable goods indus­
tries account for at least two-thirds of m anu­

portant in areas where m anufacturing is less

Springfield SMSA, 91 percent of m anufactur­
ing employment is concentrated in durable
goods industries (see Table II).
The importance of individual m anufactur­
ing industries relative to total m anufacturing
employment in the nine areas is also shown

2 Considerable caution must be exercised in generalizing
from the information in Table I because covered employ­
ment represents only a portion of the total nonagricultural
employment of an area. For exam ple, state and local
government employment is not reported separately in any
are a, and Federal Government employment is only re­
ported for a few are as. Consequently, the relative im­
portance of the employment categories indicated in Table
I lends to be overstated, particularly manufacturing em­
ployment.

Digitized12
for FRASER


facturing employment in each of the nine
areas under review, com pared with 59 per­
cent in the nation. At the extreme, in the

in Table II. The nature of employment con­
centration in individual industries is in marked
contrast to the distribution of manufacturing
workers in the nation. The primary metal

O CTOBER 1968

T A B L E II
Percent D istrib u tio n o f M a n u fa c t u r in g E m p lo y m e n t 4
U n ite d State s a n d N in e Fourth D istrict S M S A s
1966

Total Manufacturing

United
Statest

Eriet

HamiltonMiddletown

HuntingtonAshland

Johnstown!

Lima

LorainElyria

Mansfield

Springfield

SteubenvilleW eirtonj

10 0 . 0 %

1 0 0 .0 %

1 0 0 .0 %

10 0 . 0 %

10 0 . 0 %

10 0 . 0 %

10 0 . 0 %

10 0 . 0 %

10 0 . 0 %

10 0 . 0 %

58.6

78.9

68.5

71.2

70.2

77.2

90.3

85.1

90.9

91.4

Lumber and wood products

3.1

0.7

1.7

n.a.

2.1

n.a.

n.a.

0.6

0.8

0.8

Stone, clay, and glass

3.4

0.3

0.9

13.1

2.2

n.a.

1.4

4.3

1.5

n.a.
73.3

Durable goods

Primary metals

7.0

10.4

29.5

41.9

50.4

0.3

28.4

9.6

2.3

Fabricated metals

7.0

13.8

20.4

n.a.

1.5

7.5

14.9

20.7

7.1

3.2

Nonelectrical machinery

9.9

10.7

8.3

1.7

19.3

5.4

5.0

22.8

0.5
0.2

Electrical machinery
Transportation equipment
Other durables
Nondurable goods

3.0

9.9

15.5

0.9

0.5

12.4

4.7

31.3

11.1

10.1

14.1

5.1

n.a.

9.7

22.2

33.9

2.8

39.5

0.1

8.2

13.4

1.7

13.2

2.1

15.5

1.6

10.8

5.8

13.3

41.4

21.1

31.5

28.8

29.8

22.8

9.7

14.9

9.1

8.6

Food and kindred products

9.3

4.4

3.4

5.2

5.7

7.0

1.3

1.8

3.1

1.7

A pparel

7.4

0.4

1.0

5.6

19.9

n.a.

n.a.

n.a.

0.4

0.1

Paper and products

3.5

5.0

23.6

n.a.

0.1

n.a.

n.a.

1.3

0.8

n.a.

Printing and publishing

5.2

2.0

2.1

2.6

1.7

2.5

1.7

3.9

2.9

1.3

Chemicals and
allied products

5.0

0.5

n.a.

9.4

0.2

1.7

4.2

0.3

n.a.

n.a.

Rubber and
miscellaneous plastics

2.6

8.1

n.a.

n.a.

0.1

0.4

1.8

7.0

n.a.

n.a.

Other nondurables

8.4

0.7

1.4

6.0

2.1

11.2

0.7

0.6

1.9

5.5

n.a. Not available.
* Unless otherwise stated, covered employment used,
f 1 9 6 0 data from Census of Population,
t Nonagricultural employment.
Sources: U. S. Department of Commerce, Bureau of the Census; U. S. Department of Labor, Bureau of Labor Statistics; Division of Research and Statistics,
Ohio Bureau of Employment Services; Pennsylvania Department of Internal Affairs

industries, for exam ple, account for about
three-fourths of m anufacturing employment
in the Steubenville-Weirton SM S A, one-half
in Johnstown, 42 percent in HuntingtonAshland, and nearly 3 0 percent in HamiltonMiddletown and Lorain-Elyria. Nationwide,
the primary metal industries account for only
7 percent of manufacturing employees.
The transportation equipment industry,
which employs 10 percent of the m anufac­
turing workers in the nation, accounts for 40
percent of m anufacturing employment in
Springfield, over one-third in Lorain-Elyria,
over one-fifth in Lima, and about 14 percent



in Erie. In all of the SM S As, with the excep ­
tion of Erie and Lima, the two leading durable
goods employers account for at least 50 per­
cent of m anufacturing employment.
In addition, within the durable goods in­
dustries that dominate manufacturing em­
ployment, individual com panies stand out as
the main employers in the areas. For example,
in the Erie SM SA, two product divisions of
the G eneral Electric Company account for
more than 25 percent of manufacturing em­
ployment. International Harvester C orpora­
tion employs nearly one-third of Springfield's
manufacturing workers, while in Johnstown,
13

E C O N O M IC R E V IEW

Bethlehem Steel Corporation is responsible
for about 50 percent of the area's m anufac­
turing em ployees. While employment con­
centration, whether in specific industries or
com panies, is not necessarily adverse to
economic growth, it does make an area
extremely vulnerable to the impact of chan ges
in specific industries an d /or firms.

TABLE III
Net M ig ra tio n Estim ates
N ine Fourth District S M S A s
1940-1965
1 9 4 0 -1 9 5 0
+ 1 5 ,0 0 0

—

Hamilton-Middletown

+

7,000

-(-20,000

—

6,000

Huntington-Ashland

— 15,000

— 28,000

—

9,000

Johnstown

— 43,000

— 49,000

— 22,000

Lima

+

5,000

*

+

1,000

Lorain-Elyria

+ 2 0 ,0 0 0

+ 3 4 ,0 0 0

+

4,000

Mansfield

Except for Johnstown, each SM SA under
review has had continuous population growth
since 1940. (Population in the Johnstown
SM SA declined by 2 8 ,0 0 0 persons between
1940 and 1965.) Absolute and relative gains
in population vary widely among the other
eight areas (see Chart 1). The Lorain-Elyria
SM SA recently experienced the greatest in­
crease in population, with an addition of
some 9 2 ,0 0 0 persons between 1950 and
1965, an increase of 62 percent. Among the
other areas under review, the smallest in­
creases in population between 1950 and 1965
occurred in Steubenville-Weirton (12,000 per­
sons or 8 percent) and Huntington-Ashland
(13,000 persons or 5 percent).
By definition, population chan ge is the

Springfield

+

Steubenville-Weirton

— 16,000

ference between in- and out-migrations (net
migration). Table III presents estimates of net
migration for each of the nine areas. Although
it is difficult to generalize from net migration
data, it is apparent that rapid increases in
population are associated with net in-migra­
tions; in contrast, low rates of increase in
population, as well as declines, are related
to net out-migrations of people. For exam ple,
the Lorain-Elyria, Hamilton-Middletown, Lima,
Digitized14
for FRASER


6,000

1 9 60-1 965

Erie

POPULATION TRENDS

algeb raic sum of the difference between the
number of births and deaths, and the dif­

1 9 5 0 -1 9 6 0

— 11,000

n.a.

+

4,000

4,000

+

2,000

+

8,000

*

— 13,000

—

7,000

n.a. Not available.
* Less than 500.
Source: U. S. Department o f Commerce

Mansfield, and Springfield SM SAs, where
population growth has been fairly rapid,
tended to realize net in-migrations of people
after 1940. On the other hand, SM SA s with
slower rates of increase in population (Erie,
Huntington-Ashland, and Steuben ville-Weir­
ton) experienced net outflows of people after
1940. The Johnstown SM SA experienced the
largest net out-migration from 1940 to 1965
(114,000 persons) and was also the only
SM SA to show a decline in population.
Although people move for many reasons,
chan ges in economic conditions in individual
areas are related to large movements of
people. G enerally speaking, net in-migra­
tions are related to in creased job opportunities
in an area; net out-migrations are related to
labor surpluses and deficiencies in new em ­
ployment opportunities.3 Thus, net migration
3 Migration estim ates for SMSAs can also reflect subur­
banization. For exam ple, a portion of the Lorain-Elyria
SM SA's population gain from net in-migration is due to
suburbanization of residents and workers from the Cleve­
land area.

OCTOBER 1968
C h a r t 1.

POPULATION GROWTH
U n it e d S t a t e s a n d
M illio n s o f p e r s o n s

N in e F o u rth D is tr ic t S M S A s
T h o u sa n d s of p e rso n s

onn __________

250
200

S o u r c e s o f d o to :

U. S. D e p a r t m e n t o f C o m m e rc e , B u r e a u o f th e C e n s u s ; O h io D e p a rt m e n t o f H e a lt h , D i v i s i o n o f V it a l S t a t is t ic s ; P e n n s y lv a n i a S t a t e P l a n n in g B o a r d




15

E C O N O M IC R E V IEW

estimates su ggest that, although the employ­
ment distributions of the nine SM SA s are
broadly similar, employment conditions vary
considerably am ong the SM SAs.

TABLE IV
Total N o n agric u ltu ra l Em ploym ent
United States a n d N ine Fourth District S M S A s
1950-1960

EMPLOYMENT GROW TH
1960
(Thousands of
persons)

Trends. During the 1950's, several national

trends had a restraining influence on the nine
SM SAs and resulted in rather sluggish em ­
ployment growth in most of the areas. For
exam ple, employment growth was affected by
the recessions in the nation in 1953-1954
and 1957-1958. In addition, becau se of major
technological changes in mining operations,
changing coal markets, a languid steel indus­
try, the relocation of plants, am ong other
reasons, employment growth in the nine
SM SAs did not generally resume until after
1961. The sluggishness of economic activity
during the 1950's in the SM SAs under review
is su ggested by the data shown in Table IV.
Only the Lorain-Elyria and Hamilton-Middletown SM SAs had average annual rates of
chan ge in total nonagricultural employment
that were greater than the national average
for the d ecad e.4
4 Bureau of Ihe Census d a la are given by place of resi­
dence rather than place of employment. Consequently,
some of the employment increase indicated in the nine
SM SAs represents growth in adjacent a re as. For exam ple,
the Lorain-Elyria SMSA, which is geographically a d ja ­
cent to Cleveland, h ad an estimated one-seventh of its
employed residents commute to jobs outside of Lorain
County in 1960. Estimates of the percent of employed
residents commuting to jobs outside of the resident county
in 1960 are:
Erie
HamillonMiddletown

2.2%
11.3

Huniington-

Lima
Lorain-Elyria
Mansfield
Springfield

6.1
SleubenvilleAshland
Weirton
Johnstown
5.0
Source: U. S. Department of Commerce


16


n.a.
14.1%
4.3
16.9
6.8

United States

60,289.4

Actual
A ve rage
Ch ange
Annual
1 9 5 0 -1 9 6 0
Rate of
(Thousands of
Change
persons)
1 9 5 0 -1 9 6 0
+ 10,887.7

+ 2 .0 %

Erie

84.1

+

2.0

+ 0.2

HamiltownMiddletown

68.7

+

15.7

+ 2 .6

HuntingtonAshland

78.5

+

4.3

+ 0 .6

Johnstown

81.8

—

6.0

— 0.7

Lima

51.5

+

6.7

+ 1.4

Lorain-Elyria

73.5

+

18.0

+ 2.8

Mansfield

41.9

+

7.8

+ 2 .1

Springfield

45.5

+

4.5

+ 1.0

SteubenvilleWeirton

55.7

+

0.1

*

* Less than 0.1 percent.
Source: U. S. Department of Commerce, Bureau of the Census

Com pared with the sluggish growth of the
1950's, employment in the nine SM SA s in the
1960's generally has shown a marked im­
provement. A vailable data,5 as shown in
Table V, indicate that since 1961 employ­
ment growth in four a re a s—Erie, Lima,
Lorain-Elyria, and Springfield—has exceeded
the average annual rate of increase in the
United States. The Huntington-Ashland SM SA
improved its rate of employment growth
appreciably and outperformed the nation,
while the Mansfield area continued to hold
at about the sam e p ace as in the nation. A l­
though showing significant improvement
over perform ance during 1950-1960, the
Steubenville-W eirton and lohnstown areas
5 D ata on total nonagricultural employment for each are a
are av ailab le only for those y ears in which the decennial
census is taken. Another d ata source is required to obtain
information on periods of less than a decade.

OCTOBER 1968
TABLE V
Total Covered Em ploym ent
United States an d N ine Fourth District S M S A s
1961 and 1967

United States

1961

1967

40,020,000

47,631,081 +

A verage
Annual
Rate of
Change
1 9 6 1 -1 9 6 7
+ 3 .5 §

Erie*

58,746

73 ,547

+ 3 .8 %

HamiltonMiddletown

44,825

52,149

+ 2.6

HuntingtonAshland

4 9 ,2 6 6 f

57,9 9 6 f

+ 4 .2 f

Johnstown

48,261

55,564

+ 2 .4

Lima

34,971

43,104

+ 3 .5

Lorain-Elyria

45,096

56,339

+ 3.8

Mansfield

32,006

39,638

+ 3.6

Springfield

27,724

34,849

+ 3 .9

SteubenvilleWeirton

4 3 ,0 8 9 f

47 ,626 f

+ 2 .5 f

* First quarter only,
f Data are for 1 962 and 1 966.
J Data are for 1966.
§ Data are for 1961 and 1966.
Sources: U. S. Department of Labor, Bureau o f Labor Statistics;
Research and Statistics Unit, Kentucky Department of
Economic Security; Division of Research and Statistics,
O hio Bureau o f Employment Services; Division of
Research and Statistics, Pennsylvania Bureau of Employ­
ment Security; Research and Statistics Division, W est
Virginia Department o f Employment Security

have continued to fall considerably below the
national rate of advance. Nevertheless, the
2.5 percent annual rate of in crease in em­
ployment in the Johnstown SM SA during
1961-1967 represents the reversal of a down­
ward trend that began in the 1 940's. The
forces behind the sluggishness of employ­
ment during the 1950's and the growth since
1961 in the nine areas are discussed in the
following sections.
Im pact of C h a n g e s in C oal M in in g. Three

a re a s—Johnstown, Steubenville-Weirton, and
Huntington-Ashland—sustained employment
losses in bituminous coal mining during the
1950's and 1960's because of the combi­



nation of production cutbacks and produc­
tivity gains. Fewer workers are required to
maintain production schedules, due to in­
creased productivity resulting from tech­
nological chan ges in mining and loading
operations. As indicated in Table VI, pro­
ductivity in coal mining, m easured by average
tons per man per day, in creased 148 percent
in the Johnstown area between 1950 and
1966, which was well below tl\e 188-percent
increase in the United States. Although pro­
ductivity in coal mining continues to be
greater in the Steubenville-W eirton area
than in the nation, productivity in the former
area in creased at a much slower pace, a d ­
vancing by 130 percent between 1950 and
1966. Productivity differences largely reflect
the types of mining operations that prevail
in the respective areas. For example, under­
ground mines predominate in the Johnstown
area, while stripping operations account for
most of the bituminous coal production in the
Steuben ville-Weirton SMSA.
After reaching a peak in 1943, consum p­
tion of coal produced in the United States
declined sharply, resulting in production cut­
backs and employment losses in the coal in­
dustry (for developments after 1950, see
Table VI). Major market losses occurred in
railroad fuels, retail and industrial uses, and
exports. On the other hand, the electric
utilities market becam e a major source of
consumption growth. Currently, electric
utilities consume about two-thirds of the coal
produced in the districts that include the
Johnstown and Steuben ville-Weirton SM SAs.
Concurrent production losses and pro­
ductivity gains in mining resulted in employ­
ment losses in the three areas under review.
17

E C O N O M IC R E V IEW
TABLE V I
Production, Em ploym ent, and Productivity in Bitum inous C o a l M in in g
United States an d H u ntington -A sh land , Johnstow n, an d Steubenville-W eirton S M S A s
Selected Years, 1950-1966
Production
(net tons, thousands)

United S t a t e s ........................................................

1950

1955

1960

1966

437,868.0

464,633.4

415,512.3

533,881.2

H u n tin gto n -A sh la n d .................................................

1,114.3

Jo h n sto w n ...............................................................

18,733.3

S t e u b e n v ille -W e ir t o n ..............................................

7,717.0

965.1

524.4

n.a.

13,985.4

8,762.6

12,238.4

5,115.3

3,957.8

5,662.9

A ve rage Number of Men W orking Daily
United S t a t e s .........................................................

433,698

225,093

169,400

1,062

569

181

20,679

10,967

6,302

4,387

3,874

1,773

1,098

1,014

H u n tin gto n -A sh la n d .................................................
Jo h n sto w n ................................................................
Steubenville-W eirton.................................................

131,752
n.a.

A ve rage Tons Per M a n Per D a y
United S t a t e s .........................................................

6.43

9.84

12.83

H u n tin gto n -A sh la n d .................................................

5.89

9.55

13.85

18.52
n.a.

J o h n sto w n ................................................................

4.90

6.28

8.05

12.16

Steubenville-W eirton.................................................

10.10

13.61

17.13

23.21

n.a. Not available.
Source: U. S. Department of the Interior

For exam ple, in the Johnstown SM SA, em­
ployment in bituminous coal mining accounted
for about 2 0 ,7 0 0 jobs in 1950 (24 percent of
total nonagricultural employment), in con­
trast to 6 ,3 0 0 jobs in 1960 and less than
4 ,4 0 0 jobs in 1966. Between 1950 and 1966,
the number of jobs in total mining activity
in Johnstown was reduced by 77 percent.

continued to fall since that time. In fact, coal
mining has all but ceased in the Huntington-

Similarly, between 1950 and 1960, mining
employment in the Steubenville-W eirton area

also occurred. At the sam e time, there was
an influx of agricultural workers into the non­

declined by 2 ,2 0 0 jobs, principally in bitu­
minous coal mining. In the SteubenvilleWeirton area, mining employment in 1966

agricultural labor force of each of the three
areas, which was not accom panied by ex­
pansion in major employment sectors, p ar­

represented less than one-third of the 1950
total (see Table VI). The Huntington-Ashland
area experienced a loss of about 900 jobs in
the bituminous coal industry in the 1950-

ticularly manufacturing. An insufficient
number of manufacturing jobs in the Huntington-Ashland, Johnstown, and Steuben­
ville-Weirton SM SAs reflected an inability

1960 period, and mining employment has

to attract new production activities as well as

Digitized 18
for FRASER


Ashland SMSA.
The losses suffered in mining employment
produced heavy unemployment in the Hun­
tington-Ashland, Johnstown, and Steubenville-Weirton areas, and, as mentioned
earlier, heavy out-migrations from those areas

OCTOBER 1968

growth problems in existing industries.
G ro w th

in

M a n u fa c tu r in g

E m p lo y m e n t.

Periods of economic slowdown in the nation
and plant closures in individual areas largely
account for the abrupt changes in manu­
facturing employment in the nine areas since
1950 (see Chart 2). For example, severe
m anufacturing employment losses in the Erie
and Springfield SM SAs in the middle and
late 1950's and the Hamilton-Middle town
SM S A in the early 1960's occurred as a re­
sult of the combination of the effects of re­
cessions (1953-1954, 1957-1958, and 19601961) and the loss of major employers in each
area. M anufacturing employment in Erie d e­
clined in 1954 and 1955 b ecause of the trans­
fer of the G eneral Electric Com pany's re­
frigerator division to Louisville, Kentucky.
The machinery industries in Erie in 1960 em ­
ployed 12,000 less workers than in 1950.
More generally, total m anufacturing em ­
ployment in Erie dropped 12 percent b e­
tween 1950 and 1960.
Similarly, in the Springfield SMSA, nearly
2 ,0 0 0 m anufacturing jobs were lost between
1950 and 1960, due largely to the closing of
the Crowell-Collier Publishing Company
plant. The Hamilton-Middle town SM SA lost
four m ajor industry employers in the early
1 960's, resulting in the significant drop in
employment shown in Chart 2. Although
m anufacturing employment in the HamiltonMiddletown area b egan to increase in 1963,
primarily b ecau se of expansion program s of
local industries, it has not yet returned to the
levels of the m id-1950's or the early 1960's.
As indicated in Chart 2, growth of manu­
facturing employment in the Lima and M ans­
field SM SAs since 1950 has tended to con­



form more closely to the national pattern
than is the case in the other areas. Thus far in
the 1960's, manufacturing employment sur­
p assed previous peak levels in only three of
the eight areas under review —Lima, M ans­
field, and Lorain-Elyria.6 The continuing de­
cline of employment in the stone, clay, and
glass industry is a major factor in explaining
the shrinkage of m anufacturing employment
in the Steubenville-W eirton SMSA. In ad ­
dition, the perform ance of the nation's steel
industry also had a major influence on the
employment situation in Steubenville-W eir­
ton and six of the other SM SAs.
In flu e n c e o f the Ste e l In d u s t r y . S te e l
production and the manufacture of steel mill
products are important sources of employ­
ment in seven of the nine SM SAs under re­
view. As a source of employment, the primary
metal industries (steel) are most important in
Steubenville-Weirton, followed respectively
by Johnstown, Huntington-Ashland, Hamilton-Middletown, Lorain-Elyria, Erie, and M ans­
field (see Table II). Thus, the prospects and
problems of the nation's steel industry affect
considerably these seven urban economies.
During the 1950's, the perform ance of the
steel industry was adversely affected by re­
cessions and three major strikes, and the slow
growth of production was insufficient to
overcome the decline in employment result­
ing from automation.7 Sluggish gains in
production resulted from the lack of growth
6 Lack of com parable d ata precludes a similar compari­
son for Huntington-Ashland.
7 See "Some Perspective on Steel," Economic Review,
Federal Reserve Bank of Cleveland, Cleveland, Ohio
(August 1965), pp. 3-11.

19

E C O N O M IC R E V IEW
C h a rt 2

MANUFACTURING EMPLOYMENT
U n ite d S t a t e s a n d N in e Fou rth D is t r ic t S M S A s
M i lli o n s o f p e r s o n s
25
U N IT E D STATES

10

T h ou san d s o fp e rso n s
30
L IM A

1—1—L

I I I I I I I I 1 I I 1 I I I 1 I I I

T h ou san d s of p e rso n s
55
E R IE

50
45
40
35
30

i

i

i

i

i

i

i

I

I

I

l

l

l

i

m

i

i

i

i

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

................. I I l l I I I I I I I I l

40
H A M IL T O N - M ID D L E T O W N

15

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

l l l I l I I l I 1 l

25
S P R IN G F IE L D

H U N T IN G T O N - A S H L A N D

30
25
.1..1 ..I

20

I

I

I

1..1.. 1 I

I

I

I

I

1 L
S T E U B E N V IL L E - W E I R T O N

40

35
JO HNSTO W N

35

-

30
AN N U ALLY

I I I I I I I
'70

N o te:

AN N U ALLY

25

I I
1950

I

I

I I
'5 5

I

I

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'6 0

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’65

I

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’70

D a sh e d lin e in d ic a te s la ck o f d a ta; a v a ila b le d a ta are conn e cte d to in d ic a te tren d .

S o u r c e s o f d a ta :

U. S . D e p a r t m e n t o f C o m m e rc e , B u r e a u o f t h e C e n s u s ; D i v i s i o n o f R e s e a r c h a n d S t a t is t ic s , O h io B u r e a u o f E m p lo y m e n t S e r v ic e s ;
D iv isio n

o f R e s e a r c h a n d S t a t i s t i c s , P e n n s y l v a n i a B u r e a u o f E m p lo y m e n t S e c u r it y ;

o f L a b o r S t a t is t ic s , 1 9 6 8 ; D iv i s i o n o f R e s e a r c h


http://fraser.stlouisfed.org/
20
Federal Reserve
Bank of St. Louis

S t a t i s t i c a l A b s t r a c t o f th e U n it e d

a n d S t a t i s t i c s , W e s t V i r g i n i a D e p a rt m e n t o f E m p lo y m e n t S e c u r it y

State s H a n d b o o k

■ I

O CTOBER 1968

of both domestic steel consumption and
United States steel exports. While domestic
steel consumption has markedly in creased in
the 1960's, steel imports have advanced at a
more rapid pace and exports have declined.8
To understand the impact of these develop­
ments on the seven SM SAs that are impor­
tantly affected, differential growth rates in
various steel mill products should be con­
sidered.
Steel mill plants are complex facilities that
specialize in certain steel mill products. The
product specialities of the plants located in
each of the seven SM SAs are identified in
Table VII; the growth of domestic consum p­
tion and imports of these product specialties
is shown in Table VIII. From 1956 through
1967,9 the gains in production and consum p­
tion of steel mill products lagge d the gain in
all m anufacturing production in the United
States.10 During the period, total manufactur­
ing production in creased at an av erage an ­
n u a l rate of 4 .5 p e rc e n t, c o m p a re d with
a n i n c r e a s e of l e s s th a n 1 p e r c e n t fo r
production of steel mill products and 1 per­
cent for domestic steel consumption (net
of imports). As shown in Table VIII, since
1956, domestic consumption (net of imports)
of 6 of the 11 steel mill products has increased
at the sam e p ace or more than the consum p­
tion of all steel mill products. The six products
8 See "United Stales Trade in Steel," Economic Review,
Federal Reserve Bank of Cleveland, Cleveland, Ohio
(June 1968), pp. 9-22.
9 Nineteen hundred and fifty-six is the first y ear for which
consistent data are av ailab le for the steel mill products
listed in Table VIII.
10 B ased on the Federal Reserve Board's industrial pro­
duction index for manufacturing.




are (based on the increase in actual tonnage
c o n su m e d ): c o ld -ro lle d sh e e ts, h ot-rolled
sheets, galvanized and other coated sheets,
plates, wire rods, and tin plate. However,
domestic consumption (net of imports) of only
one product, galvanized and other coated
sheets, has in creased at a rate greater than
the overall manufacturing index (4.9 percent
com pared with 4.5 percent). The growth of
all of the 11 product markets available to
domestic producers was affected by the rise
in imports. For exam ple, the small, but posi­
tive, increases in consumption of pipes and
tubing and bars becam e net market losses for
domestic producers, when the effects of
imports are considered. That is, despite the
increase in total domestic consumption, the
tonnage volume of these products supplied by
domestic producers was actually less in 1967
than in 1956, while the tonnage supplied by
imports was greater.
The differential rates of growth in product
markets affect producers in the seven Fourth
District SM SAs listed above. By combining
the information in Tables VII and VIII, and
assum ing that the steel mill plants in these
areas are responsive to changes in the re­
spective national product markets, it is ap ­
parent that the Hamilton-Middletown, Huntington-Ashland, and Mansfield SM SAs bene­
fited from gains in the markets for the three
types of sheet steel identified in Table VIII.
The data shown in Table IX su ggest that these
three areas, especially the Huntington-Ashland SMSA, experienced sizable employment
increases in the primary metal industries.
B ecause of the distribution of steel pro­
duction am ong many plants in the nation, it
is likely that the rem aining areas encountered
21

E C O N O M IC REVIEW

TAB LE V II
M a jo r Steel Produ cers a n d P rincipa l Products
Seven Fourth District S M S A s
1960*

SM SA

Producer

Principal Products
(in order o f greatest
to least plant capacity)

Erie

Erie Forge and Steel Corp.

Steel forgings
Steel castings

Hamilton-Middletown

Armco Steel Corporation

Hot-rolled sheetsf
Sheets-cold-rolled f
Sheets- g a Ivanized
Pipes and tubes-Spiralweld
Sheets-long terne

Huntington-Ashland

Armco Steel Corporation

Hot-rolled sheetsf
Sheets-galvanized f
Sheets-cold-rolled f
Plates-sheared

Johnstown

Bethlehem Steel Com pany

Bars (other than concrete reinforcement) f
Plates-sheared and universal
W ire rods
W ire products!
Freight and mine cars
W heels and axles (rolled)

Lorain-Elyria

United States Steel Corporation
National Tube Division

Pipe and tubing§
Seamless tube rounds
Skelp

Mansfield

Unviersal-Cyclops Steel Corp.
Empire-Reeves Steel Corp.

Hot-rolled plates, sheets, and stripf
Strip and sheets-cold-rolled
Sheets and coils-galvanized
Sheets and strips-electrical
Sheets-long terne

Steubenville-Weirf on

National Steel Corporation
W eirton Steel Comp. Div.

Coils for cold reduced black plate and tin plate
Tin plate-electrical
Sheets-cold-rolled
Sheets-galvanized
Structural shapes
Tin and terne plate-hot dipped
Black plate-ordinary

W heeling Steel Corporation

Coils for cold reduced black plate and tin plate
Sheets-cold-rolled
Black plate-ordinary
Tin plate-electrolytic
Hot-rolled sheets
Strip-cold-rolled
Sheets-long terne

* Latest year for which information is available.
f The relative importance of this product line may have changed as indicated
in the respective company’s annual reports since 1960.
| Includes plain and galvanized wire, wire nails, and fence posts.
§ Includes buttweld and seamless pipe and tubing and galvanized pipe.
Source: American Iron and Steel Institute

22FRASER
Digitized for


OCTOBER 1968

T A B L E V III
R o le o f Im p o r ts in A p p a r e n t C o n s u m p t io n o f S e le cte d Steel M i l l P ro d u c ts in the U n ite d S ta te s
1956-1967
Average Annual Rate
of Change in Apparent
Consumption
Apparent Consumption
(thousands of tons)
-------------------------------------------------------------------------------------1962
1958
1960
1964
1966
1967
1956
All steel mill products
Sheets-hot-rolled
Sheets-cold-rolled
Sheets-galvanized and
other coated
Black plate
Pipes and tubing
Plates
Wire rods
W ire products
Strip-cold-rolled
Bars-other than concrete
reinforcement
Tin plate-hot dipped and
electrolytic

80,239
8,520
1 2,902

58,789
6,147

71,531

10,009

13,603

3,010

2,916

667

516

9,555
7,467

6,324

7,961

72,639
7,753
13,358

+
+

1 .0 %
1.6

6.9

+

2.7

+

1.8

3.9

8.7

9.8

1.7
9.1

2.0

1.7
10.8

0.1

0.4

2.6

*

2.8

3.1
0.9
8.7

4,877

5,806

5,350

428

399

594

0.1

*

7,338
6,252

7,566
6,298

8,671

469
10,025

3.2

9,978

9,793
8,912

3.9
6.5

0.4

3.4

2.4

5.3
45.1
21.0

1,493

963

1,290

3,716
1,431

10,602

6,748

8,556

8,819

1,316
3,493

4,899

2,504

2,335

1.5
0.7
5.4

1,348

3,900
1,358

6.0
0.2

17.1
12.5
0.2

31.0
15.7
0.3

39.2

4,319
1,567

10,516

12,008

1 0,770

2.1

2.6

5.5

*

0.4

8,776
2,1 14
3,860

1,645

5,303

5,359

5,184

5,875

*

10.6
9.5
45.9

+ 5.9
— 0.3

+ 4.9
— 0.5

1 1.5

+
+

+
+

46.1
20.4

+ 7.3
— 0.1

+ 1-5
— 1.7

2.0

+ 0.5

+

0.4

+

1.3

+

0.4

+ 2.1

+

1.9

1.4

4.4

7.2

8.6

10.8

1.0

1.5

2.4

2.7

Source: American Iron and Steel Institute

T ABLE IX
Percent C h a n g e in E m p lo ym e n t in the
P rim a ry M e ta l Ind u stries
United States a n d Se ve n Fourth District S M S A s
1950-1960 and 1960-1966
Percent Change
19 5 0 -1 9 6 0 *

1 0 .9 %
16.2

20.0
1.4

17.6
0.3

* Less than 0.01 percent.




3.8

*

16,057

0.3
*

3,826

1,179
4,134

5,100

2 .1 %

+

7 .3 %
5.3

1 .7 %

1 1,477

15,905

+

5 .6 %
1.6

93,667

11,995
17,054

1 9 60-1 966

United States

+

3 .4 %

+

9 .3 % f

Erie

+

+

7.3t

Hamilton-Middletown

+

2.4
2.2

Huntington-Ashland
Johnstown

+ 3 4 .9
+ 3.5

-

2.3f§

Lorain-Elyria

— 19.2

+

l.lt

Mansfield

+

6.8

+ 10.1J

Steubenville-W eirton

+

2.7

n.a.

+ 11.5J
+ 3 1 .7 **

n.a. Not available.
* Bureau of the Census estimates of total employment in the
primary metal industries,
f W a g e and salary employment.
| Covered employment.
§ Includes SIC Industries 33-37.
* * Includes SIC Industries 33-34.
Sources: U. S. Department o f Commerce, Bureau o f the Census;
U. S. Department o f Labor; Division o f Research and
Statistics, O hio Bureau of Employment Services; Division
o f Research and Statistics, Pennsylvania Bureau o f
Employment Security

^ et
Imports
1 95 6 -1 9 67

1 2 .2 %

4 .7 %
2.6

99,024

9,956

195 6 -1 9 67

19.7
8.9

2 .9 %
0.4
*

87,943

3,356
498

5,039
1,060
3,448

4,819

Imports as a Percent of
Apparent Consumption
---------------------------------------------------------------------------------1956
1958
1960
1962
1964
1966
1967

1.7
3.5

0.8
2.3

E C O N O M IC R EV IEW

declining or sluggish steel product markets.
The employment setbacks in the primary
metal industries in the Lorain-Elyria SMSA,
for exam ple, reflect the net market loss and
production decline of pipes and tubing in
that area. The steel industry in Johnstown
specializes in bars (other than concrete rein­
forcement), plates, wire rods, and wire prod­
ucts. While Johnstown has probably benefited
from the dem ands of the Vietnam conflict for
plates and wire products, employment in the
primary metal industries in 1966 was still

similarly high 15.1 percent in Johnstown;11
in the Huntington-Ashland SMSA, the un­
employment rate was 13.3 percent.12 The
resumption of growth in these areas in the
1960's coupled with the effects of out-migra-

below the 1960 level.
The Steubenville-W eirton area produces
steel mill products that have experienced
differing rates of growth. Principal products in
the area include cold-rolled sheets and tin
plate, whose markets (net of imports) in­
creased at an average annual rate of 1.8
and 1.9 percent, respectively, during 19561967, and black plate, which has experienced
a declining national market. (Consumption
estimates for the principal product of the
steel industry in the Steuben ville-Weirton
SM SA —coils for reduced black plate and tin
plate—are not available.)
Unem ploym ent. Unemployment estimates

than the national rate, were reduced to about
one-third of 1959 levels.
In the remaining SM SAs, unemployment
rates have generally been below the national
average since 1965. The upturn in unemploy­
ment rates in all nine SM SAs and the leveling
of the national rate in 1967 represented a
reduced rate of expansion in m anufacturing
employment in general, especially in the
durable goods industries. From 1966 to 1967,
m anufacturing employment declined in four
of the SM SAs (see Chart 2 ).1*
Sum m ary. The specialized industrial and
product mixes of economic activity in the
nine SM SAs have produced differing reac­
tions to technological change, geograph ical
shifts in production and markets, and weak­
ened dem ands in certain national product

for the 1950's, if available, would likely in­
dicate that unemployment rates were rela­
tively high in those SM SA s that incurred the
loss of a major area employer or experienced
the decline of an important industry in the
area. Special surveys of selected areas classi­
fied three of the nine SM SAs as areas of
chronic and persistent unemployment in the
late 1 9 5 0 's. For example, at the end of the
first quarter of 1959, when the unemploy­
ment rate in the nation was at 6.4 percent, the
rate was a high 15.4 percent in Erie and a
2 4FRASER
Digitized for


tion helped to improve markedly the unem­
ployment situation. A s shown in Table X, the
unemployment rate in Erie has been below the
national average since 1965, after being
nearly two and one-half times greater in 1959.
Unemployment rates in Johnstown and Huntington-Ashland in 1967, although still greater

n U. S. Department of Labor, Chronic Labor Surplus
A reas: Experience and Outlook, July 1959.
12 George Iden, "Industrial Growth in A reas of Chronic
Unemployment," Monthly Labor Review, LXXXIX (1966),
pp. 485-490.
i:<In part, the different changes in the unemployment
rates of the nine SM SAs and the United States from 1966
to 1967 reflect different methods of estimation.

O CTOBER 1968
TABLE X
Rate of U n em ploym ent a s a Percent of C ivilian Labor Force
United States an d N ine Fourth District S M S A s
1960-1967
1960

1961

1962

1963

1964

1965

1966

1967

United States

5 .5 %

5 .5 %

5 .7 %

5 .2 %

4 .5 %

3 .8 %

3 .8 %

Erie

9.3

10.4

7.8

7.7

5.8

4.1

2.9

3.6

Hamilton-Middletown

6.9

9.1

8.0

7.5

6.0

4.5

3.5

3.9

Huntington-Ashland

12.1

12.3

10.7

9.0

7.9

6.5

4.8

5.2

Johnstown

12.9

18.2

15.1

10.6

7.1

5.7

4.6

5.3

6 .7 %

Lima*

n.a.

n.a.

n.a.

n.a.

n.a.

2.9

2.9

4.8

Lorain-Elyria

7.1

8.9

6.5

6.0

5.0

3.9

3.6

4.1

Mansfield*

n.a.

n.a.

n.a.

n.a.

n.a.

3.3

2.8

4.1

Springfield*

n.a.

n.a.

n.a.

n.a.

n.a.

3.1

2.8

3.3

Steubenville-Weirton

6.1

6.9

6.6

6.4

3.9

3.6

3.4

4.0

n.a. Not available.
* Estimated by Federal Reserve Bank of Cleveland.
Sources: U. S. Department of Labor; Division of Research and Statistics, Ohio Bureau of Employment Services; Division o f Research and
Statistics, Pennsylvania Bureau of Employment Security

markets. Major chan ges in all facets of the
coal industry plus specialization in industries
whose products encountered weak national
dem and resulted in major economic adjust­
ment problems in Johnstown, SteubenvilleWeirton, and Huntington-Ashland. While
Johnstown recently registered employment
gains after more than two decades of decline,
the Steubenville-W eirton area tended to b al­
ance out employment gains and losses during
the 1950's and has not yet evidenced su s­
tained employment growth. Reaction in the
Huntington-Ashland area was less severe, as
both coal mining and m anufacturing are less
dominant in the employment structure of the
area than in Johnstown and SteubenvilleWeirton. In addition, the products of the
primary metal industries in the HuntingtonAshland SM SA have not suffered from weak­
ened dem and to the sam e extent as Johnstown
and Steubenville-Weirton. However, the rela­
tively high unemployment rates in the Hun­
tington-Ashland area in recent years suggest



that out-migrations and expanding industrial
production were insufficient to overcom e em ­
ployment losses in the 195 0 's and the con­
tinuing growth of the labor force.
Three SM SAs labored under the loss of
major area employers. Erie lost major m a­
chinery producers and experien ced a dem ise
of activities in connection w ith.shipping on
the G reat Lakes. Nevertheless, although em ­
ployment has not returned to the levels of the
early 1950's, Erie is now experiencing rela­
tively rapid growth and correspondingly
lower rates of unemployment. Springfield,
too, recouped employment losses resulting
from plant closures, and recent expansion in
the transportation equipment industry repre­
sents a primary source of growth in that area.
In the Hamilton-Middletown area, a com bina­
tion of people leaving the area and expansion
in existing firms has improved the unem­
ployment situation; in fact, the HamiltonMiddletown SM SA has now recovered from
most of its earlier employment loss.
25

E C O N O M IC R E V IEW

Three metropolitan areas, Lima, LorainElyria, and Mansfield, have experienced more
consistent patterns of growth. Other than
interruptions that coincided with national
business recessions, employment growth has
been reasonably steady in the three areas
since 1950. Employment setbacks in the
primary metal industries in Lorain-Elyria were
more than com pensated for by other types of
industrial expansion in the area.

SELECTED MEASURES OF
E C O N O M IC ACTIVITY
V a lu e A d d ed . One m easure of the impor­
tance of m anufacturing in the nine metro­
politan areas is value added by m anufac­
turing. Differences in value added among the
areas reflect differences in industrial and
product mixes, volume of goods produced,
and the degree of capital intensity involved

in the production activities in the respective
areas. Among the nine areas, value added
by manufacture in 1965 was highest in the
Lorain-Elyria SM SA and lowest in the Sprin g­
field area (see Table XI). During the 19601965 period, Huntington-Ashland, Johnstown,
and Erie showed the largest percent in creases
in value added, considerably above the
national average.
Differences in labor productivity are su g ­
gested by the variation in value added per
employee in the nine SM SAs. As a m easure
of labor productivity, value added per em­
ployee in 1965 was highest in Lorain-Elyria
and the lowest in Johnstown. High value
added in Lorain-Elyria is due in part to the
importance of the are a's transportation equip­
ment and primary metal industries, two of the
most capital intensive industries in the United
States. The comparatively low value added

TABLE X I
V a lu e A d d e d by M an ufactu re
United States an d N ine Fourth District S M S A s
1965 and Percent C hange 1960-1965

1965
(mil. of $)

Percent
Ch ange
1 9 60-1 965

Value A d de d
Per Employee
1965
Dollars
$12,477

Percent
Change
19 60-1 965

United States.................................................

$225,366

+

3 7 .4 %

Erie...............................................................

518

+

44.5

13,248

+
+

2 2 .9 %

H a m ilt o n -M id d le to w n ...................................

446

+

20.3

15,872

+

26.6

H u n tin gto n -A sh la n d .......................................

360

+

51.8

14,063

+

23.8 f

J o h n sto w n .....................................................

283

+

45.5

11,012

+

51.3

L im a * ............................................................

253

+ 1 0 .9

16,013

+

9.6

L o ra in -E ly ria .................................................

642

+

31.4

18,772

+

16.2

M a n s f i e ld .....................................................

345

+

38.2

15,899

+

32.9

Sp rin gfield .....................................................

214

+

40.7

12,229

+

Steubenville-W eirton.......................................

483

+

24.9

15,581

+

33.2

19.1
18.I f

* Data are for Allen County, Ohio,
t D ata are for 1962-1965.
Sources: U. S. Department of Commerce; Division of Research and Statistics, Ohio Bureau of Employment Services; Division of Research
and Statistics, Pennsylvania Bureau o f Employment Security; Research and Statistics Division, W e st Virginia Department of
Employment Security


26


OCTOBER 1968

TABLE X II
C a p ita l Expenditures (N ew ) by M an ufactu rers
United States an d N ine Fourth District S M S A s
Annual Average
1958-1961
(mil. o f $)

1963
(mil. of $)

1964
(mil. of $)

1965
(mil. o f $)

United States.................................................

$9,460

$11,370.9

$13,263.3

$16,354.2

Erie...............................................................

18.2

18.2

19.9

29.9

H a m ilto n -M id d le to w n ...................................

34.3

16.5

31.8

26.0

H u n tin gto n -A sh la n d .......................................

25.2

105.7

43.0

41.1

Johnstow n.....................................................

1 2.6

19.7

1 1.9

17.0

L i m a ............................................................

10.8

13.8

8.6*

25.1*

L o rain -E ly ria .................................................

23.9

25.7

29.5

34.7

M a n s f i e ld .....................................................

15.2

20.1

18.9

26.2

Sp rin gfield .....................................................

n.a.

5.5

5.2

9.4

Steubenville-Weirton.......................................

30.0

58.6

110.0

108.5

n.a. Not available.
* Data are for Allen County, Ohio.
Source: U. S. Department of Commerce

per employee in Johnstown is associated with
the apparel industry in the area — an indus­
try that nationally is characterized by low
value added per employee — and the em­
ployment practices of manufacturers in the
area. Employment in manufacturing in Johns­
town was supported by a reduction in the
number of average weekly hours worked per
employee, a policy that helped to alleviate
the unemployment problem in the area by
allowing more people to work. However, a
reduction in average weekly hours probably
has a negative influence on value added per
employee.
Nevertheless, in terms of value added per
employee during 1960-1965, the Johnstown
SMSA showed the greatest gain, reflecting
in part an increase in the average hourly
workweek over the period as a whole despite
the reduction in hours referred to earlier.
Even so, the average hourly workweek in
Johnstown is below that in the nation as a



whole.14 Erie and Mansfield also showed
rates of increase considerably greater than
for the nation as a whole. In contrast, in four
areas — Springfield, Steubenville-Weirton,
Lorain-Elyria, and Lim a—the percent changes
in value added per employee from 1960 to
1965 were below the national rate.
N e w Capital Expenditures. Significant in­
creases were m ade in expenditures for new
plant and equipment in the SteubenvilleWeirton SMSA during 1963-1965 (see Table
XII). In fact, the four-year average of new
capital expenditures during 1962-1965 in the
Steubenville-Weirton SMSA (not shown in
table) was more than two and one-half times
greater than the average for the four preced­
ing years and largely represented new tech­
nology and additional capacity in the primary
14 The av erage hourly workweek in all manufacturing
in Johnstown w as 37.0 hours in 1960 and 38.1 hours in
1965, compared wiih 39.7 hours in 1960 and 41.2 hours in
1965 for ihe United States a s a whole.

27

ECON O M IC REVIEW

metal industries in the area. New capital
expenditures in all nine areas, except the
Hamilton-Middletown SMSA, were greater in
1965 than the respective annual averages
during 1958-1961.
A v e ra g e W eekly Earnings. A verage weekly
earnings of m anufacturing workers in all nine
SM SAs exceeded the national average in
1967 (see Table XIII). The comparatively high
levels of earnings reflect the heavy concen­
tration of workers in durable goods industries
in each of the SM SAs. As discussed earlier, a
shortened workweek and the influence of the
apparel industry exert a downward bias on
earnings in Johnstown. Only in the Sprin g­
field SM SA was the percent change in aver­
ag e weekly earnings from 1961 to 1967 greater

TABLE X III
A v e ra g e W e e k ly E arn in gs of
Covered W orkers in M an u fac tu rin g
United States an d N ine Fourth District S M S A s
1967 and Percent C hange 1961-1967
A ve rage W eekly
Earnings
1967
United States

$1 14.90

Percent
Change
19 6 1 -1 9 6 7
+ 2 4 .4 %

Erie

130.21*

+ 21.8

Hamilton-Middletown

160.43

+ 18.1

Huntington-Ashland

1 32.47f

+ 1 4 .5 J

Johnstown

115.90*

+ 17.5

Lima

135.44

+ 19.5

Lorain-Elyria

150.55

+ 15.6

Mansfield

140.71

+ 17.6

Springfield

139.03

+ 26.6

Steubenville-Weirton

154.40f

+ 13.2+

than the change in the nation. (The perform­
ance of the other SM SAs of course reflects
in part the higher starting b ase in those areas
in 1961.)
N e w C ar Registrations. The behavior of
new car registrations is one indicator of con­
sumer spending in a local area. In 1967, the
number of new car registrations in the areas
under review was greatest in the Erie SM SA
(see Table XIV). The lohnstown area also
registered over 10,000 new cars in 1967.
From 1961 to 1967, the Hamilton-Middletown SM SA experienced the greatest percent
increase in new car registrations of the nine
areas under review, and only the HamiltonMiddletown and Springfield areas exceeded
the percent increase in the nation.
Residential Construction. Trends in the
dollar value of residential construction con­
tracts provide some additional insights into
the economic perform ance of the nine areas
under review. As shown in Chart 3, resi­
dential construction in the United States has
TABLE X IV
N e w C a r R egistrations
United States an d N ine Fourth District S M S A s
1961 and 1967 and Percent C hange 1961-1967

1961

1967

Percent
Change
19 6 1 -1 9 6 7
+ 4 1 .2 %

Number of Cars

5,854,747

8,267,129

Erie

8,398

11,591

Hamilton-Middletown

5,869

8,589

+ 4 6 .3

Huntington-Ashland

6,164

8,594

+ 39.4
+ 4 1 .1

United States

+ 38.0

* First quarter only,

Johnstown

7,186

10,138

f 1966.

Lima

5,087

6,962

J Percent change 1962-1966.

Lorain-Elyria

6,919

9,726

+ 4 0 .6

Sources: U. S. Department of Labor; Research and Statistics Unit,
Kentucky Bureau of Economic Security; Division of Research
and Statistics, Ohio Bureau of Employment Services;
Division of Research and Statistics, Pennsylvania Bureau
o f Employment Security; Research and Statistics Division,
W e st Virginia Department o f Employment Security

Mansfield

4,528

5,549

+ 2 2 .5

Springfield

4,558

6,561

+ 4 3 .9

Steubenville-Weirton

4,838

6,197

+ 2 8 .1

Digitized for
2 8FRASER


+ 36.9

Source: R. L. Polk & Co. Further use of these d ata without the
express permission of R. L. Polk & Co. is forbidden.

OCTOBER 1968

C h a r t 3.

VALUE of RESIDENTIAL CONSTRUCTION CONTRACTS
U n it e d S t a t e s a n d

E i g h t * F o u rth D is t r ic t S M S A s

B i l li o n s o f d o l l a r s

25

S P R IN G F I E L D

________

-

H U N T IN G T O N - A S H L A N D

/
1... J

J O H N S T O W N

v

I

1956

L a st e n t ry :
*
* *

1

1

'58

1

1

1

1

1

L

I

AN N U ALLY
1

-

I

I

I

A

a / v

^

1

/

S T E U B E N V I L L E - W E I R T O N

A

-

I

V

\

1

'6 0

1

'6 2

1

1

1

64

1

'6 6

1

I

1

'68

AN N U ALLY

J___I___ I___L

1

'70

1956

’58

'6 0

J___ I—

'6 2

I___I___ I___L

'6 4

'6 6

'6 8

'70

1967

D a t a fo r M a n s f i e l d S M S A

a re n o t a v a ila b le .

N o t a v a ila b le .

S o u r c e o f d a ta :

F.W . D o d g e D iv is io n , M c G r a w - H i l l In f o r m a t i o n S y s t e m s C o m p a n y




29

E C O N O M IC R E V IE W

in creased fairly substantially since 1957, d e­
spite sluggishness in 1966 and 1967. Among
the nine SM SAs, Erie showed the sharpest
increase in residential construction, with the
dollar value of contracts in 1967 more than
double the 1960 volume. During the 1960's,
residential construction also increased a p ­
preciably in the Huntington-Ashland and
Springfield SM SAs. The sharp advances in
the Springfield area are associated with
apartment and dormitory construction. Resi­
dential construction declined in the HamiltonMiddletown area from 1959 to 1962, the same
period in which there was a loss of industry
and out-migration from the area. Since 1962,
however, residential construction has ex­
panded in the Hamilton-Middletown area.
Residential construction in the Lorain-Elyria
SM SA has been influenced by several factors,
including apartment construction, expanding
population and employment, and suburban­
ization of C leveland area residents. In the
rem aining areas — Johnstown, Lima, and
Steubenville-Weirton — residential construc­
tion has been relatively sluggish during the
1960's. For exam ple, in 1967, the dollar value
of residential construction contracts in Steu­
benville-Weirton was only 9 percent above

in general and durable goods production in
particular in those areas. The present article
reveals an even greater dependence on du­
rable goods production in nine other SM SAs
in the District than in the largest Fourth
District SM SAs, as well as in the nation as a
whole. Moreover, economic activity in the
nine SM SAs tends to be dominated by one or
two industries and single major producing
firms.
A brief review of a number of economic
indicators shows that since 1950 the nine
areas under review have experienced periods
of economic adjustment as well as periods of
economic expansion. In several areas, the
problems of adjustment, in part a response to
business conditions in the nation, were seri­
ously influenced by changing technology,
company relocations, and declining product
markets. The resiliency of the nine areas
differs markedly, as is evidenced by their
respective perform ances during the economic
expansion that b egan in 1961.
The adjustment problems of the Johnstown
and Steubenville-W eirton SM SAs have been
more pronounced than those of the other
areas, largely b ecau se of a heavy commit­
ment to industries that are growing slowly in

the 1960 level and was virtually unchanged
in Lima. In Johnstown, residential construc­
tion in 1967 was 4 7 percent below the 1960
dollar value of aw ards. (Data for the M ans­

the nation. Both the Johnstown and Steuben­
ville-Weirton areas have thus far been unable
to recast significantly their respective indus­
trial and product mixes, which appears to be
necessary if those areas are to achieve growth

field SM SA are not available.)

Earlier studies of the largest metropolitan
areas in the Fourth District revealed an in­

com parable to the other SM SAs. Despite the
recent loss of large industrial employers, the
Hamilton-Middletown area has experienced
employment and population growth during
the I9 6 0 's.

tense concentration of m anufacturing activity

In the other six SMSAs, economic expansion

C O N C LU D IN G CO M M EN TS


0


OCTOBER 1968

(including employment, population, and other
m easures) is being achieved either through
an intensification of the activities of the in­
dustries that are expanding nationally and
are already located in the areas, or through
a broadening of the industrial mix. As a case
in point, new capacity in the transportation

equipment industry has been a major impetus
to growth in the Lorain-Elyria and Sprin g­
field SM SAs since 1960. The areas that
appear to have been able to maintain eco­
nomic growth at or above the national rate
of expansion are: Erie, Huntington-Ashland,
Lima, Mansfield, Lorain-Elyria, and Springfield.

A P P E N D IX
D efinitions of N ine Fourth District S M S A s
Population
1965

SM SA

Counties
Erie County

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

255,000

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

208,000

Butler County

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

259,000

Cabell and W a y n e counties, W e st Virginia;
Boyd County, Kentucky; Lawernce County,
Ohio

Johnstown, Penn sylvan ia..................

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

270,000

Cam bria and Somerset counties

Lima, O h i o ...................................

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

171,000

Allen, Putnam, and V an W e rt counties

Lorain-Elyria, O h i o .........................

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

240,000

Lorain County

Mansfield, O h i o ............................

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

126,000

Richland County

Springfield, O h io ............................

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

147,000

Clark County

Steubenville-Weirton, OhioW e st V ir g i n ia ................................

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

170,000

Jefferson County, Ohio; Brooke and
Hancock counties, W e st Virginia

Erie, P e n n s y lv a n ia .........................
Hamilton-Middletown, Ohio

Huntington-Ashland, W est VirginiaK e n t u c k y - O h io ............................

Sources: Bureau of the Budget and U. S. Department of Commerce




31




Fourth Federal Reserve District