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Economic
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I FEDERAL RESERVE BANK OF ATLANTA
NOVEMBER 1982
4 BANK SIZE, BANK COSTS
COST STRUCTURE
A
^ RISK AND
MARKET SHARE CHANGES
A LARGE BANK ENTRY A PROFITS
OR MARKETSHARE? A PAYMENTS
SYSTEMS COSTS
Economic
Review
FEDERAL
RESERVE
BANK
O F ATLANTA
President:
William F. Ford
Sr. Vice President and
Director of Research:
Donald L Koch
Vice President and
Associate Director of Research:
William N. Cox
Financial Structure:
B. Frank King, Research Officer
David D. Whitehead
Larry D. Wall
National Economics:
Robert E. Keleher, Research Officer
Stephen O. Morrell
Mary S. Rosenbaum
Regional Economics:
Gene D. Sullivan, Research Officer
Charlie Carter
William J. Kahley
Database Management:
Delores W. Steinhauser
Payments Research
• Veronica M. Bennett
Paul F. Metzker
Visiting Scholars:
James R. Barth
George Washington University
James T. Bennett
George Mason University
George J. Benston
University of Rochester
Gerald P. Dwyer
Emory University
Robert A. Eisenbeis
University of North Carolina
John Hekman
University of North Carolina
Paul M. Horvitz
University of Houston
Peter Merrill
Peter Merrill Associates
Communications Officer:
Donald E Bedwell
Public Information Representative:
Duane Kline
Editing:
Gary W. Tapp
Graphics:
Susan F. Taylor
Eddie W. Lee, Jr.
The E c o n o m i c Review seeks to inform the public
a b o u t Federal Reserve policies a n d t h e economic
environment and, in particular, to narrow the gap
b e t w e e n specialists a n d c o n c e r n e d laymen. Views
expressed in the Economic Review aren't necessarily
t h o s e of this Bank or the Federal Reserve System.
Material may be reprinted or abstracted if the Review
a n d author are credited. Please provide the Bank's
Research Department with a copy of any publication
containing reprinted material. Free subscriptions and
additional copies are available from the Information
Center, Federal Reserve Bank of Atlanta, P.O. Box
1731, Atlanta, G a 3 0 3 0 1 (404/586-8788). Also contact the Information Center t o receive Southeastern
E c o n o m i c Insight a free newsletter on economic
trends published by t h e Atlanta Fed twice a month.
2
N O V E M B E R 1982, E C O N O M I C
REVIEW
•••••••••
Economies of Scale in Banking:
An Overview
4
Operating Costs in
Commercial Banking
6
Do operating costs shrink as a bank increases in
size? Are unit banks more expensive to operate
than branch banks? Does holding company affiliation affect costs? Some surprising results from a
major study.
Economies of Scale:
A Case Study of the Florida Savings
and Loan Industry
22
Bank Size and Risk:
A Note on the Evidence
32
A new study examines the cost structure of Florida
S&Ls. The evidence suggests some differences in
the cost structures of banks and S&Ls.
Is there a relationship between a bank's size and
its degree of risk? A review of the evidence.
Changes in Large Banks'
Market Share
The Impact of Local Market Entry by
Large Bank Holding Companies
41
35
If there are economies of scale in banking, larger
banks would be expected to capture larger shares
of local markets. A new Atlanta Fed study compares
larger banks' performance with smaller banks in the
same local markets.
An Alternative View of
Bank Competition:
Profit or Share Maximization
What happens to market share, profits, and risk
when a large bank holding company enters a local
market? Do holding company subsidiaries have a
competitive advantage?
48
Future Payments System Technology:
Can Small Banks Compete?
58
One theory holds that small banks seek to gain
market share, while large banks aim for profits. An
Atlanta Fed study tested the theory in southeastern
markets.
Will the explosion in payments system technology
favor larger banks and S&Ls? Not necessarily,
especially if smaller institutions are able to share
technology and services through networks
Statistical Supplement
V O L U M E LXVII, N O . 11
68
Economies of Scale i
Private institutions and public regulators alike
have been erasing boundaries between financial
institutions. Some40,000 depository institutions
are now able to offer a full range of consumer
financial services where there were only 13,000
in March 1980. With the recent enactment of
landmark banking legislation, another4,000 new
competitors (savings and loan associations) will
be able to offer banking services to businesses.
Besides these new competitors, nondepository
institutions have entered consumer and business
markets with an expanding variety of financial
instruments and services.
How many of these new competitors will prosper?
What will the survivors and the financial system
look like? The answers to these rather broad
questions depend, t o a great extent, on the
answer to a narrower question: do larger financial
institutions enjoy lower costs than smaller
institutions?
Evidence on this question will be vital to
thinking through the implications of future financial deregulation. For instance, how would
interstate deposit-taking operations by banks
and S&Ls affect the structure and competitive
health of the nation's financial system? Will large
institutions "gobble up" smaller ones, or will
smaller ones be able to remain competitive? Part
of the answer depends on whether the large
institutions can produce financial services more
cheaply than smaller ones—in the language of
economics, whether production of financial services is subject to "economies of scale."
This issue of the Economic Review concentrates
on present and future competition between
larger and smaller financial institutions. With remarkable consistency, the studies reported here
suggest that large size does not seem to give a
financial institution significant competitive advantages. This implies that, contrary to many
predictions, large banks and S&Lsare not likely to
4
drive smaller ones out of business as deregulation
progresses.
The first study, dealing with operating costs at
banking organizations, is presented by George J.
Benston, visiting scholar at the Federal Reserve
Bank of Atlanta and professor of accounting,
economics and finance at the University of
Rochester's Graduate School of Management;
Gerald A. Hanweck, economist, Board of Governors
of the Federal Reserve System, and David B.
Humphrey, chief of the Federal Reserve Board's
Financial Studies Section. They estimated costs
for branch and unit banks (unit banks are individual banks in states that prohibit bank branches)
and tested for the impact of bank holding company affiliation on costs. They found that costs
per account for banks larger than $50 million in
deposits increased as bank size increased, while
costs declined with size for banks with less than
$25 million in deposits.
^
In the second article, James E. McNulty, assistant vice president and economist, Federal Home
Loan Bank of Atlanta, reports on a new study of
the cost structure of savings and loan associations.
M c N u l t y found decreasing costs forS&Ls with up
to about $500 million in deposits but did not
fully account for normal methods of expansion.
Above the $500 million level, costs increased
slightly.
Larger S&Ls, then, may capture some economies
of scale if they can expand significantly w i t h o u t
adding a proportionate number of branches.
Since S&Ls specialize in low activity functions
such as mortgages and savings accounts, McNulty
suggests, these results are not likely to be carried
over as S&L operations broaden to include transactions accounts and business and consumer
loans.
Following McNulty's study, David D. Whitehead,
senior financial economist Federal Reserve Bank
of Atlanta, and Robert L Schweitzer, assistant
N O V E M B E R 1982, E C O N O M I C
REVIEW
r
: An Overview
professor of economics, University of Delaware,
survey the evidence linking size and risk in
banking. Operating cost studies fail to consider
the relationship between risk costs and size in
financial institutions. Greater risk requires greater
compensating returns to shareholders and other
providers of funds and thus may put riskier
institutions at a competitive disadvantage. In their
review of the sparse evidence found in studies of
credit risk, interest rate risk, bank capital adequacy,
and early warning systems for problem banks,
Whitehead and Schweitzer found little evidence
that small banks operate with greater risks that
cannot be controlled.
Moving from studies of relationship between
size and costs to the playing out of competition
in the real world, B. Frank King, research officer at
the Atlanta Fed, asks how well larger banks in
local markets have performed versus the smaller
ones over the past decade and a half. Citing
evidence from several studies, including the
Atlanta Fed's new study covering southeastern
markets between 1974 and 1981, he concludes
that larger banks generally have lost market share
to smaller local competitors. The evidence supports
that conclusion for any subperiod, any area of
the country and any type of market studied over
the past 15 years.
Carrying the consideration of one-on-one competition a step further, King then looks at the
impact of large bank holding companies' acquisition
of local banks in three southeastern states. King
studied two types of banks—de novo (newly
organized) banks and large banks acquired by
large holding companies. He compared them
with similar independent banks in the same
markets. The evidence indicated that after several
years the holding company subsidiaries did not
generally differ from the independents in size,
profitability or risk.
If smaller banks operate with different goals
than larger ones, the smaller banks may be able
FEDERAL RESERVE BANK O F A T L A N T A 5
to survive despite some competitive disadvantages,
according to another study. It also found that
small banks may contribute a competitive element
that would be lost with their demise. David D.
Whitehead tested indirectly the theory that small
banks attempt to gain market share at the expense
of profits, while large banks seek profits even if
they must sacrifice market share. He found
evidence consistent with his hypothesis that
small banks emphasize market share. Smaller
banks may survive even if they do not earn quite
so much as larger ones. They may also create
significant price competition.
The final study in this issue takes a forward look
at payments system technology and tries to
project the impact of this important and rapidly
changing segment of financial institutions' operations on their competitiveness. Paul F. Metzker,
an economist on the Atlanta Fed's payments
research team, foresees substantial and growing
economies of scale in the production of payments
services. However, he also expects small institutions to capture the benefits of scale by sharing
production facilities through networks, service
bureaus and franchises. He finds evidence that
small banks already are moving toward shared
facilities.
These studies present considerable new evidence on competition between small and large
institutions—and that evidence generally is consistent. Large institutions do not seem to have
enjoyed significant competitive advantages over
small ones even in the recent past. Further, in the
important business of payments services, smaller
institutions seem likely to keep up despite broad
technological changes. This evidence indicates
that interstate banking is not likely to produce
rapid consolidation of institutions or to greatly
increase productive efficiency or safety for the
financial system.
Operating Costs
in Commercial
Banking
Evidence indicates that
bank operating costs,
when adjusted for normal
methods of expansion,
increase with size in
banks with deposits of
$ 5 0 million or more.
6
Reasons for Concern with Banks'
Operating Costs
In most businesses, operating costs are a private
matter. In banking, though, these costs receive
wider attention. A bank's managers and owners
clearly are concerned with costs since they profit
if costs are controlled. A bank's customers also
are concerned, since banking costs ultimately
are passed on to users of the bank's services. In
addition, legislators and those charged with bank
regulation have a derivative concern; the more
efficiently banks are operated, the larger the
earnings flows that may improve safety by absorbing losses, the more efficiently the nation's
payments system works and the more efficiently
savings are channeled into investment.
NOVEMBER 1982, E C O N O M I C
REVIEW
Large versus Small Institutions
Legislators and regulators also have a direct
concern with banks' operating efficiency, because
efficency may influence the way specific regulations
are enforced. In particular, if larger banks produce
a given level and quality of services at a lower
cost than smaller banks—that is, if banking is
subject t o economies of scale—then larger banks
could offer lower prices or more service than
smaller banks. In an unrestricted environment,
larger banks might well displace the small banks,
reducing competition. If these economies of
scale are large enough, the savings of resources
might offset anticipated reductions in competition.
However, if economies of scale aren't significant,
a policy of unrestricted chartering (free entry)
would probably not result in failure of new banks
due to their inherent inability to compete successfully with larger banks. Instead, failure would be
associated more w i t h management skill and
specific economic events than with the scale of
operation.
Form of Organization—Branching and Holding
Companies
Financial institutions' operating costs also may
be related t o their form of organization. Information on this relationship is important for states
trying to decide what type of bank branching and
bank holding companies they will allow, and for
the federal government as it considers various
proposals for interstate banking. Branches, independent banks and bank holding company subsidiaries may all have different relationships
between size and operating costs per unit of
output. Branches, in particular, may be more or
less costly to run than similar sized unit banks
(banks without branches). Or very small branches
may be more efficient than small unit banks,
while large branches may be less efficient than
similar sized unit banks. And, even if branches
were more costly t o operate, they might permit a
bank t o grow and take advantage of economies
of scale, the savings from which could offset the
presumed extra costs of branching. Considering
the costs of holding companies' operations is
important, since they are an alternative t o branching.
on individual products is required; some other
questions require information on the bank as a
whole. In some cases, the costs and amounts of
various services must be separated so that institutions producing different types and quantities
of outputs can be compared meaningfully. Estimates of the production cost of a specific service,
such as mortgage lending, are desirable in a
market analysis for a particular product. For
example, in considering competition between
commercial banks and savings and loan associations, the possibilities for economies of scale in
mortgage lending and time deposits are of primary
concern; the costs of many other banking services
may not be important.
". . . if banking is subject to
economies of scale—then larger
banks could offer lower prices
or more service than smaller
banks."
Aggregating the costs of multiple banking services is necessary to determine if a financial
institution as a whole is subject to economies of
scope. These economies occur when several
products (such as time and demand deposits or
demand deposits and business loans) are produced together at a lower total cost than when
produced separately. If there were significant
economies of scope in producing, say, business,
consumer and mortgage loans in one operation,
specialized institutions such as S&Ls w o u l d be
less efficient than full-service commercial banks.
The c o m m o n production of transactions in corporate and government securities also could give
rise to economies of scope. This has implications
for public policy regarding the powers allowed
thrift associations and commercial banks as well
as for mergers between different types of insti1
tutions.
Multiple Products
Results of a Current Bank Cost Study
Banks produce multiple products. To answer
some of the above questions, cost information
This study reviews research on bank costs and
reports on a recently published study by the
7
FEDERAL RESERVE B A N K O F A T L A N T A
authors. Consecutive sections address the technical problems of defining and measuringoperating
costs and output, estimating operating efficiency,
and obtaining appropriate data for cost analysis.
The article then reports the finding of our latest
study and discusses them in relation to other
recent studies of bank operating costs. Results
and implications of the analysis are summarized
on page 21.
The important objectives of bank cost studies
have been to determine: (1) the extent that the
scale of bank operations affects bank costs; (2)
the effects of branching and holding company
organization on costs; (3) the cost effects of
banks producing multiple services; and (4) the
effects of different types of bank customers on
bank costs. A number of fundamental problems
are common to all bank cost studies as well as
cost studies of other industries. Fortunately,
measurement problems are not great using data
from the Federal Reserve's Functional Cost Analysis (FCA) program.
• The most recent research (using 1975-78 FCA
data, a more flexible estimating functional form,
and a theoretically supportable index number
method of aggregating the various banking outputs) generally confirms many of the results of
previous research. New results are summarized
as follows:
(1) Banks with more than $50 million$75 million in deposits in unit banking
states experienced diseconomies of s c a l e that is, average costs increased as the
banks increased in size.
(2) Banks of all sizes in states that allow
branch banking experienced economies
of scale with respect to the numbers of
deposits and loan accounts.
(3) When the mode of e x p a n s i o n increasing the number of accounts or the
number of offices for branching banks but
only expanding the number of accounts
for unit banks was accounted for, banks in
both branching and unit states above $50
million-$75 million in deposits experienced
diseconomies of scale.
(4) Economies of scale appeared to be
unchanged over the 1975-78 period.
(5) Larger account sizes for both types
of banks increased costs less than proportionately.
(6) Average costs (unadjusted for certain
differences in branch and unit banks)
were similar for banks with up to $75
8
million in deposits in branch and unit
states; larger banks in branching states had
considerably lower average costs than similar banks in unit states.
(7) Taking into account the different
ways that branch and unit state banks can
expand—by increasing offices or average
account size, respectively—average costs
were similar among banks of similar size in
unit and branching states.
(8) Bank holding c o m p a n y affiliation was
found to have little effect on bank costs.
Definition and Measurement
of Operating Costs and Output
Measuring Operating Costs
Public and private policy questions require
numbers that meaningfully reflect economic
values rather than accounting measurements.
Regulators and bankers should be concerned
with "opportunity costs," the value of resources
given up because of a decision to do one thing
rather than another. For example, the cost of
making and servicing a mortgage loan is the
dollar value of resources that, as a consequence,
cannot be used for the next best opportunity.
Where outlays are made in cash or in close
equivalents (e.g., the present value of promises
to pay cash in the future) for such expenses as
salaries, supplies and computer services, the
accounting numbers reflect economic values
well, since the amount of cash used for the stated
purpose is no longer available for another.
Other costs may not be so well reflected,
however. For example, the economic cost of the
space occupied by the mortgage loan department is not well measured in accounting statements. These statements include depreciation,
an essentially arbitrary allocation of a portion of
the original cost of the building and equipment
to a given activity over a specific time period.
These figures seldom provide valid estimates of
the present economic cost of using the building.
This cost is measured by the bank's next best
opportunity. This would be the amount that it
would receive if it rented out the space occupied
by the mortgage department or the amount it
could save by giving up space occupied by
another function that could be moved into the
mortgage department's space. Other costs that
may be similarly misstated are inventories valued
N O V E M B E R 1982, E C O N O M I C REVIEW
at acquisition cost and salaries and other tax
deductible compensation that are substituted
for dividends. Clearly, opportunity costs involved
in these situations are very difficult and often
impossible t o measure.
Even when costs are measured reasonably
well, it often is very difficult to assign them to
specific types of output with reasonable accuracy.
For example, the cost of employing the bank
president might be measured correctly if the
present value of his pension and other fringe
benefits were accounted for along with his salary.
But how much of the president's compensation
should be charged to demand deposits, business
loans, mortgage loans, and the other banking
functions? Even if one could keep track of the
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. . it is often very difficult to
assign [costs] to specific types
of output with reasonable
accuracy."
president's time, there is no reason t o expect a
direct relationship between the time spent with
a department and the value of the president's
services to the bank. Similar problems beset the
allocation of other overhead costs.1
Fortunately, the divergence of the numbers
that can be obtained (accounting data) from
those that one wants (economic values) is relatively small for financial institutions. Salaries,
which can be measured by accounting numbers,
comprise about 52 percent of commercial banks'
operating costs (excluding interest and loan and
security losses). Occupancy expense, including
building depreciation, represents only 9 percent
of those costs.2 The cost of supplies and goods
sold, a large part of most other enterprises' costs,
is negligible for financial institutions. Thus, except
for a relatively small amount of depreciation and
the inherent difficulty of assigning costs to specific
' S e e Benston (1982) for a more c o m p l e t e description of the difference
b e t w e e n e c o n o m i c values a n d accounting numbers.
Federal Reserve, Functional Cost Analysis: 1 9 7 8 Average Banks, p.
20. The percentages are almost the same for other years 1978 figures
are used here because data for this year are analyzed further below
2
FEDERAL RESERVE B A N K O F A T L A N T A
outputs, the accounting numbers recorded on
financial institutions' books provide reasonably
good proxy measures of economic values.
Further problems arise because not all costs of
producing financial services are recorded on the
institutions' books; however, these problems are
considerably less than those for cost studies of
other firms. Two problems specific to financial
institutions' costs arise from the possible tradeoffs between revenues and expenses included in
operating costs. With respect to lending operations,
for instance, higher expenses for monitoring and
collecting loans can substitute for higher loan
losses. To the extent that this substitution is
made, operating expenses will be higher, since
actual loan losses are not considered operating
costs, but are charged t o reserves. As an alternative, higher loan losses could be compensated
for with higher interest and fee income. In this
event, not only must loan losses be excluded from
operating expense, but higher losses need not
even be associated with lower monitoring (operating) expenses.
Interest and other payments for deposits present
the second problem. These payments are returns
to depositors on their investments, as much as
dividends and capital gains on mutual funds
shares are returns to shareholders. The bank is
merely an intermediary, as is a mutual fund.
While interest is an important outlay to the bank,
it is determined by market forces that reflect
alternative investments available to depositors.
Thus interest is not an operating expense for
purposes of measuring banks' efficiency. However, the amount a bank can pay its depositors in
the form of interest is constrained by law. For this
and other reasons such as personal income taxes
and administrative efficiency, banks may pay
customers for their deposits in the form of "free"
services, preferred lending arrangements (including lower interest charges) or more convenient
banking facilities. "Free" services result in higher
operating costs while preferred lending arrangements result in lower revenue. A similar problem
may affect the recorded expenses of banks that
get services from other banks in exchange for
compensating balances.
Differences in incurring and recording operating costs may produce misleading conclusions
about bank efficiency if the differences are
related systematically to the size or organizational
form of the institution. Fortunately, this seems
not to be the case, at least with respect to the size
of banks. For banks with deposits up to $50
9
million, from $50 to $200 million and over $200
million, occupancy expenses average 9.0 percent,
9.7 and 9.7 percent of total operating expenses. 3
For these same bank size groupings, the five-year
average amount of loan losses, expressed as
percentages of loans outstanding, are .15 percent,
.16 percent and .21 percent. The reported gross
yields on loans for these banks average 9.8
percent, 9.8 percent and 10.2 percent. 4 Thus the
relatively larger loan losses at banks with deposits
over $200 million appear t o be compensated for
by higher yields.
Nor does the understatement of respondent
banks' operating expenses (since they pay for
some correspondent bank services with compensating balances rather than with fees) appear to
distort the cost data with respect to bank size. In
t w o previous studies, the opportunity cost of
these balances was computed and added to the
banks' operating expenses; this adjustment had
no significant effect on the estimates of economies of scale.5 Hence, we conclude that bank
operating costs, as usually reported, measure
economic values reasonably well and, to the
extent they do n o t appear not to bias economies
of scale estimates. A major problem is the
exclusion of the cost of customer inconvenience
when there are too few banking offices available
due t o legal restrictions on banking.
Measurement of Output—What Do
Banks Really Produce?
Measuring output is a more difficult problem.
One's view of what banks produce depends on
one's interests. Economists w h o are concerned
with economy-wide (macro) issues tend t o
view the banks' output as dollars of deposits or
loans. Monetary economists see banks as producers of money—demand deposits. 6 Others
see banks as producing loans, with demand
and time deposits being analogous to raw
materials. 7 Thus banking statistics are reported
and banks described in dollar terms, as a
"million-dollar bank." Customers also often describe the output of a bank in dollar terms, since
3
lbid.
Ibid, p. 5.
Flannery (1981) and Benston, H a n w e c k a n d H u m p h r e y (1982). Dunham
(1982) also made this correction but did not estimate total bank cost
output elasticities for t h e bank as a whole.
6
For example, s e e Goldschmidt (1981).
' S t u d i e s that employ this definition (e.g., Greenbaum, 1967) are reviewed
4
5
they hold so many dollars in deposits or want t o
borrow a given amount of money.
But banks do not incur operating costs directly
as a function of the number of dollars of
deposits or loans they process. The cost of
accepting and collecting a deposited check is
affected only slightly by the number of digits
that appear around the decimal point. While a
$10,000 check involves somewhat more risk to
process than a $10 check, the extra cost is not
1,000 times greater. Similarly, a $100,000 loan
may involve more careful administration than a
$ 10,000 loan, but not by a factor of 10. Indeed,
with respect t o operating costs, a bank is best
described as a recordkeeping and processing
"factory." The key cost-causing output variable
is the number and types of pieces of paper and
electronic signals processed.
Though not proportionately so, the dollars
written on the paper processed are also relevant. The risk, should a deposit be mishandled,
a check not collected, a loan not repaid, or a
security defaulted, is related positively t o the
amount of the check, loan or security. The
amount of services a bank is willing to give t o its
depositors in lieu of direct interest payments
(which are legally prohibited or restrained)
also is a function of the value of the deposit.
Therefore, to be complete, the dollar amount
as well as the number of items and accounts
processed should be considered operative costcausing factors.
Which particular variables are taken t o measure output? It
depends on the question
asked. For the regulatory and bank management questions posed above, the preferred
measure is that which yields answers to such
questions as, " w h a t are the operating costs of
large compared to small banks, of branches
compared to unit banks, automated teller machines compared t o bank offices, of banks
compared to thrift associations, and of combinations of financial institutions?" To answer
these questions, we must attempt t o relate the
costs incurred by various institutions to the
same set of cost-causing activities. For these
purposes, it is meaningless t o report that a large
bank enjoys lower costs per dollar of loans than
a small bank if this " e c o n o m y " is achieved
because the large bank makes larger loans.
Most operating costs are related to the loan, as
such, rather than to its a m o u n t Comparing the
efficiency of a large and small bank in this
manner is like comparing costs per dollar of
below.
10
N O V E M B E R 1982, E C O N O M I C
REVIEW
sales of a wholesaler selling by the case and a
retailer selling by the item.
Measurements of operating costs per dollar
can be useful, however, since the lower cost
per dollar loaned may explain why interest
rates are lower on larger loans. But unless the
size of loans or deposits is expected t o change
as a consequence of a regulatory or business
decision, the variables used to measure output
should refer to the ongoing factors that generate
operating costs.
Any analysis of the output of financial institutions, then, should be multifaceted, and
should include the numbers of deposit items
processed and loans made and serviced. Collateral banking services, such as trust and safe
deposit boxes, also should be accounted for. If
different institutions are compared, differences
in the levels and qualities of their outputs
should be considered. And, because the costs
incurred are functions of local economic conditions and the value of the dollar over time
(when data for different time periods are used),
the recorded costs should be adjusted for the
effect of price-level factors.
Problems of Estimating Operating
Efficiency
Two basic problems beset researchers w h o
would analyze operating cost. One is accounting for differences among banks with respect
to the amounts of costs recorded and the types
of outputs produced. The second is accounting
for differences in costs related to unique attributes of specific banks or markets rather than
to general attributes, such as size and type of
organization. For instance, a bank may have
grown large because it was run efficiently,
possibly because of the genius of particular
individuals. Their compensation for superior
abilities would not be included in current
operating costs if it was paid for w i t h stock
options or if it occurred in the past. The cost of
these factors may have been expensed in the
past or may have been fortuitously acquired.
That such banks currently achieve low operating
costs and have grown large does not necessarily
mean banking is characterized by economies
of scale. Similarly, lower operating costs and,
say, small size, could be associated jointly with
characteristics of the markets in which banks
operate. Thus small towns may have both
lower wages and small banks. This relationship
FEDERAL RESERVE B A N K O F A T L A N T A
"Operating cost is taken to be
adequately measured by the
amount reported in the bank's
earnings statements."
is not an indication of economies of scale, since
banks in small towns cannot effectively serve
customers w h o live in distant large cities.
Fortunately, these problems are not serious
for studies of financial institutions' costs. The
technology and managerial methods used by
banks are generally well-known and available.
Furthermore, branching and chartering laws
restrict banks to given geographic areas for
deposit services. Except for large business
loans, their markets are constrained by the cost
t o customers of dealing with banks far outside
their communities and the cost t o banks of
acquiring information about and monitoring
distant customers. Thus banks tend to be large
or small because of the markets in which they
operate. The operating cost and output data,
therefore, are likely to trace out cost curves
from intersections of supply and demand curves
rather than tracing out demand curves.
The problem of accounting for factors that
produce differences among banks in recorded
costs and types of output is dealt with in t w o
ways. W i t h respect t o cost, one way is to
assume, usually implicitly, that these differences
either are trivial or are not systematically related t o bank output. Operating cost, then, is
taken to be adequately measured by the amount
reported in the banks' earnings statements.
The bias in this simple "solution" is not likely to
be serious, at least with respect t o bank size.
However, differences among individual banks
should be kept in mind. In situations where
differences may be important, the data should
be adjusted and checked to see if perceived
differences are systematically related to the
variables at issue.
W i t h respect to output, t w o approaches of
measuring comparative bank efficiency have
been followed. In one, differences among banks
are assumed to be unimportant. Total costs of
producing outputs such as deposits or loans
11
are divided by total outstanding amounts of
these outputs. This gives costs per dollar of
output, which are taken to be a valid measure
of operating efficiency. The unit costs are
presented in tables (tabular analysis) comparing
banks grouped according to a variable of interest
(for example, deposit size). The second approach
uses the statistical method of multiple regression
analysis to account for differences in output in
order to isolate the scale effect from other costcausing factors. The advantages, shortcomings,
and findings of each type of analysis are presented in the next t w o sections.
Data for Cost Analyses
All Bank Aggregate Data
Since all chartered financial institutions regularly report income, expense and balance sheet
data, measuring operating efficiency as total
recorded costs divided by total deposits, loans
and securities, or assets has considerable advantages. In studies using this method, costs
per dollar typically are averaged for banks
grouped by deposit size and compared in
tables (hence, tabular analysis). This procedure
was followed by Alhadeff (1954), who published
the first study of bank operating costs, using
California data from the years 1938-1950. But
this comparison does not account for differences
among banks, such as the composition of their
earning assets, deposits, type of organization,
and location. Horvitz (1963) replicated Alhadeffs
study with data from all Federal Reserve member
banks for 1949-1960. He subdivided the 1959
data into branch and unit banks and into three
groupings according to the ratio of time to total
deposits. Other variables were not accounted
for. Assuming that these other variables are not
important or are unrelated to size, Horvitz
found (as did Alhadeff) that "once a bank
reaches the relatively small size of $5 million in
deposits, additional size does not result in
reduced costs to any great extent until a bank
reaches the giant size of over $500 million"
(p. 37), and that branch banks have uniformly
higher costs per dollar of loans and investments
than unit banks. But, as the more complete
statistical analyses reported below indicate,
the assumptions necessary for this exercise are
not likely t o be valid.
12
FCA Data
One important shortcoming of the data used
in these early studies is the lack of detail with
respect to specific banking outputs. Fortunately,
a rich source of data on the costs of major
banking functions has been available since the
late 1950s. The Federal Reserve provides banks
with a Functional Cost Analysis (FCA) service in
which the banks allocate costs and revenue to
specific banking functions. These figures are
then structured into a standard format that
may be compared to other reporting banks.
The FCA program is voluntary, with 780 banks
responding nationwide in 1978.
Among the data allocated to the banking
functions are itemized revenue, expense, dollars
of deposits and assets (averages of 12 month
end amounts), and the number of accounts
opened and items processed. Thus, these data
provide a wealth of detail that permits the
analyst to improve upon potentially misleading
tabular analyses.
However, even though FCA figures are aggregated by three bank deposit sizes, a comparison
of the numbers must rest on several possibly
untenable assumptions. One is that the banks'
organizational structure is not relevant, since
branch and holding company banks are not
distinguished from unit banks in the published
results. Another is that the location of a bank
(e.g., urban or rural) does not affect its costs.
Third, the analyst either must remove the
allocated overhead expenses or accept the
essentially arbitrary allocations made in the
FCA data. Perhaps most important for a measure
of efficiency is that output can be measured
with only one variable for each type of p r o d u c t number of accounts serviced, number of items
"We measured output using
the average number of deposit
and loan accounts serviced,
augmented with information
on the average balances of the
accounts."
NOVEMBER 1982, E C O N O M I C
REVIEW
processed, or dollars of account balances outstanding. The joint effect of items processed,
accounts serviced and dollars outstanding cannot be simply measured. In order to assess the
joint effect of these variables, economists w h o
have used these and other data employ multiple
regression analysis.
Findings of a Recent Study8
The Model
W e recently specified and estimated a bank
cost function using multiple regression analysis.
We used annual Federal Reserve FCA data for
the years 1975 through 1978 involving from
747 to 852 banks, amounting to about 15
percent of the Federal Reserve members. Since
this program is voluntary, the banks included
are likely t o be more conscious than most of
the value of cost control. The banks range up to
$1 billion in deposits, since the few banks in
the FCA panel larger than this were excluded.
Thus, the sample covers the range of U. S.
banks except the giants, and it is perhaps
overrepresentative of more efficient banks due
to the voluntary nature of the FCA program.
Operating cost was defined to exclude interest
and loan losses—since only the outputs of the
banking deposit and loan functions were analyzed, the direct and allocated costs of the
functions of safe deposit box, trust, customer
computer services and investments were also
excluded. The included outputs account for
more than 72 percent of total operating costs.
W e measured o u t p u t using the average
number of deposit and loan accounts serviced,
augmented with information on the average
balances of the accounts. Since w e wanted to
estimate the relationship between total operating cost and output (and other variables), we
had to construct an index to represent the
multiple products produced by banks. For this
purpose we employed the technique suggested
by aggregation theory (see Diewert, 1976 and
Barnett, 1981) to construct a Divisia multilateral
index number of bank output. In effect, w e
weighted the number of accounts of each of
the five types of output (demand deposits,
time and savings deposits, real estate loans,
installment loans, and business loans) by their
proportionate share in total operating costs
using the FCA data. 9 The Divisia Index number
of accounts provides a valid measure of the
aggregate cost-causing transactions undertaken
by banks for their customers. Including the
average size of accounts serves as a control for
activities that are related primarily to the dollar
amounts of the accounts.
Differences among the banks in the prices of
inputs were accounted for with variables that
measured the average annual salaries plus
fringe benefits paid per employee and an index
of regional office floor space rental costs—the
opportunity cost per square foot of bank building
space.
Two types of organizational differences were
recognized. The effect of multibank holding
company (MBHC) affiliation on operating cost
was captured with two variables, one of which
measures its effect on total cost and the other
its interaction between branching and M H B C
affiliation. The costs of branching also were
accounted for in t w o ways. First, the data were
analyzed separately for banks in unit banking
states and banks in states that permitted branch
banking. This procedure avoids forcing the
estimated parameters to be equal for branch
and unit state banks, a common (but incorrect)
assumption of other studies. Second, interactions
between the number of offices and output
were specified so that the effect of branching
was not measured as merely a simple and
constant percentage of total cost. W e believe
that absence of this more general branching
specification seriously mars the findings of
previous studies whose effect was t o assume
that the cost of adding a branch office was a
constant percentage of total operating costs.
Thus the cost to a larger bank of adding a
branch of a given size w o u l d always be proportionately greater than the cost of adding the
same size branch to a smaller bank. 10 Our
specification allows the cost of an additional
branch, as a percentage of operating costs, to
vary across different sized banks.
Finally, the functional form fitted, the translog
cost function, is designed t o permit increasing
"See Benston, Hanweck a n d Humphrey, 1982, for details.
For example. Longbrake a n d Haslem (1975. Table 2) estimate the
d e m a n d deposit cost of an additional branch at a bank having from t w o to
five branches as S 1 2 5 3 while the same sized additional branch at a bank
having b e t w e e n twenty-five a n d fifty branches is $3,760
,0
"Details of this study may be found in Benston, Hanweck and Humphrey 1981
a n d 1982.
FEDERAL RESERVE BANK O F A T L A N T A
13
Table 1. Scale Economy (Elasticity) Estimates, Unit and Branch States Banks, 1978 FCA Data
Deposit
Size Group
($ millions)
Operating Cost
Number of
Accounts
A. Unit State Banks
$0-10
10-25
25-50
50-75
75-100
100-200
200-300
300-400
400+
Total Sample
Including Interest
Dollars of
Accounts
Operating Cost
Number of
Accounts
Excluding Interest
Dollars of
Accounts
.95
1.01
1.07
1.11*
1.13*
1.19*
1.19*
1.24*
1.23*
1.09*
.73*
.82*
.88*
.92°
.96
1.01
1.06
1.06
1.12
.92°
.95
.98
1.00
1.01
1.03
1.05
1.08°
1.06
1.09
1.01
B. Branch State Banks
.81*
$0-10
.89°
10-25
.93*
25-25
.93*
50-75
.92*
75-100
.94
100-200
.92
200-300
.93
300-400
.92
400+
.92*
Total Sample
.63*
.74*
.81*
.84*
.85*
.89*
.90
.93
.94
.84
.81
.95*
1.02
1.04*
1.05*
1.06*
1.06*
1.05
1.04
1.04*
.96°
.95*
.96*
.98*
1.00
1.02
1.09*
1.13*
1.13*
.97*
1.01
1.02
1.02*
1.02*
1.01*
1.01
1.00
.99
.99
1.02*
Notes: a. Source - Benston, Hariweck a n d Humphrey 1981 a n d 1982
*(°) Indicates elasticities different from 1.0 (constant costs) at the 0 5 ( 1 0 ) c o n f i d e n c e level in a t w o tail t-test
and/or decreasing costs to be measured as
output increases, as well as t o provide estimates
of economies of scale, of branching, and of
account size that are permitted to vary by size
of bank. It is not constrained to meet the
requirements of a particular production function,
such as the Cobb-Douglas function which was
almost exclusively used in earlier studies.
Three principal shortcomings of this study
must be emphasized. One is that the data
include only the fraction of U. S. banks that
participate in the FCA program. The other
shortcomings are that estimates of economies
of scope have not been separated from estimates
of economies of scale and that scale economies
of individual banking functions are not separately estimated. These analyses are in progress.
Since economies of scale and average costs
per account can and do differ for each bank,
derived estimates of economies of scale and
14
other parameters from the regression estimates
were based on unit and branch banking state
subsamples for nine deposit-size groups. The
relevant measures were then calculated for the
(geometric) average bank in each group. The
following findings may be drawn from our
analysis.11
Economies of Scale
•
Banks in unit b a n k i n g states above $50
million-$75 million in deposits experienced
diseconomies of scale w i t h respect t o t h e
Divisia n u m b e r of accounts. The smaller
banks in these states had scale e c o n o m i e s
or constant costs. The elasticities range
' ' T h e numbers presented are for the analysis of 1 9 7 8 data. The analysis of
the 1975, 1 9 7 6 and 1977 data yield similar results. See Benston,
Hanweck and H u m p h r e y (1982) for details.
NOVEMBER 1982, E C O N O M I C
REVIEW
f r o m .95 t o 1.23. 1 2 (See Table 1, c o l u m n
1.)
•
Banks in b r a n c h i n g states of all sizes
e x p e r i e n c e d e c o n o m i e s of scale w i t h respect to the Divisia n u m b e r of accounts.
The elasticities range f r o m .81 for t h e
smallest d e p o s i t size group t o .92 for the
largest. These elasticities were calculated
for each d e p o s i t size group, so t h e fact
that larger branch banks have more branches
was taken into account. (See Table 1,
c o l u m n 1.)
The e c o n o m i e s of scale e x p e r i e n c e d by
banks in b r a n c h i n g states appear to result
from t h e a b i l i t y of branch banks t o o p e r a t e
out of many smaller offices, a v o i d i n g the
diseconomies associated w i t h a large n u m b e r
of accounts per office.
To a c c o u n t for d i f f e r e n c e s in the m o d e of
branch bank e x p a n s i o n (by a d d i n g branches
each w i t h a g i v e n n u m b e r o f accounts) versus
that for unit banks (by a d d i n g more accounts
at a single o f f i c e ) , w e c a l c u l a t e d a u g m e n t e d
elasticities, where the effect on costs of changes
in the n u m b e r o f offices as w e l l as the n u m b e r
of accounts serviced is a c c o u n t e d for. These
a u g m e n t e d elasticities ( n o t shown in Table
1) show that:
• Banks in unit states w i t h deposits b e l o w
$25 m i l l i o n e n j o y e d e c o n o m i e s of scale.
The m i d d l e - s i z e d banks ($75 m i l l i o n t o
$300 m i l l i o n in deposits) had significant
d i s e c o n o m i e s of scale and t h e others had
i n s i g n i f i c a n t scale d i s e c o n o m i e s . ( T h e
n u m b e r s are almost t h e same as t h o s e
given in Table 1 for t h e u n a u g m e n t e d
measure.)
• Banks in b r a n c h i n g states w i t h m o r e
than $25 m i l l i o n in deposits e x p e r i e n c e d
statistically significant d i s e c o n o m i e s of
scale (using t h e n u m b e r of accounts as
o u t p u t ) . The elasticities range f r o m 1.09
for banks w i t h $25 m i l l i o n t o $50 m i l l i o n
in deposit size group t o 1.1 6 f o r t h e largest.
Smaller banks experienced approximately
constant costs.
Thus, w h e n the n o r m a l path of e x p a n s i o n is
a c c o u n t e d for, branch and unit state banks
'-'An elasticity is the proportional c h a n g e in cost associated with a given
proportional c h a n g e in output For example, an elasticity of 9 5 means
that a 100 percent increase in output is associated with a 9 5 percent
increase in cost. Since cost increases less than proportionately, the
banks are said to experience e c o n o m i e s of scale
FEDERAL RESERVE BANK O F A T L A N T A
e x p e r i e n c e d similar scale e c o n o m y or dise c o n o m y values. O t h e r results i n d i c a t e that:
• Economies of scale appear t o be unchanged over the p e r i o d 1975 t h r o u g h
1978, since t h e elasticities c o m p u t e d are
either very similar or show unsystematic
changes over the years.
• W i t h respect t o the average size of
accounts, banks in both unit and branching
states experienced conside~able economies
of scale. Elasticities averaged b e t w e e n .28
and .50 over t h e four years s t u d i e d . The
elasticities increase c o n s i d e r a b l y for the
larger d e p o s i t size groups of banks. In
particular, the smallest banks had almost
no a d d i t i o n a l cost associated w i t h larger
account sizes, but t h e cost of the largest
deposit size banks (particularly t h e u n i t
state banks) almost d o u b l e d w h e n t h e i r
average a c c o u n t sizes d o u b l e d . This finding indicates that the larger banks, w h i c h
have larger loans and d e p o s i t accounts,
incur proportionately larger costs, probably
arising f r o m m o n i t o r i n g t h e loans and attracting the deposits.
Average Cost per Account
For many p o l i c y questions, average costs
per account are more relevant than economies
of scale. It may be t h a t unit banks e x p e r i e n c e
d i s e c o n o m i e s of scale but t h e i r costs per
account serviced m i g h t be l o w e r than those
for branch banks.
Average cost p e r a c c o u n t was c a l c u l a t e d in
several ways. First, the average ( g e o m e t r i c
mean) values of input prices, holding company
affiliation, size of account, and n u m b e r of
offices of each of t h e nine d e p o s i t size groups
were used for the calculation. Thus the calculated average cost p e r a c c o u n t is the average
e x p e r i e n c e d for each size group. These are
plotted in Chart 1 and show:
• Similar average costs for banks in unit
and branch states u p t o $75 m i l l i o n in
deposits.
• Greatly increasing average costs for larger
banks in unit states. Costs i n c u r r e d by the
largest banks were more than d o u b l e those
for the m i d d l e size group.
• Higher average costs for larger banks in
b r a n c h i n g states that, nevertheless, are
considerably b e l o w those for similarly sized
banks in unit states.
15
C h a r t 1 . Average Cost per Account, 1978 FCA Data,
At Unit and Branch State Banks
Cos! Per
Account
30
60
90
Deposit Size Groups
120
S millions)
A - unit state banks, variables at m e a n s of deposit size g r o u p
B - branch state banks, variables at means of deposit size groups.
C - u n i t state banks, variables at branch state bank. M e a n s for entire
sample, except number of a c c o u n t s a n d offices. "Deposit size group
$ 4 0 0 - 1 , 0 0 0 is o m i t t e d since none of the unit state banks had
numbers of a c c o u n t s of the magnitude serviced by branch state
banks.
D - branch state banks, variables at m e a n s for entire sample, except
number of a c c o u n t s and offices.
therefore, it w o u l d be unrealistic t o assume
that higher o u t p u t c o u l d be a c h i e v e d w i t h o u t
branch expansion. U n i t banks, t h o u g h , must
e x p a n d at a single full-service office.
To c o m p a r e average costs of banks in unit
states w i t h average costs of banks in branching states, w e s u b s t i t u t e d b r a n c h i n g state
cost d e t e r m i n a n t s in t h e unit states' cost
equation. W e e n t e r e d averages of n u m b e r of
accounts, n u m b e r of offices, a c c o u n t size
and h o l d i n g c o m p a n y a f f i l i a t i o n . Average
n u m b e r of offices in b r a n c h i n g states c o u l d
not be e n t e r e d in the unit state e q u a t i o n ;
thus, this cost d e t e r m i n a n t was ignored. W e
e m e r g e d f r o m this exercise w i t h an e s t i m a t e
of the average costs of unit banks w i t h all of
the characteristics of b r a n c h banks but m u l t i ple offices. These calculations ( p l o t t e d in
Chart 1) show:
• Somewhat higher average costs for larger
banks.
• Very similar average costs for similar
sizes of banks in unit and b r a n c h i n g state
banks.
These results indicate t h a t w h e n w e take
p r o p e r a c c o u n t of the c u r r e n t d i f f e r e n c e
b e t w e e n unit and branch state banks, these
t w o classes of banks w o u l d experience similar
average costs. This reinforces the earlier rep o r t e d similarities w i t h the scale e c o n o m y
results w h e n a c c o u n t is taken of t h e d i f f e r e n t
expansion m e t h o d s used by unit and branch
banks ( d u e t o regulatory constraints).
Cost of Branching and Holding
Company Affiliation
For most p o l i c y questions (for e x a m p l e ,
mergers and unit versus branch banking), t h e
average size of accounts is not relevant. Presumably, bank customers w o u l d d e m a n d loans
and hold deposits that met their convenience
rather than the bank's. C o n s e q u e n t l y , we
e x t e n d e d our analysis t o abstract f r o m this
difference among banks, by holding the average
size of a c c o u n t constant at t h e mean values
for the e n t i r e b r a n c h i n g state bank sample.
I n p u t prices and h o l d i n g c o m p a n y a f f i l i a t i o n
also w e r e held constant at t h e b r a n c h i n g
state sample means; h o w e v e r , t h e n u m b e r of
offices operated was not held constant. Branch
banks t e n d t o expand by o p e n i n g more offices;
W e can also compare estimated operating
costs of a branch with those of a similar sized
unit bank. Such comparisons are relevant to
public choice of unit versus branch banking
and of methods of interstate banking. The
typical branch serves from 5,000 t o 11,000
accounts. The operating costs of unit banks
w i t h the same o u t p u t are $210,000 and
$462,000. 13 Branches serving the same number
of accounts at smaller branch banking organizations have estimated costs of $213,000 and
$483,000, respectively. Similar sized branches
1978 data (as are the following numbers) The a m o u n t s for the other
years studied (1975-1977) are similar, though lower due to the effects of
inflation over the same period See Benston. Hanweck and Humphrey
1981. Table 6 for the individual year amounts.
16
N O V E M B E R 1982, E C O N O M I C
REVIEW
at larger banking organizations are estimated
to have increasingly higher operating costs (for
example, an 11,000-account branch of a bank
with $300 million to $400 million in total
deposits costs $650,000 to operate.) Thus,
small unit banks appear able t o compete successfully with branches, particularly those operated by large banks.
W e found the effect on operating costs of
bank holding company affiliation to be insignificant. Not only were the coefficients of relevant variables generally statistically insignificant,
but calculations of average costs that included
or excluded consideration of these variables
produced numbers that were almost identical.
(Cont. on p. 21)
Regression Studies of Bank Operating Costs
Before considering the implications of these findings
for the policy questions delineated above, we review
briefly the previously published regression studies
of bank operations costs. These studies may be
grouped according to the type of data used, which, in
large measure, determined the researchers' definition
and measurement of output. The first group used
balance sheet and income statement data, with
output defined as dollars of assets, while the other
used FCA data, with output defined as number of
accounts.
Output as Dollars of Earning Assets
Three of the six regression studies that use dollars
of assets as output report economies of scale. (Two of
these employed specifications that imparted a strong
bias towards this result.) One study (Powers) found
some evidence of diseconomies and two others
(Schweitzer and Kalish-Gilbert) found strong evidence
of U-shaped average cost curves, that is, decreasing
costs at lower output levels and increasing costs at
higher levels. The use of dollars of earning assets as
the measure of output appears to have biased the
findings of the studies away from showing higher
costs for larger banks and deemphasizes the Ushape of the average cost curves We reach this
conclusion in part because when our present study
is recast roughly in terms of these previous analyses,
the findings are rather similar to theirs. All the
studies found branch banking organizations as having
higher costs than unit banks. The two studies that
included measures of holding company affiliation
report conflicting findings.
The first two studies that employed multiple regression analysis measured costs as total operating
expenses (including interest) divided by year-end
total assets (Schweiger and McGee (1961) and
Gramley (1962)). This cost measure was regressed
on bank size as measured by deposit size groups by
Schweiger-McGee and total assets by Gramley. Other
variables used to hold bank characteristics constant
were the ratios of time to total deposits, various types
of earning assets as a percent of total assets, and
whether a bank was a unit or branch bank SchweigerMcGee used all member bank data for 1959 and
Gramley used a sample of Tenth (Kansas City)
District member banks Both studies found evidence of
large economies of scale. Schweiger-McGee also
reported higher costs per dollar of assets for branch
banks (Gramley's sample included only unit banks).
Unfortunately, the use of costs per dollar of assets
to measure unit costs imparted strong bias toward
the finding of economies of scale. The use of dollars
of assets as the output measure requires the implicit
and incorrect assumption that large and small loans
are equally costly per dollar outstanding. Thus banks
with larger average loan sizes appear more efficient.
Equally important is the fact that neither study included
variables that could identify U-shaped cost curves nor
made a formal determination that a U-shaped curve was
not necessary to properly describe the data they
used.
Four studies defined output as loans and securities
with deposit services being considered an input.
Greenbaum (1967), Powers (1969) and Schweitzer
(1972), and Kalish and Gilbert (1973) reasoned that
the "social" value of these earning assets is equal to
the amount people are willing to pay to obtain them.
Hence, except for Powers, they weighted each bank's
dollars of loans and securities outstanding by the
average gross yields on these assets overall banks in
the sample to abstract from the effect of local market
conditions. Powers used the rates charged at each
bank rather than the average rate for all banks because
he believed that a loan's social value is measured best
by its actual local price. Thus output is equal to gross
revenue or a variant thereof. Cost is defined as total
operating cost, including interest, less fees for deposit
services. 14
Greenbaum (1967) analyzed 1961 data of 745 and
413 insured banks in the Tenth (Kansas City) and Fifth
(Richmond) Federal Districts. He found U-shaped
average costs in both districts; however, 98 percent of
the banks are on the portion of the cost curve that
showed economies of scale. The Fifth District sample
was analyzed separately for branch and unit banks
When thus separated, both groups have downward
sloping average costs. The unit banks have lower and
more rapidly declining costs than the branch banks,
but the unit banks are much smaller. Greenbaum concludes that banks grow larger by branching because
large unit banks may be more costly to operate.
Powers (1969) analyzed 1962 data from all insured
banks in the Seventh (Chicago) Reserve District. He
' " G r e e n b a u m d i d not d e d u c t deposit service fees from costs.
FEDERAL RESERVE B A N K O F A T L A N T A
17
stratified his sample of 2,411 banks into 24 subsamples, according to asset size, current operating
revenue to total output (which he defined as total
revenue), lending output to total output, and branch
versus unit. Of these sub-samples, five have some
suggestion of a U-shaped cost curve within the range
of the data With respect to the branch versus unit
dichotomy, Powers finds that the branch banking
organizations generally (but far from uniformly) have
higher average costs than do unit banks.
Schweitzer (1972) analyzed 1964 data from 1,325
Ninth (Minneapolis) District banks. Unlike Greenbaum
and Powers, he included the following additional variables: time deposit rate paid, two dummy variables for
city location to account for input price differences
among banks, and dummy variables measuring the
effect of Federal Reserve membership and bank
holding company affiliation. The data were sub-categorized into four size of loans and securities groups.
Schweitzer reports "scale economies for banks with
total assets under $3.5 million, constant returns to
scale for banks between $3.5 and $25.0 million, and
decreasing returns for larger banks." (p. 265). He also
found significant economies associated with large
holding company affiliation, except for banks over
$25.0 million in assets. Small bank holding company
affiliation indicated economies that are not statistically
significant.
Kalish and Gilbert (1973) analyzed 1968 data from
898 FCA banks, using a method that traced out costs
with observations from the most efficient banks The
banks were separated into sub-samples of 86 holding
company affiliates, 353 branch banks and 460 unit
banks. They report U-shaped average cost curves for
all three groups, with unit banks having the lowest
costs (except for the very largest banks). Branch banks
above $1 million in adjusted revenue (or $10 million in
loans and investments) show lower costs than holding
company subsidiaries and smaller branch banks had
higher costs than similar sized holding company
affiliates.
The four studies that allowed for finding of diseconomies of large scale found them. 15 However, the
evidence of eventually upward sloping curves is slight
in Greenbaum's study and mixed in Powers' study.
The four studies that included measures of branch
versus unit banking report higher costs for branch
banks. Results on holding company affiliation are
conflicting. Using 1964 data Schweitzer found holding
company affiliates to have lower costs (Schweitzer,
1964 data); using 1968 data Kalish and Gilbert found
them"to have higher costs (Kalish and Gilbert, 1968
data).
Before these results can be accepted as meaningful, at least with respect to the banks and time
periods analyzed, we must consider the extent to
which the more important misspecifications may bias
these findings. The three principal problems are (1)
,5
S c h w e i g e r - M c G e e a n d Gramley e m p l o y e d different m e t h o d s which,
we' feel, biased their measures of scale (as discussed above).
18
exclusion of variables that account for differences in
input prices and types of deposit services, (2) inclusion of interest in operating expenses, and, most
important, (3) output defined as dollars of assets
outstanding.
The exclusion of input price differences in the
studies does not appear to be serious, at least with
respect to the calculation of elasticities and average
costs, where the banks are ordered by size and by type
of organization (branch and unit). We calculated these
numbers for our samples holding these factor prices
constant over the entire sample; the changes in the
scale economy estimates and average costs were
slight and did not affect any of the conclusions. However, ignoring differences in types of deposits is likely
to be serious, since about half of the total operating
expenses (excluding interest) are due to deposits. 16
Furthermore, the proportion is higher at the small
banks (those with deposits under $50 million): 53
percent compared to 49 percent for banks with $50 to
$200 million in deposits and 46 percent for banks with
over $200 million in deposits. The smaller banks also
have relatively more demand deposit expense (39
percent versus 36 and 35 percent). This misspecif¡cation
probably overstates the average costs of smaller
banks.
Exclusion of interest from operating expenses might
understate the costs of large banks, since they generally purchase a greater proportion of theirfunds in the
market. We tested this hypothesis by including interest
in operating expenses in our data and recalculating
the cost functions. The recalculations showed greater
economies of scale for all the banks (See Table 1,
column 3). With interest included and the Divisia
number of accounts as the measure of output, the
larger banks (over $25 million in deposits) in unit
states had nearly constant costs. The smaller (under
$25 million in deposits) branch banks had statistically
significant economies of scale, and the medium-sized
($50 million to $300 million in deposits) banks in
branching states had small, but statistically significant,
diseconomies of scale. Thus, inclusion of interest
could account, in part, for the larger economies or
lower diseconomies of scale for larger banks found in
the other studies.
Finally, measuring output with assets (weighted by
revenues in most of the studies) may impart a bias for
banks that service larger accounts showing them as
being more efficient. We tested for this bias by recalculating the elasticities and average costs with dollars
of deposits and loans as the output measure instead of
the number of accounts and average size of account.
These elasticities are considerably lower for all size
groups of the unit banks and for all but the larger(up to
$200 million to $300 million in deposits) branch banks
(see Table 1, column 2). With interest included as part
of operating expenses, the middle-sized banks in both
unit and branch states show diseconomies of scale, a
finding similar to those reported in the studies that
,6
1 9 7 8 Functional Cost Analysis data.
N O V E M B E R 1982, E C O N O M I C
REVIEW
similarly measured cost and output (see Table 1,
column 4). Thus using dollars of deposits is equivalent
to measuring output by the number of accounts while
assuming that the size of accounts is uniform among
banks. This assumption biases the elasticity estimates
"Measuring output with assets may
impart a bias for banks that service
larger accounts, showing them as
being more efficient."
towards greater economies of scale particularly at the
large unit banks. This effect also is reflected in the
average cost per dollar of deposits and loans (not
shown): the cost curve is'less U-shaped.
Output as Numbers of Accounts and
Average Size of Accounts in a Cobb-Douglas
Production
Function
Benston (1965A) is the first study to use the FCA
data, which permitted him to specify output as the
average number of accounts serviced and the average
size of accounts, and to analyze costs of separate
banking functions. He analyzed each of the five functions—demand deposits, time and savings deposits,
real estate loans, installment loans, business loans and
securities—and overhead costs. Overhead was regressed on total assets rather than the humber and
average size of accounts For most of the analyses
Benston used a functional form that can show only
continously rising, falling, or flat average cost curves.
But by including higher powers on the output measure
he also tested for the presence of U-shaped cost
curves. This study used data from some 80 banks in
the Boston Federal Reserve District for 1959, 1960
and 1961 and found economies of scale for all except
the business loan function and the overhead costs
Slight U-shaped curves were present for installment
loans only. The estimated elasticities (averaged over
the three years) ranged from .74 (securities) and .87
(demand deposits) to 1.0 (business development and
overhead). However, the largest bank included had
$55 million in assets(1961 price level), so the data did
not cover the full range of bank output. Branch banks
were found to have higher operating costs than unit
banks that serviced the same number of accounts
(Benston 1965B), but because the cost effect of
branching was misspecified the validity of this finding
is questionable.
Bell and Murphy (1968) extended Benston's work
considerably. They analyzed data from 210 to 283
banks in the Boston, New York and Philadelphia
Federal Reserve Districts that reported FCA data for
FEDERAL RESERVE B A N K O F A T L A N T A
1 9 6 3 , 1 9 6 4 and 1965. They did not explicitly test the
data for the presence of U-shaped cost curves since
they explicitly based their analysis on the CobbDouglas production function. They estimated elasticities
(averaged over the three years) ranging from .83
(securities) and .86 (real estate loans) to 1.0 (safe
deposits and trust department). They constructed an
overall measure of economies of scale by weighting
the individual elasticities by the average cost of each
function and type of overhead expense. This yielded a
total elasticity of .93. Branch banks were found to have
higher operating costs than unit banks, but Bell and
Murphy calculated that expansion of branch banks
did not generate greater average costs, since the
higher cost of branching, in their calculations was
offset almost exactly by economies from a larger
volume of output.
Murphy (1972) replicated and further extended this
work with a larger sample (967 banks) of large banks
(up to $5.5 billion in deposits) nationwide for 1968.
The only important difference between the elasticities
measured with these data compared to the earlier
(1965) results is the change from significant economies
of scale in demand deposits to approximately constant
costs. Most of the other functions showed only small
economies of scale, so that the estimated total elasticity
for the 1968 sample is .95.
Longbrake and Haslem (1975) also used these data
(1968 FCA banks, nationwide), but restricted the
analysis to direct demand deposit costs, emphasizing
the effect on these costs of organizations structure.
They separated the sample of 767 banks into four
sub-sets: unit banks and branch banks, each affiliated
or not affiliated with holding companies. They found
statistically significant economies of scale (elasticities
of .93 for unit affiliates and branch non-affiliates and
.82 for branch affiliates) for all except the unit bank
non-affiliates, which had constant costs (elasticity of
1.03). In general, the branch banks (particularly the
larger ones) had higher estimated costs per account
or dollar of deposit than did the unit banks, the
affiliated unit banks had higher costs than the unaffiliated
unit banks, but the affiliated branch banks had lower
costs than the unaffiliated branch banks.
Mullineaux (1975) also separated a 1970 sample of
196 FCA banks in the Boston, New York and Philadelphia Reserve Districts, into branch (167) and unit
(29) banks, to test the hypothesis that the estimated
coefficients differ by type of organization. Elasticities
were estimated for each of the five principal banking
functions and the hypothesis was accepted. For most
functions, unit banks had economies of scale and
branch banks had diseconomies. As the previous
studies found, branch banks appeared to have higher
operating expenses than similar unit banks.
Benston and Hanweck(1977) reported preliminary
findings of a study of nationwide FCA banks for the
years 1968 through 1974 (904 banks in 1974). The
direct costs of the five principal banking functions
were analyzed separately. Unlike the other studies
which used the Cobb-Douglas cost function, a quadratic
cost function was estimated which permitted estimation
19
of U-shaped cost curves.17 They report finding scale
economies for most years only for business loans.
Little indication of systematic economies or diseconomies was found for the real estate, installment loan
or time deposit functions. The demand deposits function,
though, exhibited diseconomies of scale starting at
low output levels.
The effect of holding company affiliation was tested
by separating the sample into affiliated and independent banks. The affiliated banks exhibited somewhat lesser scale economies than the independents.
But average costs per account at the affiliates were
lower, particularly with respect to demand deposits.
For 1974, demand deposits costs averaged 4 percent
lower for banks affiliated with a small holding company
and 17 percent lower for banks affiliated with a large
holding company. Branch and unit banks were not
separately identified and this misspecification may
have confounded the results somewhat.
Finally, a recent study by Dunham (1982) used 1978
FCA data for three Federal Reserve Districts (Boston,
New York and Chicago). The Cobb-Douglas form was
used and separate estimation was performed for five
banking functions—demand deposits, time deposits,
commercial and agricultural loans, installment loans
and mortgage loans. Operating costs were adjusted
for correspondent services paid for with non-interest
bearing balances by imputing a cost based on the
three-month Treasury bill rate applied to net "due
from" balances. Output was measured by the number
of accounts for each function. When operating costs
are not adjusted for the imputed cost of correspondent
services, the demand deposit function exhibited constant costs while the other functions showed significant scale economies. After costs were adjusted, the
demand deposit function also exhibited significant
economies of scale. In addition, this study also found
that branch banks had higher costs than unit banks
with the same characteristics. Thus, the results are
similar to those of Benston, Bell and Murphy.
These studies offer some important insights into
costs of individual bank outputs and changes in banks
cost structure over time. The analyses indicated economies of scale in the early 1960s for all banking
functions and departments except safe deposit boxes
and trust. The late 1960s and early 1970s data
revealed a change to constant costs for the important
demand deposit function, at least for unit banks not
affiliated with holding companies. Affiliated unit banks
and branch banks were found to have economies of
scale in demand deposit operations similar to those
computed with earlier data Data for 1970 yielded
approximately constant direct costs for branch banks
but economies of scale for unit banks. However, one
study that used data through 1974 found diseconomies
pf scale. This study (Benston-Hanweck) is the only one
using data covering a broad range of bank sizes that
specified a cost function to test for U-shaped cost
curves. Thus, the earlier findings of continuous slight
economies of scale might be due to this misspecification or to a change over time in the cost function
faced by commercial banks.
It also is important to note that none of these studies
tested for economies of scale for banks as entire
entities. Where overhead costs were analyzed, these
costs were regressed on output measured as total
assets. Hence, the elasticities of banks that serviced
larger average size accounts appear to be biased
downward. This problem could have resulted in a
finding of economies of scale or constant costs when,
in fact, diseconomies of scale were experienced.
To test for the possible misspecification effect of not
allowing for U-shaped cost curves and of not analyzing
the banks as an entire entity, and as a means of
separating the effects of sample and specification
differences, we reestimated our 1978 findings using
the Cobb-Douglas cost function. This functional form
yields the following elasticities: branch state banks,
.93*, unit state banks 1.07*, and for the entire sample,
1.01 (an asterisk indicates elasticities statistically
significantly different from 1.0—constant costs—at
the 95 percent confidence level). These are almost
the same as the mean elasticities computed with our
more complex translog cost function which allows for
a U-shaped cost curve. But, as Table 1, column 1
shows, the mean elasticity value masks the finding of
lower elasticities for smaller banks and higherelasticities
for larger banks. Combining unit and branch banks in a
single sample also masks important and statistically
significant differences between them. Furthermore,
as the augmented measure of branch bank elasticities
presented above shows, ignoring the way in which
branch banks actually expand understates the elasticities experienced by branch banks when one wishes
to determine the scale economy of the entire organization rather than of a single office.
" T h e earlier findings of continuous
slight e c o n o m i e s of scale might be
d u e to this misspecification or to a
c h a n g e over time in the cost function
faced by c o m m e r c i a l banks."
With respect to branch banking, most of the studies
reported higher branching costs that appeared to be
offset by measured economies of scale. Studies that
calculated average costs found them to be higher for
branch banks, with larger branching systems having
even higher costs per account. Those findings are
consistent with our more current study, with one
exception. We found branch and unit banks to have
very similar costs' per account when differences between them, in terms of their mode of expansion, were
accounted for properly.
" T h e variables w e r e divided by output to correct for heteroscedasticity
20
NOVEMBER 1982, E C O N O M I C REVIEW
Implications of the Studies
and Conclusion
At this point, only a few implications can be
drawn concerning commercial banks' operating
costs. To date, w e are unable to weigh the
possibilities and magnitudes of economies of
scale or the cost savings from producing bank
services jointly rather than separately. However,
studies using data from 1959 through 1970
provide us with some evidence on banks' costs
to produce individual services, such as demand
deposits and installment loans. Unfortunately,
the functional forms used appear t o have understated the costs for larger banks. Also, their old
data may not reflect present cost conditions.
Thus w e are unable at this time to go much
beyond saying it is unlikely that there are large, if
any, economies of scale in producing the most
important banking services. (Business loans may
be an exception.)
costs per account, after we adjust for the higher
cost of servicing customers w i t h larger accounts.
Small branch and unit banks, though, appear t o
be more efficient than larger banks.
W e should emphasize that customer-borne
costs, such as inconvenience, are not accounted
for, nor is the benefit to customers of using
collateral services offered by an individual bank.
Presumably, the effect of these factors should be
reflected in banks' revenues. Considering these
caveats, our analysis of the presently available
data leads us t o conclude that smaller banks are,
at the least, not at an operational disadvantage
with respect to large banks. As a result, mergers
appear unlikely to result in operating cost savings.
Whether or not other benefits or costs flow from
a policy of freer entry, or branching, or a more
liberal merger policy is beyond the scope of this
analysis.
—George J. Benston,
Gerald A. Hanweck,
and David B. Humphrey
However, it does appear safe to conclude that
branch and unit banks incur about the same
Hanweck
is an economist
Reserve System. Humphrey
Studies
Section.
with the Board of Governors,
is chief of the Federal Reserve's
Federal
Financial
REFERENCES
1. Alhadeff, David A M o n o p o l y a n d C o m p e t i t i o n in Banking. Berkeley,
California: University of California Press, 1954.
13. Goldschmidt, Amnon " O n the Definition a n d M e a s u r e m e n t of Bank Output."
Journal of Banking a n d Finance, 5 (1981), 575-585.
2. Barnett, William A "Divisia Indices." Encyclopedia of Statistical Sciences,
New York, New York: Wiley a n d Sons, 1981.
14. Greenbaum, Stuart I. " B a n k i n g Structure a n d Costs: A Statistical S t u d y of the
Cost-Output Relationship in Commercial Banking." National Banking Review,
4 (June, 1967), 415-34.
3. Bell, Frederick W „ a n d Neil B. Murphy Costs in C o m m e r c i a l Banking: A
Quantitive Analysis of Bank Behavior a n d its Relation to Bank Regulation.
Federal Reserve Bank of Boston, Research Report No. 41, 1968.
15. Gramley, Lyle E. A Study of Scale E c o n o m i e s in Banking. Federal Reserve
Bank of Kansas City, 1962.
4. Benston, George J. " E c o n o m i e s of Scale a n d Marginal Costs in Banking
Operations." T h e National Banking Review, 2 (June 1965A), 507-49.
16. Horvitz, Paul M., " E c o n o m i e s of Scale in Banking," Private Financial Institutions, Englewood Cliffs, N.J.: Prentice-Hall, Inc. 1963, 1-54.
5. Benston, G e o r g e J. " B r a n c h Banking a n d Economies of Scale," T h e J o u r n a l
of Finance, XX (May 1965B), 312-31.
17. Kalish, Lionel a n d R. Alton Gilbert "An Analysis of Efficiency of Scale a n d
Organizational Form in Commercial Banking." Journal of Industrial Economics, 21 (July 1973), 293-307.
6. Benston, G e o r g e J. " A c c o u n t i n g Numbers a n d Economic Values." T h e
Antitrust Bulletin, XXVII (Spring 1982), 161-215.
7 . Benston, G e o r g e J., a n d Gerald A Hanweck "A Summary Report on Bank
Holding C o m p a n y Affiliation a n d Economies of Scale." Proceedings of a
C o n f e r e n c e o n Bank Structure a n d Competition, Federal Reserve Bank of
Chicago, 1977.
8. Benston, George J., Gerald A Hanweck, a n d David B. Humphrey "Scale
E c o n o m i e s in Banking: A Restructuring a n d Reassessment." Working Paper,
Federal Reserve Board, November 1981.
9. Benston, G e o r g e J., Gerald A H a n w e c k a n d David B. Humphrey "Scale
E c o n o m i e s in Banking: A Restructuring a n d Reassessment." J o u r n a l of
M o n e y , Credit, a n d Banking, XIII (November 1982, Part I).
10. Diewert, W. Erwin "Exact a n d Superlative Index Numbers." J o u r n a l of
Econometrics, 4 (May 1976), 115-145.
11. Durham, Constance " C o m m e r c i a l Bank Costs a n d Correspondent Banking."
N e w England E c o n o m i c Review, Federal Reserve Bank of Boston, (Sept e m b e r / O c t o b e r 1981) 22-36.
18. Longbrake, William A a n d John A. Halstern "Productive Efficiency in Commercial Banking: The Effects of Size a n d Legal Form of Organization on t h e Cost
of Producing Demand-Deposit Sen/ices."Journal of M o n e y , Credit a n d
Banking, 7 (August 1975), 3 1 7 - 3 3 0 .
19. Mullineaux, Donald J. " E c o n o m i e s of Scale of Financial Institutions: A
Comment." J o u r n a l of Monetary Economics, 1 (April 1975), 233-240.
20. Murphy, Neil B. "A Re-estimation of the Benston-Bell-Murphy Cost Functions
f o r a Larger Sample with GreaterSize a n d Geographical Dispersion." J o u r n a l
of Financial a n d Quantitative Analysis 7 (December 1972), 2 0 9 7 - 1 0 5 .
21. Powers, J o h n A " B r a n c h Versus Unit Banking; Bank Output and Cost Economies." Southern E c o n o m i c Journal, 3 6 (October 1969), 153-64.
22. Schweiger, Irving a n d J o h n S. M c G e e "Chicago Banking: The Structure a n d
Performance of Banks a n d Related Financial Institutions in Chicago a n d
Other A r e a s " Journal of Business, 3 4 (July 1961), 203-366.
23. Schweitzer, A A " E c o n o m i e s of Scale a n d Holding Company Affiliation in
Banking." Southern E c o n o m i c Journal, 3 9 (October, 1972), 258-266.
12. Flannery, Mark J. "Correspondent Services a n d Cost Economies in Commercial Banking." Research Paper No. 77, Federal Reserve Bank of Philadelphia, November 1981.
21
FEDERAL RESERVE BANK O F A T L A N T A
Economies of Scale:
A Case Study of the
Florida Savings and Loan Industry
A study of Florida S&Ls shows
that operating costs decrease
as S&Ls increase in size up to
$500 million in deposits.
H o w does the structure of costs at savings and
loan associations compare with that of commercial
banks? In view of the trend toward deregulation,
the large number of mergers of thrift institutions,
proposals for new powers for thrift institutions,
and prospects for increased competition and
consolidation among all types of financial institutions, this is certainly not an academic question.
This article reviews recent studies regarding
savings and loan scale economies, discusses the
profit implications of S&L consolidation, and
then presents some new results based on a study
of the S&L industry in Florida. Since the Florida
S&L industry ranks second to California nationally in
terms of assets, these results should also be
reasonably representative of S&L costs in other
areas of the country.
S&L costs are both different from and similar to
commercial bank costs. Operating costs are
considerably lower at S&Ls, for instance, because
these organizations have specialized in the lowcost functions of mortgage lending and servicing,
and the collection and servicing of time deposits.
This study indicates that S&Ls experience economies of scale up to about $500 million in assets.
Except at small sizes, however, costs savings are
not very large as size increases. If S&Ls could
expand assets significantly without adding offices,
they could capture important economies of
scale beyond the $500 million asset level; however,
most are not able to do this without expanding
their office networks.
22
NOVEMBER 1982, E C O N O M I C
REVIEW
Measuring Economies of Scale
Studies of operating costs typically have measured economies of scale by estimating the
elasticity of cost with respect t o output. For
example, if assets are used as a measure of bank
or S&L output, the elasticity would be calculated
as the percent change in cost divided by the
percent change in assets. Thus, if a typical bank
or S&L with $100 million in assets had operating
expenses of $1 million, and one with $200
million in assets had expenses of $1.9 million,
the elasticity would be calculated as follows:
p e r c e n t change in costs
p e r c e n t change in assets
(1.9/1.0) - 1
(200/100) -
1
90%
=
100%
=
°-9-
If costs increase by less in percentage terms than
the increase in asset size, the elasticity is less
than one. In such a case average costs would
decline as size increases, and economies of scale
would exist in this industry. Elasticities that are
greater than one indicate that average costs rise
as size increases, in economic terms, "diseconomies of scale."
Until a few years ago it was generally accepted
that economies of scale existed at all types of
financial institutions and were significant in
most asset size ranges. For example, in a survey
of the major studies published in 1972, Benston
(4) concluded that, on average, the overall elasticity of cost with respect to output was about
0.93 for commercial banks. Roughly similar results
had been found for S&Ls. This led Benston to
conclude that banks and S&Ls have approximately
the same cost structure.
Recent studies, however, have called into
question the conventional wisdom about economies of scale at financial institutions. For example,
Gilligan, Smirlock and Marshall have concluded
that, based on their investigation of the issue,
" t h e empirical evidence does not indicate the
existence of scale economies in banking, except
for relatively low o u t p u t levels...(therefore) a
public policy that attempts to increase bank
scale through controlling entry or encouraging
merger cannot be justified on the basis of cost
savings" (11, p. 27). In a recent paper, Benston,
Hanweck and Humphrey have also found evidence of diseconomies of scale (increasing expense
ratios) for commercial banks at bank office sizes
in excess of $25 million of deposits (5). Similar
controversy surrounds the existence of economies
of scale at credit unions (1 5).
Profit Implications
To put into perspective the differences between
S&L and bank costs, w e should note that if
economies of scale exist, the profit implications
of changing size are somewhat different for S&Ls
than for commercial banks. The typical S&L
reported an operating cost ratio (operating costs
divided by average assets) of 1.35 percent in
1980, while the typical commercial bank had a
ratio approximately twice that amount. 1 This
difference is a result of the much greater diversity
of functions performed by banks.
Demand deposits, consumer lending, and corporate lending involve high turnover and thus
require constant activity on the part of a bank's
staff just to keep asset and deposit size at a
certain level. In contrast, the bulk of S&L assets
are long-term mortgage loans. These require
servicing but involve little additional operating
cost unless they become d e l i n q u e n t In addition,
savings deposits (the primary liability item for
S&Ls) involve less operating costs per dollar than
demand deposits.
Table 1 shows a hypothetical situation in
which a typical S&L and a typical commercial
bank experience growth and enjoy cost savings
as a result of economies of scale. Both are
assumed t o have the same cost elasticity with
respect t o output. Because of its much larger
initial operating cost ratio, the commercial bank
experiences a pre-tax profit gain of 12 basis
points; for the S&L the effect on profits is only half
as great.
Previous Research Reviewed
Earlier studies seem to indicate quite clearly
that economies of scale do exist at savings and
loan associations. The most recent study to
confirm this finding was the Brookings study of
the thrift industry, conducted by Andrew Carron
(8). As indicated in Table 2, Carron's results
(which were based on 1980 data) are reasonably
consistent w i t h many earlier findings going back
to the late 1960s.
These studies suggest, however, that the cost
savings from growth will not be particularly large.
' S e e the note to Table 1 for the precise figures a n d the sources of data.
23
FEDERAL RESERVE BANK O F A T L A N T A
Table 1 . Hypothetical Effect of a Merger
on Profitability
Savings and Loan
Association
Commercial
Bank
Before Merger
Operating Costs (millions)
Assets (millions)
Cost: Assets
Elasticity of Cost
With Respect to
Output (Assets)
$
1.25
$100.00
1.25%
0.9
$ 2.50
$100.00
2.50%
0.9
After Merger
Operating Cost (millions)1
$ 2.38
$ 4.75
Assets (millions)
$200.00
$200.00
Cost/Assets
1.19%
2.38%
Cost Savings (equals
6 basis points 12 basis points
Pretax Profit Gain)
1
A 90% increase in costs, which is the result of the asumed elasticity of 0.9
and the 100% increase in assets.
Note: The operating cost ratios are for illustrative purposes only. The actual
ratio of operating e x p e n s e to average assets in 1980 was 2.73% for
commercial banks a n d 1.35% for S&L's on a national average basis.
Source: Calculated for commercial banks from FDIC, Bank Operating
Statistics, 1980, a n d the Federal Reserve Bulletin, various issues; for S&L's
from FHLBB, C o m b i n e d Financial Statements, 1 9 8 0 a n d miscellaneous
news releases.
The last column of the table indicates that a
doubling of asset size (or other measure of S&L
output) is expected to cut the operating cost
ratio by less than 25 basis points. The typical
estimate, in fact, is substantially less than this—
approximately seven to 12 basis points.
Cost savings from mergers actually may be
even less. In most of these studies, when the
relationship between asset size and operating
cost was estimated, the number of branches was
held constant Mergers, of course, do not conform
to such statistical niceties—in a merger, both
asset size and the number of offices necessarily
increase. The larger number of offices w o u l d
increase operating cost, partially offsetting the
estimated cost savings shown in Table 2.
In their 1969 study, Brigham and Pettit concluded that a merger would be expected t o
produce cost savings as a result of economies of
scale. They calculated that the total operating
cost for a single S&L w i t h assets of $500 million
and 9 branches would, in most cases, be about
1 5 to 35 percent less than the cost of operating
ten $50 million unit S&Ls (associations without
branches). However, in a study done at about the
same time, Benston reported results suggesting
that a merger would not produce any cost
savings.
More recently, Henry Cassidy has shown that
the equations developed in Atkinson's 1977
study produced results more consistent with
Benston's conclusions. He estimated that costs
would be about 10 percent higher at an association with five branches than the total for five unit
associations, each of which is one-fifth as large.
However, the results were mixed, providing
some support for the Brigham and Pettit conclusions. Thus, as Cassidy has indicated, the issue of
whether a merger will reduce costs has yet to be
resolved.
In the t w o most recent studies shown in Table
2, a variable representing the number of offices
was not held constant in the regression analysis.
In other words, the number of branches was
allowed to vary with asset size. Both of these
studies found evidence of cost savings as size
increases, lending support to the idea that a
merger reduces cost.
Such cost savings should be small, however,
for mergers among institutions of roughly equal
size. The ratio of operating costs to average
assets for the S&L industry was 1.35 percent in
1980 and 1.42 percent in 1981. The estimated
cost savings of seven to 12 basis points from
doubling asset size, the result suggested by most
of the studies reviewed here, would not improve
operating expense ratios significantly.
Merging a relatively small association into a
large association, however, could offer an effective way of dealing with a profit squeeze at the
smaller association. For example, estimated operating costs for associations in the $50 million
asset range are about 1.4 percent of assets. This
drops rapidly to a range of 1.0 percent to 1.1
percent as asset size reaches the $500 million to
$1 billion range (12). This would imply a reduction
of 30 percent to 40 percent in operating cost at
the disappearing institution as a result of the
merger.
Operating Costs of Florida S&Ls
Estimating the extent of economies of scale
requires statistical analysis of data on operating
cost and other variables at a cross section of
associations. Operating cost includes all non-
24
NOVEMBER 1982, E C O N O M I C
REVIEW
Table 2. Summary of Previous Research Results on Economies of Scale at S&Ls
Author, year
of publication,
and reference
number
Period studied
and sample
design
Measures of
S&L output
utilized
Elasticity
estimate(s)
Estimated reduction in
the operating expense
to assets ratio from a
doubling in output'
Atkinson,
(1979)
[1]
1975
(1,878 S&Lsnational sample)
Total assets
0,84 to 0.91
7 to 11 basis points
Atkinson,
(1977)
[2]
1974
(1,200 S&Ls7 states2)
Total assets
0.86
8 to 9 basis points
Benston
(1969)
[3]
1963-66
(3,159 S&Lsnational sample)
(1) Number of
loans made;
(2) Number of
loans serviced;
and
(3) Number of
savings
accounts
0.91 to 0.94
5 to 7 basis points
Brigham and
Pettit
(1969)
[6]
1962-66
(approximately 450
S&Ls-Chicago,
Cleveland, Detroit,
Los Angeles SMSAs)
Total assets
N.A.
12 to 17 basis points
Carron
(1981)
[8]
1980
(approximately
4,000 S&Lsnational sample)
Total assets
N.A.
12 basis points 4 ' 5
McNulty
(1981)
[12]
1979
(approximately
360 S&Lssix area samples)
Total assets
.82 to .98
(median = .92)
10 to 24 basis points 5
Morris
(1978)
[13]
1976
(187 S&LArizona, California
and Nevada)
(1) Total loans
closed (dollar
amount) and
(2) Number of
savings accounts
(1) 0.90 for loans
closed
(2) 0.98 for number
of accounts
(1) 6 basis points^
(2) Virtually no cost
savings-1 for number
of accounts
Verbrugge, Shick
and Thygerson
(1976)
[14]
1971-72
(478 S&Lsnational sample)
Total assets
N.A.
7 basis points
3
'Estimated by the author from the equations a n d / o r other information provided in each study
'Arizona, California, Colorado, Illinois, Kansas, O h i o a n d T e x a s
^Assuming that a doubling of lending activity, or other o u t p u t measure used in the sudy, results in a doubling of a s s e t s
" B a s e d on unpublished results d o n e in c o n n e c t i o n with this study, as supplied by the author
5
B a s e d on an a s s u m e d increase in asset size from $ 2 5 0 million to $ 5 0 0 million.
interest costs, such as wages and salaries, office
occupancy expenses, advertising, fees for professional services, and so forth. This study is based
on 1980 data for 117 Florida savings and loan
associations. All insured associations file detailed
financial reports with the Federal Home Loan
FEDERAL RESERVE BANK O F A T L A N T A
Bank Board twice a year, and these reports
provided most of the required data. The sample
excludes associations in existence less than two
years.
Previous studies have often used national data.
However, many factors affecting operating cost
25
vary from area t o area. Associations operating in a
similar market environment should provide a
more appropriate basis of comparison. The industry is large and diverse in Florida and the range of
operating cost ratios experienced by Florida
S&Ls is similar to that for the country as a whole.
Therefore, the Florida results can be generalized
t o apply t o other areas of the country.
Elsewhere in this Review, Benston et a/ have
criticized the use of assets as a measure of total
output for commercial banks. Their argument
has to do with a bias introduced by the large
variation in average loan and deposit size among
commercial banks in different asset size groups.
There is also some variation in average loan and
deposit size among individual S&Ls, but it is no
doubt much less, particularly in a sample restricted
to one state. Thus the bias introduced by using
assets as the output measure is likely t o be less
important in S&L cost studies.
On the surface, a simple statistical analysis of
data on operating costs and total assets would
seem to provide the necessary information. However, many factors besides asset size affect
operating cost. These include the number of
branches, the extent to which the association is
involved in mortgage banking activity, the mix of
savings accounts, the percentage of liabilities
representing borrowed money, and wage and
salary levels in the local market(s) served by the
association.
Through multiple regression analysis, a mathematical equation was fit to the data on operating
cost, asset size, and 14 other variables likely to
affect operating costs. This has the effect of
holding these "other" factors constant, so that
the relationship between size and operating cost
can be measured.
This S&L cost study is the first to utilize a
regression form known as a"translog cost function."
Analysts w h o have used the translog form prefer
it because of its flexibility, since it does not
impose any particular shape on the cost function.
This particular functional form has been used
increasingly in economies of scale studies during
the past six years.2 The appendix contains a
detailed description of the regression equation
that was estimated, as well as a description of the
"other" variables and estimates of their effect on
operating cost.
2
O n e of the first studies was by Christensen a n d Greene (10). Another
important study is Brown, Caves a n d Christensen (7). This form w a s also
used in the two recent commercial bank studies c i t e d earlier (5,11).
26
Chart 1 . Estimated Operating Expense Ratios
Florida Savings and Loan Associations, 1980
Percent
A=
F = 25 branches
C = 10 branches
G = 3 0 branches
H = 3 5 branches
D = 15 branches
'
I = 4 0 branches
J = 4 5 branches
K = 5 0 branches
E = 2 0 branches
1 branch
B = 5 branches
I
I
L
Source: Table 3
Statistical Results
Table 3 and Chart 1 show how the estimated
operating cost ratios change as asset size changes.
W e also calculated the normal number of offices
for associations in various asset size groups.
These results are shown in Table 4, which is
based on an equation described in the appendix.
Operating cost numbers are omitted from Table
3 for asset-branch combinations outside the
normal range. For example, it is possible to
estimate the operating cost ratio for an S&L with
$2.5 billion in assets and one office. Since no
such S&L exists, however, this calculation would
not be meaningful, so is not shown in the table.
On the surface, the results suggest the existence
of substantial economies of scale. For example,
an association with assets of $50 million and five
offices has an estimated ratio of operating cost to
average assets of 1.63 percent (Table 3). The
ratio for an association with the same number of
offices (five) but an asset size of $500 million
would be only 0.94 percent. Similarly, for an
association with 20 offices, the ratio goes from
1.24 percent to 0.92 percent as assets increase
from $500 million to $2 billion.
While these cost savings are substantial, they
are not representative of what most associations
can achieve. Few association managers can increase their asset size tenfold or even fourfold
NOVEMBER 1982, E C O N O M I C
REVIEW
Table 3. Estimated Operating Expense Ratios
Florida Savings and Loan Associations, 1980
Branches
Assets
$ millions)
25
50
100
200
250
400
500
750
800
1,000
1,250
1,500
1,750
2,000
2,250
2,500
2,750
3,000
1
1.913
1.552
1.235
.965
.888
5
10
15
1.633
1.411
1.196
1.130
.996
.935
1.670
1.494
1.312
1.254
1.132
1.075
.974
.958
.904
1.386
1.332
1.220
1.166
1.069
1.054
1.001
20
1.286
1.235
1.142
1.128
1.077
1.026
.985
.951
.921
25
1.203
1.188
1.139
1.089
1.049
1.015
.986
.960
30
1.144
1.104
1.070
1.041
1.016
.993
35
40
45
50
1.153
1.120
1.091
1.066
1.043
1.023
1.004
1.164
1.136
1.111
1.088
1.068
1.050
1.152
1.130
1.110
1.091
1.191
1.169
1.149
1.130
Source: Estimated from the translog cost model described in the appendix. The "other" factors influencing oeprating cost w e r e held constant at their average
level in calculating the ratios.
while keeping their number of offices constant,
except perhaps over a long period of time.
Furthermore, as noted earlier, these cost savings
cannot be realized in a merger, which normally
involves simply combining t w o branch systems
into one.
Table 5 provides a better perspective on the
cost savings from mergers. The figures represent
estimates of the change in the operating cost
ratio from selected 50 percent and 100 percent
increases in both asset size and the number of
offices. For example, if an association with assets
of $50 million and five offices were t o merge with
another association of the same size, the operating cost ratio is estimated to decline from 1.63
percent to 1.49 percent, a decline of 14 basis
points.
It can be seen that the cost savings diminish
rapidly once asset size reaches a certain level. For
example, if t w o $500 million associations with
identical branch systems are put together, average
costs stay approximately the same. For a merger
of two $1 billion institutions, costs actually increase
slightly. Thus cost savings from a merger of t w o
associations of similar size apparently disappear
once the asset size of the resulting institution
reaches $500 million. Thus, when branches are
allowed t o vary along with assets, the estimated
average cost curve for S&Ls is the traditional Ushaped curve.
To check the reliability of these results, w e
performed an additional test by estimating a
model which directly related the operating expense ratio t o asset size and a number of other
financial ratios. The results of this "ratio model"
follow the general form of the results shown
here, and clearly confirm the existence of economies of scale. The ratio model did show lower
cost savings at small asset size levels, but costs
continued to decline until asset size reached
about $1 billion. At this point, both approaches
predict little or no further cost savings when asset
size and the number of offices are increased
proportionately.
How to Control Cost
I n a study several years ago for the U.S. League
of Savings Associations, Verbrugge et a/ (14)
27
FEDERAL RESERVE B A N K O F A T L A N T A
1
Table 4. Estimated Number of Offices for
Associations of a Given Asset Size
Florida Savings and Loan Associations, 1980
Assets
{$ millions)
Table 5. Estimated Cost Savings from Selected 50
and 100 Percent Increases in Asset Size
and the Number of Branches
Estimated Numberof Offices
Average
Range
Assets
From
50
100
250
500
750
1,000
1,250
1,500
1,750
2,000
2,250
2,500
5
6
8
12
16
20
23
27
31
35
39
43
1 -13
1 -14
1 -16
4-20
8-24
12-28
23-31
19-35
23-39
27-43
31 - 4 7
35-50
Source:Estimated from the Branch System Size e q u a t i o n described in
the appendix. The range is t w o standard errors on each side of the
regression line. This interval c o n t a i n s o v e r 9 5 % of the associations under
consideration.
found the operating cost ratio to be one of the
four key financial ratios influencing association
profit performance. The data in Table 3 suggest
something important about the influence of
branch offices on cost: with a given asset size,
associations with fewer offices tend to experience
much more favorable operating cost ratios. This
would indicate that associations (and financial
institutions in general) will want to be cautious in
expanding their branch systems.
Because of differences in their markets, and
their aggressiveness in branching, the n u m b e r o f
offices varies widely for associations of the same
asset size. (Table 4 shows the ranges for the
number of offices at which 95 percent of the
associations in Florida were operating in 1980.)
Associations operating at the lower end of these
ranges can achieve operating cost ratios of 0.9
percent to 1.0 percent. However, associations
operating at larger asset sizes, but in the middle
or upper end of their ranges, experience much
higher operating cost ratios. In addition, associations with a total number of offices in the lower
end of these ranges can experience operating
cost ratios as much as 25 percent lower than
associations in the high end of the same range.
28
To
No. of
Offices
From
Operating Cost
Ratio
To
From
To
Change
50
100
5
10
1.63 1.49
-0.14
100
100
200
200
5
10
10
20
1.41 1.31
1.49 1.44
-0.10
-0.05
200
200
400
400
5
10
10
20
1.20 1.13
1.31 1.29
-0.07
-0.02
250
250
500
500
5
10
10
20
1.13 1.08
1.25 1.24
-0.05
-0.01
500
750
10
15
1.08 1.07
-0.01
0.94 0.90
1.08 1.08
1.17 1.19
-0.04
500
500
500
1,000
1,000
1,000
5
10
15
10
20
30
750
750
750
1,500
1,500
1,500
10
15
20
20
30
40
0.97 0.99
1.07 1.10
1.14 1.20
+0.02
+0.03
+0.06
1,000
1,000
1,500
1,500
10
20
15
30
0.90 0.91
1.08 1.10
+0.01
+0.02
1,000
1,000
2,000
2,000
10
20
20
40
0.90 0.92
1.08 1.14
+0.02
+0.06
1,500
1,500
2,250
2,250
20
30
30
45
0.99 1.02
1.10 1.15
+0.03
+0.05
1,500
1,500
1,500
3,000
3,000
3,000
15
20
25
30
40
50
0.91 0.95
0.99 1.05
1.05 1.13
+0.04
+0.06
+0.08
0.00
+0.02
Source: Table 3
One way to control costs is t o limit the number
of offices relative t o asset size. The data in Table
3 indicate that this may be an even more effective
method of achieving low expense ratios than
expanding assets.3 Clearly, the results suggest
quite strongly that economies of scale cannot be
achieved by aggressive branching, since this
would tend t o push up the number of o f f i c e s more than in proportion to asset size.
,
,
•
Summary and Conclusion
Previous research indicates that economies of
scale exist in the savings and loan industry, but
3
Records maintained at t h e F H L B o f Atlanta indicate that, despite the severe
profit squeeze, only a few associations in the Southeast have closed any
offices within t h e past year.
NOVEMBER 1982, E C O N O M I C
REVIEW
y
that the potential cost savings from most types of
consolidation are small. This was confirmed in an
analysis of 1980 data on 117 savings and loan
associations in Florida The estimated cost savings
are substantial in movingfrom low asset sizes (for
example, $50 million) to the $500 million level
but are exhausted after asset size reaches $500
million. This conclusion applies t o proportional
increases in asset size and the number of offices.
Limiting the number of offices relative t o asset
size appears t o be a more effective way of
controlling cost than does unrestrained asset
growth.^
The author would like to thank David Humphrey, Robert Ott, David
Roddy, Philip Webster and James Zabel for helpful comments and
discussion, and Kathryn Whitehead for statistical assistance on this
paper.
—James E. McNulty
Assistant
Vice
President-Economist,
Federal Home Loan Bank of
Atlanta.
REFERENCES
1. Atkinson, J a y F. "Firm Size in the Savings a n d Loan Industry." Invited
Research W o r k i n g Paper No. 29, Federal H o m e Loan Bank Board
(December 1979).
2
"The Structure of Cost in t h e Savings a n d Loan Industry
During 1974." Research Working Paper No. 67, Federal H o m e Loan
Bank Board ( M a r c h 1977).
3. Benâton, George J. "Cost of Operations a n d Economies of Scale in
Savings a n d Loan A s s o c i a t i o n s " Study of t h e Savings a n d Loan
Industry, Federal H o m e Loan Bank Board. Washington: U.S. Gove r n m e n t Printing Office, 1970, 677-761.
4
"Economies of Scale of Financial Institutions." Journal
of M o n e y , Credit, a n d Banking (May 1972).
5. Benston, George J., Hanweck, Gerald A a n d Humphrey, David B.
"Scale Economies in Banking: A Restructuring a n d R e a s s e s s m e n t "
J o u r n a l of M o n e y Credit, a n d Banking (November 1982, forthcoming).
6. Brigham, Eugene F. a n d Pettit, R. Richardson, "Effects of Structure
on Performance in the Savings a n d Loan Industry." Study of t h e
Savings a n d Loan Industry, Federal H o m e Loan Bank Board.
Washington: U.S. Government Printing Office, 1 9 7 0 9 7 1 - 1 2 0 9 .
7. Brown, Randall S., Caves, Douglas W. a n d Christensen, Laurits R.
" M o d e l l i n g the Structure of Cost a n d Production for Multiproduct
Firms." S o u t h e r n E c o n o m i c J o u r n a l (July 1979).
8. Carron, Andrew S. T h e Plight of t h e Thrift Institutions. Washington:
Brookings Institution, 1982.
9. Cassidy, Henry J. "S&L Branching and Operating C o s t s " Research
Working Paper No. 75, Federal H o m e Loan Bank Board (March
1978).
10. Christensen, Laurits R. and Greene, Willima H. "Economies of Scale
in U.S. Electric Power Generation." J o u r n a l of Political E c o n o m y
(August 1976).
11. Gilligan, T h o m a s W. Smirlock, Michael L. a n d Marshall, William J.
"Cost Complementarities Scale Economies a n d Natural Monopoly
in Banking." Federal Reserve Bank of Chicago. P r o c e e d i n g s of a
C o n f e r e n c e o n Bank Structure a n d Competition, 1 9 8 2 (forthcoming; also available a s W o r k i n g Paper No. 82-5, S c h o o l
of Business Administration, W a s h i n g t o n University, St. Louis).
12. McNulty, J a m e s E. " E c o n o m i e s of Scale in the S&L Industry: New
Evidence a n d Implications for Profitability." Federal H o m e Loan
Bank Board J o u r n a l (February 1981).
13. Morris James R. "Economies of Scale at District S & L s " Commentary,
Federal H o m e Loan Bank of San Francisco (July 1978).
14. Verbrugge, James A Shick, Richard A a n d Thygerson, K e n n e t h J.
"An Analysis of Savings a n d Loan Profit Performance." J o u r n a l of
F i n a n c e (December 1976).
15. Wolken, John D. a n d Navratil, Frank J. "Economies of Scale in Credit
Unions: Further Evidence." J o u r n a l of F i n a n c e J u n e 1980).
29
FEDERAL RESERVE B A N K O F A T L A N T A
APPENDIX
Translog M o d e l . This is the first S&L scale e c o n o m y
s t u d y t o e m p l o y t h e t r a n s l o g cost model. This m o d e l
has b e e n used in industrial sector studies by Christensen
a n d G r e e n e (10) a n d Brown, C a v e s a n d C h r i s t e n s e n
(7). It recently has b e e n applied to commercial banking
by B e n s t o n , H a n w e c k a n d H u m p h r e y (5) a n d Gilligan,
S m i r l o c k a n d M a r s h a l l (11).
T h e f o r m of t h e e q u a t i o n is:
log C = a + b log Q + c (log Q) 2 / 2 + d log B
+ e log Q • log B + 1 fi log Xj
W h e r e C = o p e r a t i n g cost, Q = o u t p u t ( r e p r e s e n t e d by
a s s e t s in t h i s study), B = n u m b e r of o f f i c e s a n d
r e p r e s e n t s o t h e r f a c t o r s a f f e c t i n g cost.
This f u n c t i o n a l f o r m is c o n s i d e r e d by r e s e a r c h e r s in
this area to be a substantial improvement over t h e
simple logarithmic function which has a constant
elasticity, a n d t h u s d o e s not a l l o w t h e a v e r a g e c o s t
c u r v e t o t u r n u p w a r d at s o m e point. T h e s i m p l e
l o g a r i t h m i c f u n c t i o n " f o r c e s " e c o n o m i e s of s c a l e t o
exist at all levels of o u t p u t , if t h e d a t a i n d i c a t e s that
t h e y exist o n average. T h e d i s t i n g u i s h i n g f e a t u r e s of a
t r a n s l o g f u n c t i o n , in contrast, are t h e (log Q ) 2 t e r m a n d
t h e i n t e r a c t i o n t e r m (log Q - l o g B). (The a b o v e f o r m is
slightly d i f f e r e n t f r o m a p u r e t r a n s l o g f u n c t i o n , w h i c h
would require a separate squared term for each
v a r i a b l e i n c l u d e d in an i n t e r a c t i o n t e r m In t h i s c a s e
this w o u l d r e q u i r e i n c l u s i o n of a (log B ) 2 t e r m in t h e
e q u a t i o n . H o w e v e r , a r e g r e s i o n w h i c h i n c l u d e d this
v a r i a b l e p r o d u c e d r e s u l t s w h i c h w e r e not realistic.)
R e s u l t s of t h i s t r a n s l o g f u n c t i o n , e s t i m a t e d w i t h
d a t a o n 1 1 7 s a v i n g s a n d l o a n a s s o c i a t i o n s in Florida
for t h e y e a r 1 9 8 0 , a r e s h o w n in T a b l e A-1. T h e " o t h e r
f a c t o r s " a f f e c t i n g o p e r a t i n g c o s t are t h e v a r i a b l e s
f o u n d t o b e s i g n i f i c a n t in an earlier s t u d y of o p e r a t i n g
c o s t a n d s c a l e e c o n o m i e s by A t k i n s o n (1). All data,
e x c e p t f o r t h e local a r e a w a g e rate, c o m e f r o m semia n n u a l r e p o r t s e a c h a s s o c i a t i o n files w i t h t h e F e d e r a l
H o m e L o a n B a n k Board. T h e best available proxy f o r
inter-area w a g e d i f f e r e n c e s is p r o b a b l y p e r - c a p i t a
income, s o c o u n t y or ( w h e n a p p l i c a b l e ) S M S A perc a p i t a i n c o m e w a s u s e d as t h e w a g e variable.
T h e p e r f o r m a n c e of t h e e q u a t i o n is impressive, w i t h
e i g h t of t h e v a r i a b l e s statistically s i g n i f i c a n t w i t h t h e
expected sign. Nonetheless, not too much importance
s h o u l d b e p l a c e d o n t h e h i g h R 2 term. T h i s m e r e l y
r e f l e c t s t h e fact that l a r g e r a s s o c i a t i o n s have a h i g h e r
a b s o l u t e level of total o p e r a t i n g c o s t t h a n s m a l l e r
a s s o c i a t i o n s , w h i c h w o u l d b e t r u e r e g a r d l e s s of t h e
b e h a v i o r of a v e r a g e cost. N o n e t h e l e s s , it s h o u l d b e
n o t e d that t h e c l o s e l y r e l a t e d F-statistic of 6 3 2 . 5 w a s
t h e h i g h e s t of a n y e q u a t i o n that w a s tested.
In t h e a b o v e m o d e l t h e elasticity of c o s t w i t h r e s p e c t
t o o u t p u t c a n b e c a l c u l a t e d as f o l l o w s :
T a b l e A - 1 . S u m m a r y of R e g r e s s i o n R e s u l t s
Translog Cost Function
Variable
Coefficient
t-Statistic
Constant
Log (Assets)
(Log (Assets))2/21
Log (Total Number
of Offices)
(Log (Assets)) * (Log
(Number of Offices))
Log (Wage Rate)
Log (Scheduled Items)2
Log (Other Loans)3
Log (Loans Serviced
For Others)
Log (Loans Serviced
By Others)
Log (Borrowed Money) 4
Log (Passbook Savings)
Log (Investment in
Service Corporations)
Stock Or Mutual 5
-7.69645
1.36783
-0.0385634
-1.26834
1.294
2.033
1.004
2.335
0.0733443
2.531
0.242230
-0.00112127
-0.0286108
0.00449619
2.423
0.2298
1.406
2.128
-0.00637744
2.765
0.00235612
0.0749267
0.00841176
0.7661
1.191
1.962
0.106537
2.114
2
R : 0.9876
R2: 0.9861
Durbin-Watson: 1.7018
F-Statistic (13,103): 632.5
' U s i n g one half of t h e squared term simplifies the calculation of the
elasticity. This has no effect on the other results, since t h e percent
c h a n g e in the squared term is unaffected.
S c h e d u l e d items include foreclosed real estate o w n e d a n d loans that
are delinquent or in default, as well as loans to facilitate the sale of
foreclosed real estate.
3
Other Loans include c o n s u m e r loans, education loans, loans on
savings accounts, h o m e improvement loans a n d mobile h o m e loans.
" B o r r o w e d M o n e y includes Federal H o m e Loan Bank Advances a n d
other b o r r o w i n g s
5
Stock equals one, zero otherwise.
Note: The d e p e n d e n t variable is total operating expense. All variables
except the number of offices a n d the d u m m y variable are in dollar
amounts. The asset variable is average assets, c o m p u t e d over t h r e e
semiannual periods.
Thus, t h e elasticity varies w i t h t h e level of o u t p u t a n d
t h e n u m b e r of offices, r a t h e r t h a n r e m a i n i n g c o n s t a n t ,
as it w o u l d in a s i m p l e l o g a r i t h m i c f u n c t i o n . T a b l e A-2
s h o w s t h e e s t i m a t e d elasticity for s e l e c t e d asset
sizes a n d n u m b e r of offices. It s h o u l d be n o t e d a g a i n
that t h e s e c a l c u l a t i o n s a s s u m e t h a t it is p o s s i b l e t o
i n c r e a s e a s s e t s w i t h o u t i n c r e a s i n g t h e n u m b e r of
offices.
It s h o u l d b e e m p h a s i z e d in t h i s c o n t e x t that t h e
n e g a t i v e c o e f f i c i e n t of t h e B ( n u m b e r of offices) t e r m
has n o m e a n i n g by itself. T h e e l a s t i c i t y of c o s t w i t h
r e s p e c t to t h e n u m b e r of o f f i c e s is:
d log C
= d + e log Q
d log B
d log C
= b + c log Q + e log B
a log Q
w h i c h is positive f o r all o u t p u t (asset sizes) levels
e x c e p t for t h e very smallest.
30
N O V E M B E R 1982, E C O N O M I C
REVIEW
a
»
Table A-2. Estimated Elasticity of Cost with Respect
to Output
Table A-3. Summary of Regression Results
Ratio Model
Coefficient
Variable
Assets
($ millions)
Number of
Offices
50
50
100
100
250
250
500
500
1,000
1,000
1,500
1,500
2,000
2,000
2,500
2,500
1
10
1
10
5
15
5
20
10
25
20
35
20
40
30
50
Elasticity
0.684
0.853
0.657
0.826
0.740
0.821
0.713
0.815
0.738
0.805
0.773
0.814
0.762
0.812
0.783
0.820
Note: The elasticity has been calculated in the conventional way, which
assumes that assets can be increased without an increase in the
number of offices.
Ratio Model. The results of this model are shown in
Table A-3. This model was estimated to serve as a
check on the results of the translog model. The fit
cannot be compared directly with that of the other
equation because the dependent variable is a ratio.
However, the fit does compare favorably with ratio
models estimated in other studies (e.g. (6), (8), (11),
(14)). Nonetheless, there are less statistically significant
coefficients than in the translog equation. As noted in
the text, the ratios estimated from the ratio equation
shown in Table A-3 do confirm the existence of
economies of scale; however, economies are less in
the under $500 million asset range, but they extend
out to $1 billion when the effects of proportional
increases in assets and in the number of offices are
calculated.
Branch System Size Equation. Table A-4 shows
the results of a simple regression of the number of
offices on asset size, for the same 117 associations.
This equation was used to estimate the "average"
number of offices for associations of a given asset
size. From this we constructed a normal range for the
number of offices at each asset size level (Table 4 in
the text), so as to avoid reporting estimated cost ratios
that would not be representative or meaningful. This
normal range was set at two times the standard error
of the estimate, on either side of the estimated value.
With a standard error of estimate of 4, this led to a
range of ± 8 offices on either side of the fitted value.
The actual data were then evaluated, and over 95
percent of the observations fell within the confidence
interval.
Constant
Assets
(Assets)2
Number of Offices
(Assets)*(Number of
Offices
t-Statistic
2.832
3.049
0.9413
0.1739
0.7927
0.609988
—6.78547(E-10)
1.27676(E-19)
0.00185660
7.14398(E-12)
4.86297(E-5)
Wage Rate
Ratio: Scheduled Items - 0 . 0 1 0 8 1 9 9
to Assets
0.00479122
Ratio: Loans Serviced
For Others to Assets
Ratio: Loans Serviced
0.00290794
By Others to Assets
0.00511514
Ratio: Other Loans
to Assets
0.00670078
Ratio: Borrowed Money
to Assets
0.0173610
Ratio: Passbook
Savings to
Total Savings
-0.0294030
Ratio: Investment in
Service Corporations
to Assets
0.294797
Stock Or Mutual
2
R : 0.3557
R2: 0.2744
Durbin-Watson: 1.5851
F-Statistic (13,103): 4.374
2.325
0.2026
1.462
1.120
0.2304
1.018
4.433
0.3551
3.597
Note: The d e p e n d e n t variable is the ratio of operating cost to average
assets expressed in percentage terms. All other variables are as defined in
Table A-l.
Table A-4. Summary of Regression Results
Branch System Size Equation
Variable
Coefficient
t-Statistic
Constant
4.23264
8.330
Assets
1.57135(E-81)
20.420
R2: 0.7838
Durbin-Watson: 1.6535
F-Statistic: (1,115): 416.8
Standard Error of the Regression: 4.275
Note: The d e p e n d e n t variable is the number of offices.
31
FEDERAL RESERVE B A N K O F A T L A N T A
Bank Size
and Risk:
A Note on
the Evidence
A review of the literature finds
little evidence that small banks
operate with greater risks than
large banks.
The relationship between risk and size of financial
institutions may play a vital role in the evolution
and stability of our financial system. Three possibilities exist: large banks are more risky than
small banks, small banks are more risky than
large banks, or large and small banks are equally
risky. Everything else equal, the greater the risk of
variation in income or of failure assumed by
banks of various sizes, the greater the cost of
capital and other liabilities that they need in
order to grow. Therefore, the structure of our
financial system (the numberand size distribution
of financial institutions) will ultimately depend in
part upon the relationship between bank size
and risk. This extremely important issue has
received little or no direct empirical testing.
Most of the evidence on risk and size must be
gleaned from side results of empirical studies of
other problems such as capital adequacy, interest
rate risk, or identification of potential problem
banks.
There are four main sources of risk for financial
institutions. First, credit or default risk, the risk
that borrowers will not repay or will not repay on
schedule. Second, the risk associated w i t h variability of interest rates, which stems from the fact
that financial intermediaries must borrow or at
least pay interest on a majority of the funds they
lend and may not be able to match maturities of
the funds they lend against the funds they
acquire. Third, operating risk, a measure of how
32
N O V E M B E R 1982, E C O N O M I C REVIEW
well expenses and liquidity are managed. And
fourth, the risk associated with fraud or insider
abuse by management. Reviewing the empirical
literature on each of these risks and their association
with bank size indicates that we know far too
little about bank size and risk.
Credit Risk
There is no direct empirical evidence or good
indirect evidence showing a systematic relationship between a bank's size and its ability to
control its credit risk position.
There has not been a string of either large or
small bank failures due t o credit risk, but there is
evidence that large and small banks each face
unique types of credit risk. Small banks may find
themselves more geographically limited and hence
more dependent on the health of a specific type
of industry than d o large banks. Therefore, small
bank exposure to unforeseen regional or national
economic events may be greater than for large
banks, which tend to have greater geographic
and industry loan diversity. The vulnerability of
small rural banks to problems in the farming
industry was highlighted in 1977. Rural banks
had liquidity problems because their loan portfolios were heavily directed toward farmers w h o
were experiencing hard times resulting in their
inability t o repay their loans. The dependence of
small banks on their local economy is also
demonstrated by the current recession (See 16).
These risks, however, may be equalized by those
faced by large banks which must keep current on
large, diversified portfolios. Recently the problems
of diversification have been graphically illustrated
to banks w i t h international loans, (some loans to
Poland and/or Mexico are being restructured).
(See 10, 12).
The only empirical study on the attitude of
bank managers toward risk looked at the relative
riskiness of bank holding company banks (which
included almost all large banks) and independent
banks (which are typically smaller banks). The
study concluded that holding company bank
managers take more credit risks (14).
Interest Rate Risk
Bank interest rate risk depends on the bank's
vulnerability t o changes in interest rates. Unless
banks are able to perfectly match interest rates
and maturities of their liabilities and assets, some
interest rate risk will exist. Researchers have
found little if any systematic relationship between
large and small banks and their interest rate risk
exposure (5, 6, 7).
Use of financial futures markets is one way to
help control interest rate risk. Recent surveys of
the use of financial futures markets by banks and
savings and loan associations indicate that few
small banks presently use these markets (3, 8).
As banks increase in size, they are more likely to
use the financial futures markets. This may be
because small banks have less need t o hedge
their portfolios or because they have some
inherent disadvantage in hedging (1). Presently,
however little quantitative evidence exists that
there are differences between large and small
banks in interest rate risk exposure.
Operating Risk
Financial institutions face the risks of poor
expense control, poor product design and poor
liquidity management that afflict all firms. The
extent of these risks depends primarily on how
well the institution is managed and on the
complexity of the problems it faces. Management
problems are likely t o be simpler in smaller
organizations. Yet claims have often been made
that smaller banks are less able to attract the best
managers. In any event, there seems to be no
strong tendency for problems associated with
poor operating management to be associated
with financial institutions of a particular size.
Management Risk
The inability t o control expenses due t o poor
management is a serious problem, but a much
more serious problem arises from management
dishonesty and greed. These risks are manifest in
fraud, forgery, insider transactions and dishonest
acts by the bank's staff. Unfortunately, the bank
failure and early warning system literature reveals
that these risks are the primary cause of most
bank failures. Joseph F. Sinkey, Jr. (18) writes,
"For over 167 years, the major cause of bank
failures, dishonest bank managers, basically has
remained the same. The form has varied but the
driving force has not changed." These problems
are usually the most difficult to protect against.
The importance of managerial risk is seen in
the record of bank failures since 1960. From
1960 to May 1976,84 insured commercial banks
failed. FDIC records indicate that the principal
33
FEDERAL RESERVE BANK O F A T L A N T A
causes of failure of 45 of these banks were
insider loans and out-of-territory loans (often
connected with brokered deposits). Twenty-five
more failures were principally caused by embezzlement or other management manipulation.
Only 14 failures (17 percent of the total) resulted
from bad loans made in the bank's local area
(18).
Overall Risk
Two sets of empirical literature assess overall
bank risk. The first is the capital adequacy literature
covering the problems of determining how much
capital is necessary to buffer banks against potential losses. The second is the literature on
early warning systems which would allow regulators t o identify problem banks prior t o the
problem. Both sets of studies are extensive, yet
the size-risk relationship is seldom addressed.
The capital adequacy literature shows that
capital ratios are higher at small banks than at
large banks. In addition it shows that regulators
require higher capital ratios for smaller banks.
Therefore, either banks abide by regulation or
smaller banks in fact have more risk and compensate for this risk by holding more capital. Studies
by Peltzman (15) and Mayne (11) indicate that
regulations have little influence on bank capital
ratios, while a study by Mingo (14) reaches the
opposite conclusion. Wolkowitz (19) finds that
small banks are inherently riskier but that they
hold more capital to'compensate for that risk.
Therefore, when management decisions are made,
actual risk appears to balance out for small and
large banks. Dince and Fortson (2) also find that
bank size and capital adequacy are not related.
The "early warning system" literature studies
the characteristics of banks which have failed or
which have appeared on a regulator problem list
(See 4 for a summary). These studies generally
controlled for bank size in the sampling process,
which implicitly assumes that size is not important
One of the early warning studies that did consider
size explicitly found no relationship between
bank size and vulnerability (9). Another study
which did not control for size in its sample
selection found that the characteristics which
best distinguished problem banks did not include
size (17).
Conclusion
There has been little systematic study of the
size-risk relationship for financial institutions.
M u c h of the evidence that exists is in the form of
incidental evidence from studies of other aspects
of these institutions. Although little is known, our
review of the literature leads to t w o general
conclusions. First, no systematic evidence exists
that small banks are at a competitive disadvantage
in terms of risk. O n this front, therefore, small
banks appear to be on equal footing with large
banks. And second, as banking competition
becomes more intense, risk borne by banks will
become increasingly important. The topic deserves much more attention than it has received.
—David D. Whitehead and Robert L Schweitzer
Schweitzer
is assistant
professor
of
University
of
economics,
Delaware.
REFERENCES
1. Dew, J a m e s Kurt. "David a n d Goliath: A Skirmish in the HedgeRows." A m e r i c a n Banker, VoL 147, (September 14, 1982) pp.
4-7.
2. Dince, Robert R. a n d J. C. Fortson. "The Use of Discriminant Analysis
to Predict Capital Adequacy of C o m m e r c i a l B a n k s " J o u r n a l of
Bank Research Vol. 3 , 1 9 7 2 , pp. 54-62.
3. Drabenstott, Mark a n d A n n e O. McDonley. "The Impact of Financia!
Futures on Agricultural B a n k s " E c o n o m i c Review, Federal Reserve
Bank of Kansas City, (May 1982), pp. 19-30.
10. Martin, S a r a h "The Secrets of the Polish Memorandum." E u r o m o n e y
(August 1981), pp. 9-15.
11. Mayne, Lucille S. "Supervisory Influence on Bank Capital." J o u r n a l
of F i n a n c e Vol. 2 7 (June 1971) pp. 6 3 7 - 6 5 1 .
12. " M e x i c o ' s Moratorium Puts Damper on
C o m m e r c e (August 27, 1982) p. 5A.
Market." J o u r n a l
of
13. Mingo, J o h n J. " M a n a g e r i a l Motives, M a r k e t Structure a n d the
Performance of Holding C o m p a n y B a n k s " E c o n o m i c Inquiry, Vol.
14 (September 1976) pp. 4 1 1 - 4 2 4 .
4. Eisenbeis, Robert A "Financial Early Warning Systems: Status a n d
Future Directions." Issues in B a n k Regulation (Summer 1977), pp.
8-12.
14 .
5. Flannery, Mark J. " M a r k e t Interest Rates a n d Commercial Bank
Profitability: An Empirical Investigation." J o u r n a l of F i n a n c e
(December 1981), pp. 1 0 8 5 - 1 1 0 1 .
15. Peltzman, Sam. "Captial Investment in C o m m e r c i a l B a n k i n g a n d Its
Relation t o Portfolio Regulation." J o u r n a l of Political E c o n o m y
(January/February 1970), pp. 1 -26.
6
16. "Recession Has Bankers W a t c h i n g Loan Quality." ABA B a n k i n g
Journal, Vol. 7 4 (July 1982).
"The Impact of M a r k e t Rates on Small Commercial
B a n k s " Rodney L White Center of Financial Research, W o r k i n g Paper
No. 10-81, August 1981.
7. Hanweck, Gerald A a n d Thomas E Kilcollin. " B a n k Profitability a n d
Interest Rate Risk." Research Papers in Banking a n d Financial Economics, Board of Governors of the Federal Reserve System, July 1981.
8. Koch, Donald L , Delores W. Steinhauser a n d Pamela Whigham.
"Financial Futures as a Risk M a n a g e m e n t Tool for Banks a n d
SaLs." E c o n o m i c Review, Federal Reserve Bank of Atlanta, Vol. 5 7
(September, 1982), pp. 4-14.
9. Korobow, Leon, David P. Stuhr a n d Daniel Martin, "A Probabilistic
Approach to Early Warning of Changes in Bank Financial Condition."
Financial Crises: Institutions a n d M a r k e t s in a Fragile
Environment, ed. Edward I. Altman a n d Arnold W. Sametz (New
http://fraser.stlouisfed.org/
York: J o h n Wiley a n d Sons) 1977.
Federal Reserve Bank of St. Louis
"Regulatory Influence on B a n k Capital Investment."
J o u r n a l of F i n a n c e Vol. 130 (September 1975) pp. 1 1 1 1 - 1 1 2 1 .
17. Sinkey, J o s e p h F„ Jr. "A Multivariate Statistical Analysis of the
Characteristics of Problem B a n k s " J o u r n a l of Finance, Vol. 3 0
(1975) pp. 21-36.
18. Sinkey, Joseph F. Jr. "Problem a n d Failed Banks, Bank Examinations,
a n d Early Warning Systems: A Summary." F i n a n c i a l Crises:
Institutions a n d M a r k e t s in a Fragile E n v i r o n m e n t ed. E d w a r d I.
Altman a n d Arnold W. Sametz (New York: J o h n Wiley a n d Sons)
1977.
19. Wolkowitz, Benjamin. " M e a s u r i n g Bank S o u n d n e s s " in Bank
Structure a n d C o m p e t i t i o n . Federal Reserve B a n k of Chicago,
1975.
Changes in Large Banks'
Market Shares
From 1974 through 1981, larger
banks in the Southeast generally
lost market share to smaller
local competitors. Evidence
strongly supports that conclusion
for other areas of the country
over the past 15 years.
Several factors help determine the competitive
position of individual banks. Size, risk assumed,
management strategies, and past behavior are
thought t o play important roles. Studies of these
factors allow us to assemble evidence on their
impact t o project how a particular type of bank
will perform. An alternative way to study the
impact of these factors, particularly size, is t o
observe how a certain group of banks performs
in a total environment without isolating individual
factors.
Evidence on bank operating costs and risk
indicates that, above a relatively small size,
commercial banks do not gain
operating efficiency or reduce
risk t o any significant degree.
Other factors that might give
large banks significant competitive advantages, such as economies of scope, the ability to
invest in innovations, the ability
t o ride out errors, the concern
of regulators to keep them from
failing, have received less study.
Students of banking find it difficult to put together all the
evidence to project or explain
banks' market performance.
Banks, on the other hand,
put all of these factors together
in their markets every day. Operating costs, risk, regulatory
compliance costs, innovation,
regulatory attitudes and other
factors influence each day's
35
FEDERAL RESERVE BANK O F A T L A N T A
operations. One way to determine whether larger
banks enjoy significant competitive advantages in
local markets is to study their market performance.
If larger banks have (and use) advantages over
smaller banks, w e would expect t h e m t o gain
market share at the expense of smaller banks.
Lower costs of operations, risk taking, and the
ability t o handle the expense of developing new
products or t o ride out errors would allow larger
banks to offer lower prices or higher quality service
than smaller competitors. If they did so, then
customers w o u l d gravitate t o them from their
smaller competitors.
But studies indicate that personal and business customers are loyal t o their financial
institutions. Nevertheless, turnover in both business and consumer markets w o u l d allow banks
using price or service advantages to gain business relative t o their competitors over an extended period of time.
Evidence on the actual market performance of
large and small institutions comes from recent
direct studies of the subject and from another
group of studies by economists interested in
competition in local banking markets. These latter economists have performed several studies
of changes in the market shares of larger banks in
these markets. While these studies were not
conducted specifically t o test the relative performance of larger and smaller banks, the evidence
presented in them is relevant.
Studies indicate that smaller institutions generally have not been a t a disadvantage relative t o
large competitors over the past decade and a
half. This seems true in all sizes of markets and in
each geographic area studied. Evidence comes
from a variety of empirical work already published
and is confirmed by new work on banking markets
in the Southeast presented here for the first time.
• • • • • • • • • • • • ^ • • • • • • • ^ ^ • • • • • • • • • • • • • • • • • • • H H
"Studies indicate that smaller
institutions generally have not
been at a disadvantage relative
to large competitors over the
past decade and a half."
Our new evidence also indicates that, although
large banks generally have lost market share in
36
local markets, they have not been losing local
market share because outside institutions are
taking business away from them rather than from
smaller banks. Nor do they seem t o be losing
share because they are refraining from using
their competitive advantages so as t o keep
prices and profits high.
Studies of the Performance of Small
Institutions
Two recent studies of the performance of
small financial institutions (11) (12) during 19781980 found no evidence that smaller institutions
are not viable competitors. Both studies deal
with institutions in Standard Metropolitan Statistical Areas (SMSAs); one covers commercial
banks, the other savings and loan associations. The
authors of each compare performance of small
firms w i t h that of larger ones in the same
economic environment. Although smaller banks
and S&Ls report somewhat lower returns, they
are also clearly less risky. The studies also find
that, while there has been no difference in the
growth rates of small and large S&Ls, smaller
banks have grown faster than larger ones. 1
Studies of Large Banks' Market Shares
Another set of relevant studies looks at changes
in the market shares of larger banks relative t o
their smaller competitors. The most comprehensive of these, covering 213 SMSAs and 233 large
non-SMSA counties between 1966 and 1975
(16), recorded changes in market share of the
three largest banking organizations in each area.
If their share rose, it would offer some indication
that large banks enjoy significant advantages. In
general, however, their share declined rather than
increased. Of the SMSAs, 86 percent recorded a
falling share for the largest firms; of the nonSMSA counties, 79 percent recorded a falling
share. The average three bank share declined
from 75.8 t o 69.3 percent in the SMSAs and from
81.2 t o 78.4 percent in the non-SMSA counties.
The study also found that the three largest banks
lost most in markets where their 1966 share was
greatest. It did not, however, screen out the concurrent influence of other factors on market
share change.
' F o r o l d e r s t u d i e s of t h i s issue — w h i c h r e a c h similar c o n c l u s i o n s s e e (1)
a n d (8).
NOVEMBER 1982, E C O N O M I C
REVIEW
Another national study of market structure
changes covering a smaller sample of markets
produced similar results. The Rhoades (9) study
covered the 1966-1976 period and included only
152 SMSAs that had not had their boundaries
changed during the period and a sample of 129
non-SMSA counties. Over the period and t w o
subperiods, more than 80 percent of the SMSA
markets showed declining in market shares for
the largest three banks. In 71 percent of the county
markets, the largest three banks also lost share.
Two regional studies - one from the Midwest
and one from the Southeast - confirm the findings
of the national studies. The most recent of these
covers 53 SMSAs and 233 non-SMSA counties
with more than three banking organizations in
Illinois, Indiana, Iowa, Michigan and Wisconsin
(2). This study covers smaller areas and more
recent experience (1965-1979) than the national
studies summarized above, but its conclusions
are quite similar. Of the SMSAs, 85 percent
recorded declines in the combined market share
of the three largest banks; of the non-SMSA
counties, only 53 percent recorded declining
concentration. As in the national studies, concentration declined t o a greater extent in areas
with higher initial concentration.
Another regional study was carried on at the
Federal Reserve Bank of Atlanta in 1976 (18) and
is the springboard for new empirical evidence
presented in the next section of this article. That
study covered 98 banking markets in Alabama,
Florida and Tennessee during the 1970-1974
period. Its principal purpose was t o determine if
market concentration had increased in markets
entered by multi-bank holding companies; however, it also presented evidence on the general
issue of large bank market performance.
A comparison of 1970 and 1974 three-bank
concentration in 98 markets w i t h three or more
banks in 1970 indicated that the larger banks
had lost share in 62 (63 percent) of the markets
and only maintained share in 26 more. They had
gained market share in only 10 markets. In the 75
markets w i t h five or more banks in 1970—that is,
markets in which there are smaller banks available t o compete throughout the period—the
largest three banks lost share in 59 (79 percent)
and managed only t o maintain shares in seven
more. As was the case in other studies, large
banks in markets w i t h higher initial concentration were likely to lose a greater market share
(7).
Table 1 . Concentration Change, Markets with
Five Banks or More in June, 1981
State
Alabama
Florida
Georgia
Tennessee
Total
Number of Markets
with Decrease
Total Number Percent
29
19
65.5
24
29
82.8
69.2
13
9
14
12
85.7
85
64
75.3
with Increase
Number Percent
10
34.5
5
17.2
4
30.8
2
14.3
21
24.7
Recent Evidence from the Southeast
Our latest study adds both markets and time
to evidence from Alabama, Florida and Tennessee.
It covers the period from 1974 t o 1981 and
includes markets from Georgia as well as the
three states covered previously. Eighty-four
markets with five banking organizations or more
are included. The market areas are those used by
the Board of Governors of the Federal Reserve
System in decisions on bank holding company
acquisitions and bank mergers. They are defined
on the basis of study of banking patterns in local
areas and are updated on the basis of changing
local conditions (1 5 and 17).
The study excludes eight markets for which
the market definition was changed after 1974.
Each of these markets was redefined during the
study period t o include an expanded geographic
area. This in itself resulted in a decline in the
market share held by the largest banks. The
markets were excluded t o avoid any bias toward
a general conclusion that large bank market
shares were declining.
The evidence from Sixth District markets is
summarized in Table 1 and 2. The three largest
banks lost market share in over three quarters of
these markets, losing in each state and in
markets of all sizes. The average share held by
the three largest banks declined from 76.8 percent in 1974 t o 72.2 percent in 1981 —a drop of
almost 6 percent. As Table 2 indicates, the three
largest banks' share declined by almost 9 percent in Florida markets but by only 1.2 percent in
Georgia markets.
If changes in bank operations and competition
during the 1970s have changed large banks' performance, results of this most recent study
37
FEDERAL RESERVE BANK O F A T L A N T A
Table 2. Concentration Change, Markets with Five Banks or More
Average Concentration
Change 1974-1981
State
1974
1981
In Average
Alabama
Florida
Georgia
Tennessee
J59
.768
.804
.757
.727
.699
.794
.694
-.032
-.069
-.010
-.063
Percent
in Average
-4.217
-8.984
-1.244
-8.322
Total
.768
.722
-.046
-5.989
should be expected t o differ from previous
results. Yet results are quite similar t o previous
studies.
Explanations for Large Banks' Losses
Even if larger banks have lost market share, it
does not show conclusively that they have suffered competitive disadvantages. At least t w o
alternative explanations are possible. First, outside competitors may be taking more business
from larger banks than from smaller ones. Nonlocal and non-bank competitors are not included
in measures of local market size and share
because data on their local business generally is
not available. Consequently, large banks may
appear t o lose share to small ones w h e n they are
losing to non-local and non-bank competitors.
Second, one may argue that large banks refrain
from capitalizing on their advantages to charge
lower prices, pay more for deposits or provide
higher quality services in order to gain higher
profits. If this were so, one might find these
banks retaining or losing their market share
rather than gaining.
W e tested for these two alternative explanations
and found that neither holds up well. If nonbank
and nonlocal competitors have entered markets
and taken business away from larger banks w e
would expect their entry to have its greatest
impact in the most attractive markets. Multivariate tests of the determinants of changes in
larger banks' shares indicate that neither market
size nor market growth—two indicators of a
market's attractiveness—was related t o the
decline in large bank shares in southeastern
markets. (See the Appendix for an explanation of
the tests.)
Average
Percent Per
Market
-3.758
-8.686
-1.184
-8.138
5.732
The consistency of the study results also
implies that competitors from outside the banking industry and local markets have not differentially affected large bank shares. Markets of all
sizes have shown a decline in large banks' share
over all time periods since 1965. Yet rapid
expansion of nonlocal and nonbank competition
has been rather recent. Had this expansion
caused large banks to lose more local market
share, declining shares would have shown up in
later studies. This has not been the case.
Evidence does not entirely rule out the
possibility that large banks refrained from using
their advantages in order t o earn greater profits.
However, no supporting evidence has been
found in Southeast markets. I n three of the other
studies, tabular analysis indicated that the three
largest banks lost the highest share in markets
where they had held the highest initial share.
This type of market performance supports one
reason advanced for the ability of smaller banks
to compete with larger ones. Large banks may
refrain from exploiting some of their competitive
advantages if they are able t o earn long-run profits by doing so. Three previous studies of concentration change indicate that small banks gain
more ground when large banks hold a greater
market share—that is, when they have more
incentive to charge higher prices and/or provide
less quality. The other studies did not, however,
account for other factors that also might have
influenced large banks' share. Our study tested a
more detailed multivariate model and found no
relationship between changes in large banks'
share and the level of their share (see Appendix.)
Our tests indicate that large banks probably
have lost market share in local markets because
they have been at a competitive disadvantage of
38
NOVEMBER 1982, E C O N O M I C REVIEW
some sort. Neither differential effects of outside
and nonbank competitors nor large banks' reluctance t o use advantages seem t o explain their
loss of market share. A final element of the multivariate model gives a clue t o the identity of the
banks that gained from large bank losses and
suggests at least one dimension of large bank disadvantages. Our tests found that the entry of
new banks into local markets was closely related
to large banks' loss of market share. The introduction of new banks was followed by greater
market share loss for large banks. This finding is
consistent w i t h results of a studies of de novo
entry by Rose and Savage (13 and 14). They
found that new banks whether independent or
"Our tests found that the entry
of new banks into local markets
was closely related to large
banks' loss of market share."
started by bank holding companies made significant contributions t o decreasing concentration
of local market deposits in larger banks.
That new banks should gain market share
seems reasonable for several reasons. Their
organizers would not start them nor w o u l d
regulators approve them w i t h o u t considerable
confidence that they w o u l d attract profitable
business, that is, gain market share. In addition,
new banks are often organized by investors w h o
d o substantial banking themselves and w h o
move their business to the new institution. Finally,
most new banks in larger markets have opened
in suburban areas that grow more quickly than
the d o w n t o w n areas that are headquarters of
larger banks.
An interesting extension of this study w o u l d
be an examination of the market shares of
smaller banks that existed in local markets at the
beginning of our study period. Did they also lose
share to new banks or did they also gain share at
the expense of larger banks?
Studies reported here consistently indicate
that in the recent past smaller banks have performed at better than par with larger ones in local
markets. The smaller banks have been about as
profitable (when profits are adjusted for risk) and
have generally gained market share. Attributing
this phenomenon to mismeasurement of market
share and noncompetitive behavior of large
banks does not seem t o fit. It seems more likely
that larger banks have been at a competitive disadvantage in relation to smaller banks in some
basic product lines.
—B. Frank King
REFERENCES
1. Darnell, J e r o m e C. a n d H o w a r d Keen, Jr. "Small B a n k Survival: Is the
Wolf at t h e Door?" Business Review Federal Reserve Bank of
Philadelphia (November 1974) pp. 16-23.
10. Rhoades, S t e p h e n A. "Structure a n d Performance Studies in Banking: A S u m m a r y a n d Evaluation." Staff Economic Studies, No. 92,
Board of Governors of the Federal Reserve System, 1977.
2. Erdevig, Eleanor. "District Trends in Banking Concentration."
E c o n o m i c Perspectives, Federal Reserve B a n k of Chicago, Vol. 5
(March/April 1981) pp. 6-12.
11. Rhoades, S t e p h e n A a n d Donald T. Savage. " C a n Small B a n k s Compete?" T h e Bankers M a g a z i n e (January/February 1981) pp. 5965.
3. Farrar, D . E a n d R.R. Glauber. "Multi-collinearity in Regression
Analysis: The Problem Revisited." R e v i e w of E c o n o m i c s a n d
Statistics, Vol. 4 9 (February 1967), pp. 92-107.
12. Rhoades, S t e p h e n A a n d Donald T. Savage. "The Performance of
Small versus Large Savings and Loan Associations: Can the Small
Associations Survive?" T h e B a n k e r s M a g a z i n e (forthcoming).
4. Heggestad, Arnold A. a n d S t e p h e n A. Rhoades. "An Analysis of
C h a n g e s in Bank M a r k e t Structure." Atlantic E c o n o m i c Journal,
Fall 1976, pp. 64-69.
13. Rose, J o h n T. a n d D o n a l d T. Savage. " B a n k Entry a n d Market Share
Redistribution." S e p t e m b e r 1 9 8 2 (mimeo).
5. Hooks, Donald L. a n d T e r r e n c e F. Martell. " M u l t i b a n k Holding Company Acquisitions a n d Local Market Structure: An Analysis of
Pooled Cross Section a n d Time Series D a t a " Research Paper 81 0 1 0 , Federal Reserve Bank of S t Louis, 1981.
14. Rose, J o h n T. a n d D o n a l d T. Savage. " B a n k H o l d i n g C o m p a n y Entry
and Banking Market Déconcentration." Journal of Bank Research,
Vol. 13 ( S u m m e r 1982), pp. 9 6 - 1 0 0 .
15. Schweitzer, Paul R. "The Definition of B a n k i n g Markets." Banking
Law Journal, Vol. 9 0 (September 1973).
6. King, B. Frank. " C h a n g e s in Seller C o n c e n t r a t i o n in Banking
Markets." Working Paper, Federal Reserve Bank of Atlanta (March
1977).
16. Talley, S a m u e l H. " R e c e n t Trends in Local B a n k i n g M a r k e t Structure." Staff Economic Studies, No. 8 9 Board of Governors of t h e
Federal Reserve System.
7. King, B. F r a n k "Entry, Exit, a n d M a r k e t Structure C h a n g e in Banking." W o r k i n g Paper, Federal Reserve Bank of Atlanta (March
1979).
17. Whitehead, David D. "Relevant Geographic Banking Markets.
How S h o u l d They Be Defined?" E c o n o m i c Review Federal
Reserve Bank of Atlanta (January/February 1980), pp. 20-29.
8. Kohn, Ernest. T h e F u t u r e of S m a l l Banks. Albany, N.Y.: N e w York
State B a n k i n g Department, 1966.
18. Whitehead, David D. a n d B. Frank King. " M u l t i b a n k Holding
C o m p a n i e s a n d Local Market Concentration." Monthly Review,
Federal Reserve Bank of Atlanta (April 1976) pp. 34-43.
9. Rhoades, Stephen A "Geographic Expansion of Banks a n d Changes
in Banking Structure." Staff Economic Studies No. 102, Federal
Reserve Board.
39
FEDERAL RESERVE B A N K O F A T L A N T A
APPENDIX
To provide some evidence on the relationship of
market power of the largest banks to changes in their
shares, we developed and tested a model of concentration change. It follows the development in Working
Papers previously published by the Federal Reserve
Bank of Atlanta (6 and 7).
As explained in the text, large bank forebearance
might be thought to result from use of market power
even though large banks were more efficient. One
would expect such forebearance to be more likely the
larger the large banks' market share. Thus one feature
of the model is market share of the market's three
largest banks measured in the beginning year, 1974.
Market growth may also influence large banks'
share in two ways. First, by providing new business
opportunities and attracting migration, growth brings
in bank customers not previously attached to a local
bank. Second, growth may attract new bank competitors that apparently take market share from large
banks. (See 6) Market growth has two dimensions in
this case: the percentage change in market size and
the absolute change in size. In order to capture both
aspects, variables for percentage change in market
deposits and for total market deposits were used.
effect, but some studies find multi-bank holding companies both increasing and decreasing concentration
of business in larger banks. A variable to measure the
change in the number of multibank holding companies operating in each market was included in
the model.
These variables were regressed against the percentage change in concentration in the local markets
used in this study. The table below gives the results of
this multiple linear regression.
Only one factor was closely related to changes in
the market shares of the three largest banks. That was
the change in the number of organizations competing
in the market. Greater increases in the number of
competitors—greater entry—were associated with
greater declines in large bank shares. Market growth,
size, concentration and bank holding company activity
were not significantly related to concentration
change. 1
The equation explained almost 30 percent of concentration change, and the relationship was highly
significant. This level of explanation is quite satisfactory in view of the slowness with which changing
market conditions appear to be felt in market
We would also expect large banks' market share to
be influenced over time by changes in the number of
firms competing in the market. Additional firms would
be expected to enter only if they could take market
share from larger firms; exiting firms would give larger
firms an opportunity to increase their share.
Bank holding company activity has also been discussed as an influence on concentration (See (5) and
the next article in this Review, for summary of the
evidence.) Evidence of holding company effects is mixe d A majority of studies find no bank holding company
' W e c o n s i d e r e d the possibility that c h a n g e in t h e n u m b e r of c o m p e t i t o r s
a n d market g r o w t h might be closely related, c a u s i n g problems related
to multicollinearity. P e r c e n t a g e market growth a n d market size
explained less than 7 percent of the c h a n g e in the number of competitors in m a r k e t s in this sample. In addition exclusion of the market
growth variable from the model h a d only minor influence on other coefficients. Both facts indicate minimal multicollinearity. See (3).
Appendix Table Concentration Change Model: Regression Results
Variable
Deposit growth 1974-81
(percent, annual average)
Deposits 1974 (billion $)
Three organization
concentration, 1974
Change in number of
competing organizations,
1974-1981 (percent)
Change in number of multibank
holding companies represented, 1974-1981
Constant
Regression
Coefficient
Standard
Error
-.213
.182
-1.169
-1.435
1.039
-1.380
184
6.661
.027
-184
—5.009a
.036
-245
1.039
.360
-.882
5.273
-.167
Dependent variable: Change in three-organization concentration, 1 9 7 4 - 1 9 8 1 (percent)
"R2 — . 2 5 1 a
a
D i f f e r s f r o m 0 at .01 level.
40 N O V E M B E R 1 9 8 2 , E C O N O M I C
REVIEW
The Impact of
Local Market Entry
by Large Bank Holding Companies
Five years after selected large bank holding companies entered new
local markets, their subsidiaries showed no significant advantages
over comparable independent banks. In fact, after seven years, the
independents had gained market share on the larger holding
company banks.
If there are advantages conferred by size in
banking, they may not be limited t o large
individual institutions. Subsidiaries of larger
multi-institution organizations may have competitive advantages over smaller independent
organizations. Three states in the Sixth Federal
Reserve District have large multibank holding
companies that acquired banks during the
1970s. If membership in large organizations conferred cost or product advantages on an acquired
bank, its market share would grow and/or its
returns w o u l d increase relative t o competitors.
W e w o u l d expect banks acquired by the largest
organizations in District states to gain market
share or have higher profits than similar independent banks.
This article reports on a study that compared
the performance of t w o groups of Sixth District
banks acquired by large bank holding companies with the performance of their independent counterparts. W e looked at a group of
banks started c/e novo (not acquired by merger
or acquisition) by the four largest bank holding
companies in Alabama, Florida and Tennessee
between 1972 and 1975 and a group of larger
banks—the largest or second largest in their
markets—acquired by the four largest bank
holding companies in the same states during
those years. W e compared the de novo banks'
market share and profit performance w i t h that of
a control group of independent de novo banks
chartered in their markets during the same
period. W e compared the larger banks' performance with that of larger independent banks in
their markets. Both groups of banks were
followed for several years after holding company
acquisition—the small banks for five years and
the large ones for seven.
Our study indicates that large bank holding
companies did not offer significant advantages to
the banks they started or acquired, even several
years after acquisition. De novo banks started by
holding companies did enjoy higher assets,
deposits and rates of returns than independents
after five years of operation, but this seems to be
the result of special circumstances in which the
holding companies merged their smaller de
novo banks into other subsidiaries. Larger banks
". . . large bank holding
companies did not offer
significant advantages to the
banks that they started or
acquired, even several years
after acquisition."
acquired by large holding companies lost market
share to independent competitors through
seven years after acquisition. They also lost
ground in rates of return and in risk. Our results
cover a longer period after acquisition than d o
most studies of banks acquired by holding companies, but the results seem quite consistent
with other studies.
Evidence From Other Studies
Previous studies indicate little advantage for
subsidiaries of multibank holding companies as a
whole. Four groups of studies are relevant. A
fairly extensive volume of literature compares
the performance of banks acquired by multibank companies w i t h independent banks of
similar size in the same markets. (See Currey (2)
for a detailed summary.) The studies are consistent in their major conclusions that bank holding
company acquisition results in some changes in
acquired banks' asset portfolios and increases in
their operating expenses and income. The net
effect is that these changes produced no significant changes in return on equity of acquired
banks relative t o independents. Acquired banks,
however, have been leveraged t o a greater
extent. Studies that look at growth of acquired
and independent banks find no difference between the two.
Another set of studies culminates in the survey
of bank costs detailed in this Review. These
studies generally conclude that subsidiaries of
multibank holding companies enjoy no cost
advantages over banks that are not holding company subsidiaries.
A third set of studies analyzes changes in concentration in markets entered by bank holding
companies. (A highly concentrated market is one
where a small number of firms hold a large share
of the market.) These studies attempt to determine whether banking business in markets
entered by multibank holding companies becomes
more concentrated in a few firms after entry (4,
6, 7, 8, 10, 11, 17, 18, 21). A majority of these
studies conclude that bank holding company
entry has no impact on the concentration of
deposits in the entered market. There are,
however, contradictory studies concluding that
concentration is either increased or decreased
by holding company entry. A study of concentration change in 228 SMSAs by Heggestad and
Rhoades (4) concludes that concentration became
greater in markets entered by multibank companies. O n the other hand, three studies of
Alabama markets by Hooks and Martell (6, 7, 8)
and a case study of Colorado markets by
Schweitzer and Greene (17) find declining concentration after entry by multibank companies.
Whitehead's study of the impact of large bank
holding companies on local market performance
concludes that large companies tend to influence
market prices if not market structure (20).
The mixed results of these studies should not
be surprising. Bank holding companies enter
markets in many ways likely t o impact concentration differently. If acquisition confers advantages, w e would expect the market share held by
42
N O V E M B E R 1982, E C O N O M I C
REVIEW
large banks to increase if a large bank is acquired
but to shrink if a small or de novo bank is
acquired. Thus the manner of entry would be
crucial to the impact of bank holding company
acquisition. Yet only t w o of the studies considered that determinant.
A more relevant set of studies looks at market
performance of individual banks acquired by
multibank holding companies. These studies
follow the acquired banks for several years. In a
study of 71 banks acquired between 1965 and
1970, Goldberg (3) found no significant change
in market shares. His results were mirrored in
Burke's broader study of 227 banks acquired
between 1962 and 1970 (1). Burke reported
some subtle tendency for larger banks to lose
market share and smaller ones t o gain share.
In a series of studies, Rose and Savage
examined the performance of bank holding
company subsidiaries after acquisition. These
studies emphasize market share changes. Rose
and Savage found that relatively large banks
acquired by holding companies not otherwise
represented in their market lost share and that
small ones gained share (12). De novo banks
acquired by bank holding companies performed
no differently from independent de novo banks
in aspects other than market share (15). I ndependents had a large edge in market share in less
concentrated markets but holding company
banks had a slight edge in highly concentrated
markets (13 and 14).
One case study that addresses this question
found minimal impact from large New York City
banks' entry into upper N e w York state after
branching and bank holding restrictions were
removed. The large New York City banks' market
penetration was modest and their competitors'
performance did not suffer (9). In a study of
banks acquired by t w o Florida companies,
Hoffman found no significant increase (or decrease) in the market shares of acquired banks
relative to a control group of independent banks
in their market (5).
These studies find little evidence of holding
company impact on market share. The studies
are, however, inadequate in one way or another.
Only Hoffman's study includes a control group,
and it covers a relatively short period and only
two companies. The studies by Goldberg and
Burke use no control group of independent
banks t o isolate bank holding effects.
Despite their limitations, the studies reviewed
here cast serious doubt on the proposition that
multibank holding companies confer enough
advantages on their subsidiaries to a l l o w t h e m t o
make substantial inroads on independent competitors. The studies are neither conclusive nor—
with the exception of the studies by Rose and
Savage—without fault; their weaknesses in today's
world relate to their treatment of all multibank
companies as the same, their lack of coverage of
recent years and their lack of control groups. If
holding company size is important, only large
companies may confer advantages. Recent
innovations may have increased large companies' ability to help their subsidiaries. W i t h o u t
a control group of independent banks, w e do not
know whether bank holding companies or some
other factor accounts for acquired banks'
performance.
Our study looks only at banks acquired by the
largest multibank organizations in their states. It
follows these banks over most of a decade to the
present, and provides a control group of independent banks against which to test the holding
company subsidiaries.
New Evidence From the Southeast
Large bank holding companies entered many
markets in Alabama, Florida and Tennessee during the early 1970s and have competed in these
markets since then. To test whether acquistion
by these large organizations conferred advantages that allowed acquired banks t o gain at the
expense of independent banks, we selected t w o
extreme groups of banks acquired by the four
largest bank holding companies in each state
and paired them w i t h similar independent banks
in their markets. W e then traced three major
elements of performance from the acquisition
during the 1972-1975 period to recent dates.
To capture crucial aspects of holding company
influence, we studied de novo acquisitions and
acquisitions of the largest or second largest
banks in the relevant markets. De novo acquisition is in many ways the purest type of holding
company acquisition. The acquired bank begins
life as a subsidiary. All future performance is
under holding company influence and there is
no past t o boost or drag down the bank. The
acquiring company has no one t o blame (or congratulate) but itself for the bank's performance.
43
FEDERAL RESERVE B A N K O F A T L A N T A
Acquisition of one of a market's largest banks
may leave a holding company w i t h a residue of
past management's brilliance or mistakes, but it
also gives the acquiring company the potential to
exercise market power. Thus this type of acquisition w o u l d seem likely t o confer advantages on
organizations that already had operated successfully in a local market
During 1972-1975, the four largest bank holding companies in each of the states of Alabama,
Florida and Tennessee acquired 26 de novo
banks for which w e could find matches of
independent de novo banks in the same local
market. 1 All but t w o of these pairs were in
Florida. During the same period, companies in
Alabama, Florida and Tennessee acquired 13
banks that were the largest or second largest
banks in their markets and could be matched
with an independent in their market that was
also of that rank.These t w o sets of pairs were
studied.
W e measured three aspects of performance.
To get an overall indication of relative performance, we studied market share differences. If
one type of institution possessed advantages
, over another, then w e would expect it to widen
the gap between its market share and that of the
other type of institution. W e tested differences
between acquired and independent de novo
banks. W e followed each pair of banks up
through 1981 or until one of the pair changed its
status by being acquired, merged or divested.
Since each de novo pair started from scratch, we
tested for significant differences in assets, deposits,
rates of return on assets and equity, capital t o
total assets and capital t o risk assets one, three
and five years after acquisition.
Each larger bank started with its own established
market share and earnings and risk ratios from
the time of acquisition through one, three, five
and seven years. W e tested for differences in
market share after acquisition; that is, whether
gaps in performance widened or narrowed.
Profits were analyzed because market share
might be gained by a bank willing to sacrifice
returns by pricing lower to attract customers.
Models of this type of behavior have been
•In o r d e r to be a m a t c h , t h e i n d e p e n d e n t must have b e g u n o p e r a t i o n no
more t h a n a year b e f o r e o r after t h e h o l d i n g c o m p a n y b a n k a n d h a d t o b e
l o c a t e d in t h e s a m e local market.
44
Table 1 . Pairs of Banks Remaining After Acquisition
Years After
Acquisition
One
Three
Five
Seven
De novo
Banks
Larger
Banks
26
25
14
7
13
13
12
12
developed to analyze the N O W account experience in New England and the behavior of
southeastern banks (19). The situations tested in
this study do not closely parallel the New
England experience; however, systematic differences in profitability over time may well cast
doubts upon the long-term viability of a group of
institutions. W e tested differences in both return
on assets and return on equity.
Finally, profitability difference may be related
to the risk taken by institutions. Consequently,
we tested for risk differences among institutions
by looking at capital t o assets and capital t o risk
assets ratios.
Our samples began w i t h 26 pairs of de novo
banks and 13 pairs of larger banks. Over time,
mergers of sample banks removed pairs from the
sample. Florida—a unit banking state before
1975—authorized countywide branching in
1975 and statewide branching by merger in
1980. Large bank holding companies in Florida
chose to merge their unit banks into larger multioffice institutions after 1975, removing some of
their de novo banks and one large bank from our
samples. The number of remaining pairs is
shown in Table 1. Our test followed de novo
banks for five years after acquisition and larger
banks for seven years.
New Banks
As the first t w o panels of Table 2 indicate,
holding company and independent de novo
banks performed much the same during the first
three years after the holding company acquisition. Differences between the groups are small
enough in any case that one cannot say they
were not accounted for by chance. Holding company subsidiaries were somewhat larger after
one year but somewhat smaller than independents after three years.
N O V E M B E R 1982, E C O N O M I C
REVIEW
T a b l e 2 . P e r f o r m a n c e of D e N o v o B a n k s
Table 3. Large Bank Performance
Performance
Measure
Variable
BHC
Mean
Independent
Mean
Difference
5.63
4.60
5.55
4.32
.08
.28
-.58
-.63
.05
-2.57
-2.24
-.33
29.36
30.95
-1.59
132.57
129.43
3.14
End of Third Year After Charter Year (n=25)
Assets (millions S)
Deposits (millions $)
Return on Assets
(percent)
Return on Equity
(percent)
Equity to Assets
(percent)
Equity to Risk
Assets (percent)
11.92
10.55
12.97
10.92
-1.05
-.37
-.37
-.25
-.12
-3.00
-1.77
-1.23
11.06
16.75
-5.69
16.33
22.90
-6.57
End of Fifth Year After Charter Year
Assets (millions $)
Deposits (millions $)
Return on Assets
(percent)
Return on Equity
(percent)
Equity to Assets
(percent)
Equity to Risk
Assets (percent)
Independent
Mean
Difference*
YearO
End of Charter Year (n=26)
Assets (millions $)
Deposits (millions $)
Return on Assets
(percent)
Return on Equity
(percent)
Equity to Assets
(percent)
Equity to Risk
Assets (percent)
BHC
Mean
21.78
19.52
13.9
12.42
7.88°
.142
-.221
.363
1.434
-6.924
8.360 b
8.37
9.98
-1.615
12.77
15.18
-2.405
7.09®
a
Differs from 0 at .005 level (two tailed test)
b
Differs from 0 at .025 level (two tailed test)
"-Differs from 0 at .05 level (two tailed test)
The independent de novo banks had lower
operating losses and took less risk through three
years. The differences are not statistically significant, however.
By the fifth year after holding company
acquisition, the subsidiaries appear to have
established a considerable advantage over independent banks. Deposits and assets of the holding company de novos are significantly larger
than those of independents. Holding company
banks have become profitable while paired
independents are still losing. These results
however, are not indicative of bank holding company advantages. During the same period between
the third and fifth year after acquisition, Florida's
holding companies chose to merge nine of the
Assets (millions $)
Market Share (%)
Return on Assets
Return on Equity
Equity to Assets
Equity to Risk Assets
41.80
30.70
1.07
14.45
7.43
9.42
46.56
35.38
1.05
13.75
7.67
9.71
-4.76
-4.68
.02
.70
-.24
-.29
Year 7
Assets (millions $)
Market Share (%)
Return on Assets
Return on Equity
Equity to Assets
Equity to Risk Assets
62.32
29.74
1.02
11.64
8.81
10.14
82.85
40.01
1.20
13.24
9.11
10.92
-20.53
-10.27
-.18
-1.60
-.30
-.78
*BHC mean minus independent mean.
sample's de novo banks into other subsidiaries.
(Three of the independent banks were also
merged into other banks. One was part of a pair
with a merged holding company bank.) Banks
that the holding company merged were significantly smallerand less profitable than those they
did not merge. The fifth year results thus indicate
a choice by the holding companies to eliminate
smaller, less profitable banks rather than demonstrating competitive advantages by the remaining banks. In o r d e r t o see if this selection by bank
holding companies influenced results of our
tests in the fifth year, we tested third year differences in only the pairs remaining after five
years. These tests showed that third year results
for the remaining pairs were quite similar to fifth
year results.
Overall, there is little indication that de novo
banks chartered by large bank holding companies possess significant advantages over independent de novo banks. In the three years
before holding company mergers eliminated
their smaller, less profitable subsidiaries from the
sample, there was no difference in assets,
deposits, profitability or risk that could not be
accounted for by chance.
Large Banks
Large banks acquired by bank holding companies lost ground to their paired independent
banks in the seven years covered in this study.
The changing relative position of bank holding
company subsidiaries is shown in Table 3. At year
45
FEDERAL RESERVE BANK O F ATLANTA
Table 4. Relative Performance of Larger Bank
Holding Company Acquisitions
Mean
Difference*
Variable
End of Acquisition Year n = 1 3
Market Share
Return on Assets
Return on Equity
Equity to Assets
-.377
.075
.047
.530 c
End of Third Year After Acqusition n = 1 3
Equity to Risk Assets
Market Share
Return on Assets
Return on Equity
Equity to Assets
Equity to Risk Assets
.340
—2.248d
-.124
-2.614d
.920
3.304 b
End of Fifth Year After Acquisition n = 1 2
Market Share
Return on Assets
Return on Equity
Equity to Assets
Equity to Risk Assets
-1.909d
-.215
-2.247
-.0255
-.935
End of Seventh Year After Acquisition n = 1 2
Market Share
Return on Assets
Return on Equity
Equity to Assets
Equity to Risk Assets
-4.970*
-.222
-2.291
-.0811
-1.043
»Changes in bank holding c o m p a n y data minus c h a n g e s in
independents' data, stated in percentage p o i n t s
a
D i f f e r s f r o m 0 at .005 level (two-tailed test)
^Differs from 0 at .01 level (two-tailed test)
c
D i f f e r s from 0 at .025 level (two-tailed test)
d
D i f f e r s from 0 at .05 level (two-tailed test)
end before acquisition—when all banks in the
sample were independent—banks that remained
independents had a 4.68 percent market share
advantage on the banks acquired by bank holding companies. The independents were less profitable and somewhat less risky.
By the seventh year after acquisition, the
independent banks had gained market share
while the holding company subsidiaries had lost
share. The independents enjoyed a 10.27 percent market share advantage, reported greater
returns on assets and equity and remained
less risky.
Larger independents gained on the larger
banks acquired by bank holding companies
several years after acquisition. As Table 4 indicates,
the independents and holding company subsidiaries had not, with one exception, changed in
significantly different ways during the first year
after acquisition. Duringthe first yearthe holding
company banks raised their equity-to-assets
ratio significantly.
During the three years after acquisition the
independents' relative increases in market share
and return on assets were statistically significant.
Bank holding company subsidiaries increased
equity-to-risk assets significantly more than
independents.
In the first five years after acquisition, the gap
between independents' market share and that
of holding company banks widened t o a statistically significant extent. The gap also widened in
the same direction in each of the other variables
but not to a statistically significant extent.
After seven years the independents had
established statistically significant gains in market
share only. Their gains in return on assets and
equity and equity-to-assets and risk assets were
greater than those of the subsidiary banks but
not significantly so.
On their face, these results indicate that
independents gained market share t o a significantly greater extent than bank holding company subsidiaries in the same markets without
sacrificing either returns or safety. The position of
the holding company as a resource for its subsidiaries makes statements about returns and
risk somewhat ambiguous, however. Through
various devices, holding companies may reduce
profits in their subsidiaries by charging various
flows to the parent company to tax deductible
expenses rather than dividends. At the same
time parent companies may bear risks for subsidiaries. Thus, relatively lower reported returns
and risk for bank holding company subsidiaries
may indicate a downward bias in the reporting of
returns and risk. N o such downward bias exists in
reporting holding company banks' market shares.
Summary and Implications
This study indicates that acquisitions by large
bank holding companies of de novo or larger
banks have not helped these banks increase
their market share relative to similar independent banks over a period of several years.2
2
A l t h o u g h this s t u d y c o n c e n t r a t e s on large h o l d i n g c o m p a n i e s , t h e evid e n c e may apply to all c o m p a n i e s . Rose a n d S a v a g e (12) p r e s e n t e v i d e n c e
that h o l d i n g c o m p a n y s i z e has little impact on p e r f o r m a n c e of large companies de novo banks.
46
NOVEMBER 1982, E C O N O M I C
REVIEW
"These larger (bank holding)
organizations do not seem
to be in a position to drive
independent banks out of
business."
• • ^ • H H M B B H B I i ^ H H M H B B H B H B M B H B H H i
Indeed, the larger banks that remained independent fared better than those acquired by
holding companies, at least in market share.
Results indicate also that large independents did
not gain share at the expense of higher profits or
lower risk.
These results are consistent with most other
evidence on the advantages of multibank holding companies. This study improves on the
others by observing acquired banks over a
longer period—up t o seven years—and by providing a specific control group, studying market
share, and bringing the experience to the present all at the same time. Its samples, however,
are relatively small and confined t o three states.
Additional work should be done.
If one accepts the findings of this study and
most similar studies and projects them into the
future, one finds implications on several fronts.
On-site results seem consistent w i t h cost study
results, which indicate no bank holding company advantages. These larger organizations d o
not seem t o be in a position t o drive independent banks out of business. Their entry w o u l d
seem unlikely to have the dire effects predicted
by some opponents of bank holding company
expansion at both state and national levels. In
addition, their seeming inability t o raise returns
on assets and equity at acquired banks casts
doubts on their capability to muster resources
needed to acquire large numbers of smaller
—B. Frank King
REFERENCES
1. Burke, James. " B a n k Holding C o m p a n y Behavior a n d Structural
Change." J o u r n a l of Bank Research, Vol. 9 (Spring 1978), pp. 4351.
11. Rose, J o h n T. " B a n k i n g Holding C o m p a n y Affiliation a n d Market
Share Performance." J o u r n a l of M o n e t a r y Economics, Vol. 9
(January 1982), pp. 110-119.
2. Curry Timothy J. "The Performance of Bank Holding Companies"
T h e Bank H o l d i n g C o m p a n y M o v e m e n t t o 1 9 7 8 . A Compendium. Washington, Board of Governors of the Federal Reserve
System, 1978, pp. 95-120.
12. Rose, John T. and Donald T. Savage. "Bank Holding Company
Performance a n d Holding C o m p a n y Size." August 1 9 8 2 (mimeo).
3. Goldberg, L a w r e n c e G. " B a n k Holding C o m p a n y Acquisitions a n d
Their Impact on Market S h a r e a " J o u r n a l of M o n e y , C r e d i t a n d
Banking, Vol. 3 (February 1976), pp. 127-30.
4. Heggestad, Arnold a n d S t e p h e n A Rhoades "An Analysis of
C h a n g e s in Bank Market Structure." Atlantic E c o n o m i c J o u r n a l
Vol. 4 (Fall 1976), pp. 64-69.
5. Hoffman, Stuart G. "The Impact of Holding Company Affiliation on
Bank P e r f o r m a n c e : A C a s e S t u d y of T w o F l o r i d a M u l t i b a n k
Holding Companies." Research Paper, Federal Reserve Bank of
Atlanta (January 1976).
6. Hooks, D o n a l d L. a n d Terrence F. Martell, "Effects of Multibank
H o l d i n g C o m p a n i e s on Local M a r k e t Concentration." J o u r n a l of
t h e M i d w e s t F i n a n c e Association (September 1979), pp. 5770.
13. Rose, J o h n T. a n d Donald T. Savage. " B a n k Holding Company de
novo Entry a n d Market S h a r e Accumulation." T h e Antitrust
Bulletin, Vol. 2 6 (Winter 1981), pp. 7 5 3 - 7 6 7 .
14. Rose, J o h n T. a n d Donald T. Savage. " B a n k Holding C o m p a n y de
novo Entry, Bank Performance, a n d Holding C o m p a n y Size."
August 1982 (mimeo).
15. Rose, J o h n T. a n d D o n a l d T. Savage. " B a n k H o l d i n g C o m p a n y
Performance: B a n k H o l d i n g C o m p a n i e s Versus I n d e p e n d e n t
Banks." July 1 9 8 2 (mimeo).
16. Schull, Bernard, "Multiple-Office Banking a n d t h e Structure of
Banking Markets: The New York a n d Virginia Experience," Conf e r e n c e on Bank Structure a n d Competition, Federal Reserve
Bank of Chicago, 1972.
17. Schweitzer, Paul a n d J o s h u a Green. "Greeley in Perspective." Staff
E c o n o m i c Studies # 9 1 Board of Governors of the Federal Reserve
System, 1977.
7. Hooks, D o n a l d L. a n d Terrence F. Martell. "The Impact of Multibank
Holding Company Acquisitions on Local Market Structure." Working
Paper, University of Alabama (August 1980).
18. Ware, R o b e r t F. " B a n k C o n c e n t r a t i o n in Ohio." E c o n o m i c
C o m m e n t a r y , Federal Reserve B a n k of Cleveland (November
1975).
8. Hooks, D o n a l d L a n d T e r r e n c e F. Martell. " M u l t i b a n k Holding
C o m p a n y Acquisitions a n d Local M a r k e t Structure: An Analysis of
Pooled Cross Section a n d Time Series D a t a " Research Paper 810 1 0 Federal Reserve Bank of St. Louis, 1981.
19. Whitehead, David D. "An Alternative View of Bank Competition:
Profit or Market Share Objectives?" E c o n o m i c Review, Federal
Reserve Bank of Atlanta, Vol. 6 7 (November 1982).
9. Kunreuther, J u d i t h Berry. " B a n k i n g Structure i n New York State:
Progress a n d Prospects." M o n t h l y Review, Federal Reserve Bank
of New York (April 1976), pp. 107-115.
10. Rhoades, S t e p h e n A "The Impact of Foothold Acquisitions on Bank
Market Structure." Antitrust Bulletin, Vol. 2 2 (Spring 1977), pp.
119-28.
20. W h i t e h e a d , D a v i d D. " H o l d i n g C o m p a n y Power a n d M a r k e t
Performance: A New Index of Concentration." W o r k i n g Paper,
Federal Reserve Bank of Atlanta, D e c e m b e r 1977.
21. Whitehead, David D. a n d a Frank King. " M u l t i b a n k H o l d i n g
C o m p a n i e s a n d Local Market Concentration." M o n t h l y Review,
Federal Reserve Bank of Atlanta (April 1976), pp. 34-43.
47
FEDERAL RESERVE B A N K O F A T L A N T A
An Alternative
View of
Bank
Competition:
Profit or
Share
Maximization
A study of 5 9 0 banks over eight years finds consistent
evidence that small banks seek to increase their market
share even at the expense of profits. Large banks, on the
other hand, apparently aim to maximize both profits and
market share.
Market forces w i t h i n the financial services
industry are driving regulators and legislators
to consider further deregulation. Both product
and market restraints on financial institutions
are being reconsidered seriously in light of new
communication technology, product innovation,
and cooperative competitive agreements among
what traditionally were considered noncompeting financial institutions.
As d e r e g u l a t i o n removes the artificial
restraints t o product and market d e v e l o p m e n t ,
consolidations among financial institutions
appear inevitable. 1 Although consolidations
will occur, the degree of consolidation is
questionable because there will always be a
' T o the e x t e n t that r e g u l a t i o n has r e s t r a i n e d t h e o p t i m a l size of f i n a n c i a l
institutions, d e r e g u l a t i o n will lead to m e r g e r s or c o n s o l i d a t i o n a m o n g
f i n a n c i a l institutions. As d e r e g u l a t i o n occurs, a larger n u m b e r of
f i n a n c i a l i n s t i t u t i o n s will be able to offer similar f i n a n c i a l services. This
will t e n d to i n c r e a s e t h e n u m b e r of c o m p e t i t o r s a n d r e d u c e t h e level of
m a r k e t c o n c e n t r a t i o n , m a k i n g it easier for similar i n s t i t u t i o n s t o
merge.
place for relatively small financial organizations
w h i c h are specialized and highly efficient. O n
one hand, consolidations may offer certain
benefits, such as those associated w i t h economies of scale and the consumer's ability t o
obtain many financial services from a single
institution. O n the other hand, consolidations
may involve certain costs t o society such as the
potential loss in c o m p e t i t i v e market performance from t h e removal of some small and
potentially innovative competitors.
Given the likelihood of deregulation and the
probability that many small competitors will be
eliminated through consolidations, it is essential
t o learn w h e t h e r c o m p e t i t i o n w o u l d be
decreased if the n u m b e r of small competitors
were reduced. This study addresses the question
by analyzing the c o m p e t i t i v e performance of
relatively large and relatively small banks in the
Sixth Federal Reserve District.
Conventional antitrust analysis is based on a
traditional theoretical m o d e l that assumes a
48
N O V E M B E R 1982, E C O N O M I C
REVIEW
firm's primary goal is t o maximize profits.
Given profit maximization as the firm's objective,
it is then possible t o d e p i c t t h e firm's conduct
in various market settings. The firm's conduct
or behavior t h e n determines its performance
(that is, prices, o u t p u t , profit or rate of return).
It follows that the interaction a m o n g firms in
the same market, all a t t e m p t i n g t o maximize
profits individually, will determine the market's
competitive performance. D e p i c t i n g all firms
as profit maximizers then allows for a rather
simple analysis of markets. Knowledge of the
markef s structure (number and size distribution
of firms in the market) and the presumed
conduct of firms in their efforts t o maximize
profits t h e n allows us t o project the market's
competitive performance. Markets w i t h high
concentration ( t w o or three firms controlling a
relatively large p o r t i o n of the market) are
presumed t o be less c o m p e t i t i v e (higher prices
and lower levels of o u t p u t ) than those w i t h low
levels of concentration. This rather simple
model forms the basis for the w e l l - w o r n
analytical tool that uses a market's structure t o
project its performance.
retail and commercial accounts. Second, these
competitive actions are almost certainly directed
at new customers, those just moving into a new
area or seeking t o establish a banking relationship. It is then primarily the growth in
banking consumers for w h i c h bankers are
overtly c o m p e t i n g — n o t the entire customer
base of a market.
This leads to a t h i r d and perhaps more
important observation: small banks may emphasize deposit growth t o a greater extent than do
their larger competitors. Both large and small
banks overtly c o m p e t e for the same set of
customers, but small banks have more t o gain
by attracting new customers than d o large
. . if small banks are
indeed the most likely to
stimulate competition within
a market, then the loss of
small banks may weaken
these markets' competitive
performance."
Casual Observation
Yet the competitive interaction among banks
in market settings raises questions about t h e
premise that all banks are profit maximizers.
Commercial banks are d e p a r t m e n t stores of
financial services. The average consumer seems
t o develop a close relationship w i t h his banker
because access t o future financial services may
d e p e n d on it. This leads t o customer loyalty
perhaps unparalleled in other industries. O n c e
people decide w h i c h bank t o deal with, it is
extremely difficult t o persuade t h e m t o change.
Consumer loyalty and mutuality of benefits
appear t o be at the root of this t y p e of
behavior. As a consequence bankers are less
likely t o c o m p e t e for each o t h e r s " current
customers than for u n c o m m i t t e d customers.
This is probably more t h e case for a small retail
account than for large retail or commercial
accounts. C o m p e t i t i o n for these latter types of
accounts is probably more personal and individualized than c o m p e t i t i o n for t h e small retail
or small commercial account.
Two observations, then, seem w o r t h w h i l e .
First, most o v e r t measures of c o m p e t i t i o n
within banking markets in fact measure the
intensity of c o m p e t i t i o n for relatively small
banks. Numerous studies on economies of
scale in banking show that significant reductions
in average costs are experienced only up t o
approximately $50 t o $75 million in deposits. 2
Past this point, as a bank expands its deposits it
experiences relatively constant average costs.
Therefore, by emphasizing deposit growth, t h e
small bank may lower its average costs and
thus increase its profit potentials. It follows
that a small bank may undertake overt competitive actions ( b o t h price and nonprice) in
order t o attract proportionately more deposits
than its larger c o m p e t i t i o n . Only after t h e small
bank has o b t a i n e d a size sufficient t o realize
available economies of scale (lowest average
costs) w o u l d it turn its attention t o profits.
N o w if w e f o l l o w this line of reasoning
further, w e may hypothesize that relatively
large banks and smaller banks in t h e same
markets may have different objectives. The
2
See G e o r g e J. Benston, Gerald A. Hanweck and David B. Humphrey,
" O p e r a t i n g Costs in Commercial Banking," this Review
49
FEDERAL RESERVE B A N K O F A T L A N T A
large bank may find it less desirable t o compete
overtly for market share than t o simply take
advantage of its customer base and maximize
profits subject t o some m i n i m u m market share
constraint. O n the other hand, the smaller
bank finds it advantageous t o expand its
customer base in order t o achieve sufficient
size t o take advantage of scale economies.
Therefore, the small bank finds it advantageous
t o undertake overt c o m p e t i t i v e action t o
increase its deposit base.
To t h e e x t e n t t h a t p r o f i t m a x i m i z a t i o n
behavior and share maximization behavior are
inconsistent w e should be able t o devise an
empirical test of the hypothesis. This hypothesis
is important. If large and small banks in fact
have different objectives, and if the small bank
is most likely t o undertake overt price and
nonprice stimuli seeking t o expand its market
share, t h e n the loss of many small banks may
adversely affect the c o m p e t i t i v e performance
of banking markets. In other words, if small
banks are indeed the most likely t o stimulate
c o m p e t i t i o n w i t h i n a market, t h e n the loss of
small banks from deregulation and consolidations may weaken these financial markets'
competitive performance.
Theoretical Rationale
Thinking of a firm as something other than a
profit maximizer is by no means pathbreaking. 3
In t h e late 1950s, W. J. Baumol asserted:
" I a m prepared t o generalize f r o m these observations
a n d assert that t h e t y p i c a l oligopolist's o b j e c t i v e can
usefully be characterized, a p p r o x i m a t e l y , as sales
m a x i m i z a t i o n subject t o a m i n i m u m profit constraint.
Doubtless this premise over-specifies a rather vague
set of a t t i t u d e s b u t I b e l i e v e it is n o t t o o far f r o m t h e
truth. So long as profits are high e n o u g h t o keep
stockholders satisfied a n d c o n t r i b u t e a d e q u a t e l y t o
the financing of c o m p a n y growth, m a n a g e m e n t w i l l
b e n d its efforts t o t h e a u g m e n t a t i o n of sales revenues
rather t h a n t o f u r t h e r increase profits." 4
Baumol's generalization was based on his v i e w
of how large firms actually behaved. The
management of business firms seems t o be
obsessed w i t h sales growth. In attempts t o
impress directors, attract stockholders or simply
impress market observers, management consis3
F. M a c h l u p , " T h e o r i e s o t t h e Firm: Marginatist, Behavioral, Managerial,"
A m e r i c a n E c o n o m i c Review, M a r c h 1 9 6 7 , pp. 1-33.
• W i l l i a m J. Baumol, B u s i n e s s B e h a v i o r , V a l u e a n d G r o w t h , ( N e w York:
Macmillan, 1959), pp. 4 9 - 5 0 .
50
tently emphasized sales growth. This led Baumol
t o hypothesize that the primary objective of the
management of larger corporations is sales maximization subject t o some minimum level of
profits. This laid the foundation for a series of
empirical studies attempting to verify what came
to be known as the "sales maximization hypothesis." A number of these studies attempted to
test the phpothesis, but most found little support
for it.5 One exception, a study by Robert J.
Saunders that used a cross section of commercial
banks from the Fourth Federal Reserve District,
reported:
"This observed profit-depressing, high growth-oriented
behavior of some commercial banks w o u l d be expected
in a s i t u a t i o n w h e r e the sales m a x i m i z a t i o n hypothesis
is t r u e . . ." 6
M o r e importantly, however, Saunders f o u n d
that some commercial banks seemed t o display
profit maximizing behavior while others pursued
policies consistent w i t h sales maximization.
Issues concerning the proper behaviorial model
for t h e firm clearly are far from settled as a
n u m b e r of recent articles on expense preference behavior reveal. 7
The predictability of the relationship between
a market's structure ( n u m b e r and size distribut i o n of firms) and its c o m p e t i t i v e performance
(i.e. level of prices, profits, and o u t p u t ) largely
depends on the objectives of firms in that
market. The structure—performance relationship in banking has proved statistically significant
but quantatively weak. In other words, t h e
level of market concentration (a structural
measure of how much of the market is controlled
by the largest'firms) matters, but only very large
changes in market concentration are associated
w i t h very small changes in price, profits or the
other performance indicators. O n e probable
reason for f i n d i n g that this relationship quantitatively weak is that all firms in a market do not
operate w i t h the same objective. Numerous
studies testing various explanations (for example, the expense preference hypothesis, or the
5
S e e f o r e x a m p l e , William C. Pardridge, " S a l e s o r Profit M a x i m i z a t i o n in
M a n a g e m e n t Capitialism," W e s t e r n E c o n o m i c J o u r n a l , Spring, 1 9 6 4 ;
M a r s h a l l Hall, " S a l e s E x a m i n a t i o n " J o u r n a l of I n d u s t r i a l E c o n o m i c s ,
April, 1 9 7 7 ; a n d Bevars D. M a b r y a n d David L. Siders, " A n E m p i r i c a l Test
of the Sales Maximization Hypothesis," S o u t h e r n E c o n o m i c J o u r n a l ,
January, 1 9 6 7 .
• R o b e r t J. S a u n d e r s , " T h e S a l e s M a x i m i z a t i o n H y p o t h e s i s a n d the
Behavior of C o m m e r c i a l Banks," Mississippi Valley J o u r n a l of Business
a n d E c o n o m i c s , Vol 6, Fall 1 9 7 0 .
7
S e e S t e p h e n A. R h o a d e s , " A S u m m a r y a n d Evaluation of S t r u c t u r e P e r f o r m a n c e S t u d i e s in B a n k i n g : A n Update," W o r k i n g Paper, Staff of
t h e B o a r d of G o v e r n o r s of t h e F e d e r a l R e s e r v e System, 1 9 8 2 .
N O V E M B E R 1982, E C O N O M I C
REVIEW
limit price hypothesis, or Hick's q u i e t life
hypothesis or the linked oligopoly hypothesis)
bear out the fact that the behaviorial element
especially of the banking firms is a complex
animal. 8 A t t e m p t i n g t o understand a c o m p l e x
relationship often entails separating the components and analyzing t h e m independently.
Since it is q u i t e probable that not all firms
operate w i t h the same objective, a basic
distinguishing characteristic should separate
firms into groups sharing the same objective.
Perhaps the simplest characteristic is t h e
relative size of firms in their respective markets.
For those markets chosen in the Sixth Federal
Reserve District, banks w i t h less than 3 percent
market shares are consistantly smaller than the
deposit size necessary t o take advantage of
scale economies. Banks w i t h more than 15
percent of the market's deposits are consistently
largerthan the m i n i m u m size necessary t o take
advantage of scale economies. Therefore, this
study attempts t o gather empirical evidence
on the possibility that relatively large banking
firms' behavior (those w i t h fifteen percent or
more of market deposit) differs significantly
from that of smaller firms (those w i t h three
percent or less of market deposits) w i t h
respect t o t h e i r p r o f i t and m a r k e t share
maximizing behavior.
Hypothesis
O u r basic hypothesis is that relatively large
banks a t t e m p t t o maximize profit subject t o
some minimal market share constraint w h i l e
smaller banks a t t e m p t t o maximize market
share subject to some minimal profit constraint.
This hypothesis asserts that, in general, large
banks are willing t o sacrifice market share t o
take advantage of pricing or nonprice policies
allowing the bank to maximize profits. Therefore,
we w o u l d expect that higher levels of market
profit would be associated with declining market
share for large banks. Conversely, small banks
are in general attempting t o acquire market
share, since increased market share equates to
increased market power. It is only after the small
" S e e for e x a m p l e , F r a n k l i n R. Edwards, " M a n a g e r i a l O b j e c t i v e s in
R e g u l a t e d I n d u s t r i e s : E x p e n s e - P r e f e r e n c e B e h a v i o r in B a n k i n g , "
J o u r n a l of Political E c o n o m y , Vol. 85, F e b r u a r y - D e c e m b e r 1 9 7 7 o r
T i m o t h y H. H a n n o n , " E x p e n s e - P r e f e r e n c e B e h a v i o r in B a n k i n g : A
R e e x a m i n a t i o n , " J o u r n a l o f Political E c o n o m y , Vol. 8 7 , FebruaryD e c e m b e r , 1 9 7 9 or J a m e s A. V e r b r u g g e a n d J o h n S. Zahera, " E x p e n s e P r e f e r e n c e B e h a v i o r in t h e S a v i n g s a n d Loan Industry," J o u r n a l of
Money, Credit and Banking, November, 1981.
Figure 1. Graphic Depiction of the Hypothesized Relationship
\
Relatively large
banks maximize
profits at the
expense of share.
Profits
\
\
\
\
\
\
\
\
\
\
% Change
Market Share Controlled
0
Relatively
small
banks
maximize
growth in the
market
share
at the
expense
of market
profits.
+
% Change
Market Share Controlled
bank has acquired some level of market power,
or relative size, that its objective would change t o
maximizing profits. Therefore, we would expect
lower levels of profit to be associated with
increasing market share for small banks.
This w o u l d be expected if small banks have
the same or higher but declining average cost
as their larger competitors. It w o u l d not be
expected only in the case w h e r e the average
cost of the larger firm is higher than that of the
smaller firm, in other words, where diseconomies
of scale are encountered. Graphically, Figure I
describes the relationship expected if the t w o
sets of banks, large and small, in fact perform as
if they were a t t e m p t i n g t o maximize profits or
market shares, respectively. Conceptually, the
relationship b e t w e e n profits and growth or
decay in market share need not be continuous,
but the general relationship described by
Figure I w o u l d need t o be f o u n d t o support the
hypothesis.
Sample
To test the hypothesis we selected banking
markets in the Sixth Federal Reserve District
that contained five or more banks in 1969. 9
The criterion of five or more banks assures the
inclusion of an ample n u m b e r o f both large and
small banks. Because of the large n u m b e r of
" T h e g e o g r a p h i c m a r k e t s used w e r e t h o s e d e f i n e d by t h e Federal
Reserve B a n k of A t l a n t a a n d a c t u a l l y u s e d in t h e analysis of h o l d i n g
e o m p a n y a c q u i s i t i o n s or bank mergers.
51
FEDERAL RESERVE BANK O F A T L A N T A
banking markets in the Sixth District containing
just t w o or three banks, inclusion of markets
w i t h less than five competitors w o u l d have
artificially w e i g h t e d t h e sample in the direction
of relatively large banks. In total, 54 markets
were selected w h i c h contained 590 banks in
1969.
Income and Call Report items were studied
for each of these 590 banks for the period
1969 through 1977. Although this period
includes a relatively severe recession, it also
includes more normal periods of the business
cycle. Overall w e believe the period is fairly
representative. Market shares and other market
related calculations i n c l u d e d new entrants in
each of the markets; however, only banks
existing in 1969 were used as observation
points. These banks were segmented according
t o relative size, and the profit performance and
share experience of each of these banks was
tracked for the nine year period.
market shares of 3 percent or less, i.e. our small
bank segment. This gives us t w o groups of banks,
one relatively large the other relatively small. The
profit or share growth objectives of banks in the
mid-range (those with more than 3 percent of
the market but less than 15) are more likely t o
differ among organizations than are the objectives
of either the banks in the large or small bank
groups. Therefore, an analysis of the relationship
between bank profits and market share growth
for banks in the large group relative to those in
the small group should provide some indication
of whether or not the t w o groups of banks
perform as if they have significantly different
objectives in conformity with the hypothesis.
The model used to gather empirical evidence
took the following form:
tr ¡J = f(Msjj, Abjj, ( D D / T D ) j j , Rjj,
( C + l / T Q j j , E Hcjj
where:
7r ¡j =
Model and Test
Given that this is an exploratory study, a direct
test of the hypothesis proved too expensive to
undertake. Statistical techniques to derive the
appropriate share and profit constraints require
tremendous amounts of computer time. 10 Therefore, as a first approximation of the hypothesized
relationship a test for differences in the actual
profit and share performance of relatively large
and relatively small banks was devised. This test
is simply intended to establish whether or not
relatively large and relatively small banks display
the hypothesized patterns w i t h respect t o their
profits and market share growth.
Since the exact point at which a bank would
opt t o maximize profits instead of market share
was of little interest in this exploratory study, we
simply split our sample into t w o segments based
on the relative size of the bank within its relevant
market. O n e segment included all banks w i t h
beginning (1969) market shares of 15 percent or
more, i.e. our large bank segment. The second
segment included all banks with beginning
' " I d e a l l y , to test t h e h y p o t h e s i s in t h e f o r m in w h i c h it is p r e s e n t e d w e
w o u l d n e e d a m o d e l in w h i c h a b a n k ' s m a r k e t s h a r e a n d its profits are
d e t e r m i n e d s i m u l t a n e o u s l y . In a d d i t i o n , d e t e r m i n a t i o n of t h e m a r k e t
share g r o w t h w o u l d r e q u i r e a profit c o n s t r a i n t a n d d e t e r m i n a t i o n of
m a r k e t p r o f i t s w o u l d require a profit constraint. M a x i m u m l i k e l i h o o d
e s t i m a t i o n may be u s e d to i d e n t i f y t h e p r o p e r profit a n d s h a r e
c o n s t r a i n t s , however, this p r o c e d u r e p r o v e d t o o e x p e n s i v e f o r t h e
purpose at hand. Therefore, g i v e n t h a t this is an e x p l o r a t o r y s t u d y , an
indirect t e s t w a s d e v i s e d in o r d e r to e x p l o r e t h e r e l e v a n c e of t h e
h y p o t h e s i s w i t h o u t t h e e l a b o r a t e d i r e c t test.
52
Profits = ( N e t Income/Total Assets of the ith
bank in the j t h market.)
Msjj = Change in the market share b e t w e e n 1969 and
1977 (Market Share 977 - Market Share 1969)
Abjj = Absolute size (Total Deposits in millions of
dollars)) of the ith bank in the jth market in
1969.
( D D / T D ) j j = Average ratio of the ith bank's d e m a n d to
total deposits from 1969 t o 1977.
Rjj = a risk measure w h i c h is the bank's average loanto-asset ratio over the period relative t o the
market's loan-to-asset ratio. 11
( C + l / T L ) j j = the proportion of commercial and industrial
loans to total loans held by the ith bank in
the jth market averaged for 9 years. 12
E = the n u m b e r of new banks entering the market
during t h e 1969 to 1977 period.
Hj = The average of the jth market's Herfindahl
concentration ratios over the 9 year period.
He = a d u m m y variable w h i c h indicates w h e t h e r or not
the ith bank is a subsidiary of a bank holding
company.
Rij
=
V
T
Ali
(f
'2 < c + ™ = *
' '
r
M
ä-/N)9
(?5r)/9
N O V E M B E R 1982, E C O N O M I C REVIEW
Table. 1 Empirical Results on Relationship Between Profits and Share Growth for Large and Small Banks
(With Bank Profits the Dependent Variable)
Classification
of B a n k S i z e
A
Intercept
Ms;;
< .03 market
share
Small Bank
.008826
-.075266
> . 1 5 market
share
Large Bank
.012025
.024150
(2-45)
< .03 or
> . 1 5 market
share
Large and
Small Subset
.010708
All Banks
.011252
x
xx
xxx
A
=
=
=
=
(1.66)
Aby
He
R2
.009440
(1-41)
x
.000001
.07270
2.9903
-.002370
(0.49)
-.004326
(0.50)
-.000017
(1.42)
x
.19560
3.3348
.001607
(2.06)
-.006579
(2.66)
.000102
.04841
2.6962
379
(0.00)
.000001
(0.63)
XX
XXX
.000848
(1.44)
x
-.007490
(3.83)
-.000521
(0.13)
-.000001
(1.11)
.04372
3.8012
590
(DD/TD)¡j
R¡j
(C+l/TUjj
.000483
(2.80)
.001872
(1.59)
.000413
(0.31)
-009956
(3.22)
xxx
-.000013
(0.61)
.000280
(0.34)
.001700
(1.25)
x
.000008
(0.38)
.001043
(1.35)
XX
XXX
.014973
(1.39)
.008887
(1.08)
-.000002
(0.09)
.001314
(1.78)
(0.88)
Cases
275
A
104
A
XXX
Significant at the .10 level.
Significant at the .05 level - one tail t
Significant at the .01 level
F significant at the .01 level for all equations.
Given the hypothesis, w e are interested in the
relationship between the relative size of a bank
and its profit and market share performance
during the period. Specifically the expected
relationship is:
Change in
Firm
Market Share
Profits
Small
>
<
Large
<
>
Therefore, w e would expect the relationship
between both small and large bank profits and
changes in their market shares t o be negative.
Small banks w o u l d show lower profits as they
gained market share and large banks w o u l d
show higher profits as they lost market share.
Since the signs of both share coefficients will not
indicate whether or not the banks actually lost
market share as profits increased (as w e w o u l d
expect case for large banks) or gained market
share at the expense of profit (as we w o u l d
expect for small banks), a scatter diagram was
used t o differentiate the t w o events.
The expected signs on the remaining independent variables were as follows: profits are
expected t o expand with absolute size of the
bank, (the larger the absolute size of the bank
the more probable is profit maximizing behavior);
profits are expected t o be positively associated
with the banks' demand t o total deposit ratio,
(this ratio proxies the bank's cost of funds;
therefore, the higher the ratio the lower the cost
of funds, thus increasing the potential for higher
profits); profits and risk are assumed t o have a
positive association, (as risk increases w e expect
higher returns); the proportion of the bank's
loans allocated to commercial and industrial
borrowers in a portfolio proxy which should be
negatively associated w i t h profits (commercial
and industrial borrowers normally obtained
preferred rates); the entry variable is expected to
be positively associated w i t h bank profits, the
higher the level of bank profits the more
attractive the market for new entrants; and, He or
the holding company dummy variable is expected
to be positively associated with bank profits
(either because of deep pocket assumptions or
potential economies associated with holding
company organizational structure). The empirical
results of estimating the model appear in Table I.
As the table indicates, the model was run three
times, once including only banks with 1969
market shares 15 percent or greater, once
including only those banks w i t h 1969 market
shares of 3 percent or less, once including banks
with either 3 percent or less of the market or 15
percent or more in 1969 and once for all
banks.
The empirical results were mixed with respect
to the hypothesis tested. The F test on all three
53
FEDERAL RESERVE BANK O F ATLANTA
equations was significant at the .01 level. Each of
the independent variables with significant (t)
tests showed the expected conclusion except in
the large bank category where both the change
in market share and holding company affiliation
variables showed signs opposite those expected.
The relationship between holding company
affiliation and profits for large banks was negative
and significant at the .10 level. This would
indicate that, at least for banks which are large
relative to their markets, holding company
affiliation is negatively associated w i t h profits.
This is an interesting finding but outside the
scope of this particular study. The magnitude of
the coefficient (.000016), however, is so small
that although it is statistically significant, it is
quantitatively very weak (a little over 1/10 of a
percent).
The major unexpected occurrence was the
relationship between profits and change in
market share in the large bank category. As
hypothesized, the relationship was expected to
be negative, indicatingthat the greater the loss in
market share the higher the profits. Instead, this
relationship proved positive for large banks and
significant at the .01 level. This surprisingly
positive relationship indicates that, within the
large bank category, the larger the loss in market
share the lower the profits. To restate, the
smaller the loss in market share or the larger the
increase in market share the higher the profits.
This relationship suggests that, at least for large
banks in our sample, profit maximization and
share maximization are not inconsistent objectives.
In order to get a visual picture of the relationship
between changes in market share and profits, w e
ran scatter diagrams for both large and small
banks. W i t h the large bank category, scatters
were run on all banks w i t h 10 percent or more of
market deposits, banks w i t h 1 5 percent or more
and banks w i t h 20 percent or more of market
deposits. The three groups all showed a significant
positive relationship between change in market
share and profits. Interestingly, as the criterion of
bank size for each group increased—from a 10
percent market share, t o 15 percent and then t o
20 percent—the R2 increased from .08 to .19 and
the (t) values increased from 7.2 to 9.5. Those
findings indicate that the relationship between
changes in market share and profits became
more predictable as the bank's market share
increased in size.
54
Most importantly, however, two-thirds of all
banks holding market shares of .10 or more in
1969 lost market share during the observation
period. Three-fourths of the banks in the other
large bank categories actually lost market share—
those w i t h market shares of .15 percent and
greater, and those with 20 percent and more. In
the large bank category, then, those banks that
gave up smaller market shares during the
observation period actually performed better in
terms of profits than those that gave up more. In
addition, larger banks that increased market
share t e n d e d to enjoy higher profits than those
showing declining market share. Therefore, it
appears from this data that share maximizing
behavior is not inconsistent w i t h profit maximization for large banks.
For relatively small banks—those holding .03
percent or less of market deposits in 1969—
there appears t o be a tradeoff between share
growth and profit growth. The hypothesized
relationship between profits and change in
market share for small banks is negative, and, as
expected, the regression analysis shows a statistically significant negative relationship between
change in market share and profits for this group.
In addition, the scatter diagram of this relationship
indicated that 82 percent of the small banks
increased market share, contrasting sharply w i t h
the 75 percent of large banks showing decreases.
The small banks' actual profit and share performance is consistent with the hypothesis that
relatively small banks tended t o emphasize
share growth, accepting relatively small profits as
they gained larger market shares during the
period. Figure 2 compares the hypothesized
relationship between profits and changes in
market shares with the empirical findings.
The empirical relationship shows that the
profit and market share performance of relatively
small banks conforms t o the hypothesis that
profits and change in market share are inversely
related. This same relationship was hypothesized
for relatively large banks, but the empirical
results show a positive relationship between the
relatively large banks' profits and change in
market share. In other words, as market share
increases, profits increase. Therefore, small
banks face a trade off between growth in market
share and growth in profits which the large banks
don't face. The large banks appear t o increase
profits by minimizing the market share loss or
gaining market share.
NOVEMBER 1982, E C O N O M I C
REVIEW
Figure 2. Hypothesis Compared to
Empirical Relationship of Large and Small
Bank Profit Versus Market Share Experience
Hypothetical
Table 2. Mean Level of Profits and Standard Deviation
of Profits for Relatively Small Banks,
Relatively Large Banks and All Banks.
Empirical Finding
-1 Standard Deviation
\
\
Large
Banks
\
\
Profits
(Return
on
Assets)
Small
Banks
Profits
(Return
on
Assets)
Large
% C h a n g e in
Market Share Controlled
Banks
Small
Banks
% C h a n g e in
Market Share Controlled
Table 2 shows the mean level of profits for
small banks, large banks, and all banks represented
in the sample as well as the standard deviation of
profits within each of these groups.
Banks with relatively large market share tend
to show higher profits than either small banks or
the average of all banks. In addition, the large
banks show less variation in profits than d o small
banks. It appears that large banks do in fact
exercise their market power which results in
slightly higher profit, approximately 7 percent
greater return on assets than small banks.
Although small banks tend to show lower profits
than their larger counterparts, small banks tend
to gain market share (82 showing positive growth
in market share) while maintaining profits just
slightly lower than the mean return on assets
associated with the large banks. The mean levels
of profits for large and small banks are not
significantly different.
One conclusion w e can draw is that small
banks appear t o be at no disadvantage in
competing with their larger counterparts. The
large banks appear to place more emphasis on
profits than do small banks, but they also
evidently attempt t o minimize share loss or gain
share in concert with their profit objectives. Thus
the fact that small banks are capable of gaining
market share given these circumstances without
giving up much of their relative profitability
indicates they can compete with their larger
counterparts.
Small Banks
Large Banks
All Banks
.0046
.0066
.0051
M e a n II + S t a n d a r d Deviation
.0103
.0110
.0105
.0160
.0154
.0159
An analysis of the three equations presented
in Table 1 indicates not only that the relationship
between profits and changes in market share is
significantly different for large and small banks
but also that the model's ability t o predict profit
is reduced substantially w h e n all banks are taken
together (i.e. equation 3). Grouping the banks by
relative share of the market increases our ability
to predict market performance. This may be
taken as another indication that the market
behavior of large and small banks is significantly
different. It also argues strongly for more research
into the behavior of banks based on their relative
market size.
In order to test the consistency of these
findings with regard to market share performance
we reorganized the variables in our model,
allowing profits t o become an independent
variable and change in market share to become
the dependent variable. Table III shows the
results of rerunning the three equations.
The results of running the three equations a
second time t o evaluate market share are
entirely consistent with the analysis of profit
equation results. For relatively small banks
profits were negatively associated w i t h change in
market share and statistically significant Relatively
large banks showed a statistically significant
positive relationship between profits and change
in market share. Relatively small banks tend to
trade profits for increased market share and
relatively large banks experience increased
profits with increased market share. In addition
the R2 for both the relatively small bank sample
and the large bank sample are higher than the R2
for all banks taken together. This w o u l d again
tend t o indicate that small and large bank
behavior is in fact different and that each group's
behavior with respect to growth in market share
is more predictable than all banks taken together.
55
FEDERAL RESERVE B A N K O F A T L A N T A
Table 3. Empirical Results on Relationship Between Profits and Share Growth for Large and Small Banks
(With Change in Market Share the Dependent Variable)
Classification
of Bank Size
A
Intercept
Profits
Abjj
Small Bank
.03 market
share or less
-.0004
-.1338
(1.66)
.0010
(4.22)
Large Bank
.15 market
share or
greater
-.0308
XX
2.4554
(2.53)
-.0000
(.08)
Significant
Significant
Significant
Significant
(C+l/TUjj
ii
.0071
(5.12)
.0020
(.46)
-.0099
(1-22)
.0050
.2156
(1.04)
at
at
at
at
the
the
the
the
.10
.05
.01
.01
E
.0002
(2.35)
R2
F
Cases
-.0000
(.17)
.149
6.7
275
-.0002
(1.57)
-233
4.2
104
-.0000
(-89)
1.06
9.8
590
He
XXX
XXX
XXX
.0042
(-37)
-.0531
(1.16)
-.0034
(2.11)
XX
-.0005
(5.48)
XXX
=
=
=
=
-.0006
(-35)
R
XXX
All Banks
x
xx
xxx
F
(DD/TD)|jj
-.0095
(2.58)
XXX
.0025
(1.00)
-.0174
(1-70)
XX
-.0004
(2.23)
XX
level
level - o n e tail t
level
level for all equations.
)
A final note of interest, the entry variable is
statistically significant in each of the three
equations. Entry, however, is positively associated
with growth in small bank market share and
negatively associated w i t h larger bank growth in
market share. This, again, indicates that small
banks compete effectively against their larger
counterparts.
Conclusion
In testing the hypothesis that large banks tend
to be profit maximizers and that small banks
tend t o be share maximizers, w e come t o the
following conclusions. First, the tests were structured as an indirect test of the hypothesis, but
the results indicate a statistically significant
difference in the profit and change in market
share relationship between large and small
banks. A statistical test of significance (Chow
test) indicates the coefficients in the equation
for large banks are significantly different from the
coefficients in the small bank equation. This is
true for both sets of equations, the set predicting
profits as well as the set predicting change in
market share. This gives further evidence that
the profit performance relative t o market share
performance is in fact different for large and
small banks.
Our major finding is that the profit and market
share performance of large banks is significantly
different from that of small banks. Small banks
56
t e n d t o experience a tradeoff between increases
in their market share and profits, increasing
market share at the expense of profits. Since the
vast majority of small banks increased market
share during the period, it appears they have a
higher desire for share growth than do the larger
banks, most of which gave up market share. O n
the other hand, our finding indicates that the
relatively large banks do not experience a trade
off between profits and growth in market share.
To the contrary, it appears that relatively large
banks may simultaneously maximize profits and
market share. Given this difference and hence
the probable difference in objectives of large
and small banks, it is not hard to understand why
the literature is full of studies that show such
weak relationships between market structure
and performance.
"Small banks tend to . . .
increase market share at the
expense of profits. . .[while]
large banks may simultaneously
maximize profits and market
share."
N O V E M B E R 1982, E C O N O M I C
REVIEW
Small banks show a higher propensity to
acquire market share. Assuming that their actual
performance represents an actual objective and
not simply a mathematical necessity, small banks
attempting to increase market share add to the
competitiveness of the marketplace. But because
large banks may undertake profit and share
maximization behavior simultaneously and
because the profit differential between large and
small banks is so small, the competitive interaction
of relatively small banks may retard the ability of
large banks to acquire market share and hence
profits. To this extent the consolidation of small
banks into larger organizations may be detrimental
to competition.
On the other hand, the fact that relatively large
organizations may simultaneously maximize
share and profits indicates that few organizations
in a market may be necessary to provide
adequate levels of competition. Along the same
line, because the differential in return on assets
to relatively large and small banks is so slight,
relatively small banks appear to be at little
competitive disadvantage in relation to large
banks. It follows that small banks may then feel
little pressure to consolidate with larger organizations to compete effectively. By simply reducing
their aggressiveness and attempting to maintain
share, they can improve their return on assets.13 [
' 3 The finding that large relatively large banks appear to simultaneously
maximize share a n d profits is consistent with either increasing returns to
scale or constant returns to scale in banking. The relatively small profits
differential b e t w e e n relatively large a n d relatively small banks w o u l d argue
strongly for constant returns in banking. This seems to be consistent with
most of the empirical work on e c o n o m i e s of scale in banking.
—David D. Whitehead
and Jan Lujytes
*The authors would like to express their thanks to Robert A
Eisenbeis, Wachovia Professor of Banking, University of
North Carolina at Chapel Hill,
for his many helpful
comments and suggestions.
REFERENCES
Ballensperger, Ernst "Alternative Approaches to the Theory of The
Banking Firm" J o u r n a l of M o n e t a r y Economics, vol. 6, no. 1 , 1 9 8 0 , pp.
1-37.
Baumal, William J. "The Theory of Expansion of the Firm." T h e A m e r i c a n
E c o n o m i c Review, vol. 52, 1962, pp. 1 0 7 8 - 1 0 8 7 .
Business Behavior, V a l u e a n d Growth, New York:
Harcourt Brace a n d World, Inc.
Beighley, Prescott H. a n d Alan S. McCall. " M a r k e t Power a n d Structure
a n d C o m m e r c i a l Bank Installment Lending." J o u r n a l of M o n e y , Credit,
and Banking, November, 1975, pp. 4 4 9 - 4 6 7 .
Benston, G e o r g e J., Gerald H a n w e c k a n d David B. Humphrey. "Scale
Economies in Banking: A Restructuring a n d Reassessment." Research
Paper, Board of Governors of the Federal Reserve System, Washington,
D.C., October, 1 9 8 0 (Revised November, 1981).
Edwards, Franklin R. a n d Arnold A. Heggestad. "Uncertainty, M a r k e t
Structure, a n d Performance: The Galbraith-Caves Hypothesis a n d
Managerial Motives in Banking." Quarterly J o u r n a l of E c o n o m i c s , vol.
87, no. 3, August, 1973, pp. 4 5 5 - 4 7 3 .
Glassman, C y n t h i a A. a n d S t e p h e n A R h o a d e a " O w n e r vs. M a n a g e r
Control Effects on Bank Performance." T h e Review of E c o n o m i c s a n d
Statistics, vol. 62, 1980, pp. 2 6 3 - 2 7 0 .
Hall, Marshall. Sales Revenue Maximization: An Empirical Examination.
Hannon, Timothy H. "Expense-Preference Behavior in Banking: A
Reexamination." J o u r n a l of Political E c o n o m y , vol. 87, no. 4 , 1 9 7 9 , pp.
891-895.
Klein, Michael A "A Theory of the B a n k i n g Firm," J o u r n a l of M o n e y ,
Credit a n d B a n k i n g , vol. 3, May, 1971, pp. 205-218.
Gale, Bradley, T. "Market S h a r e a n d Rate of Return." Review of
E c o n o m i c s a n d Statistics, N o v e m b e r 1972, pp. 412-423.
Mabry, Bevars, D. a n d David L Siders. "An Empirical Test of the Sales
Maximization Hypotheses," Southern E c o n o m i c Journal, January
1967, pp.367-377.
McCall, Alan S. a n d Manfred O. Peterson. "A Critical Level of C o m m e r c i a l
Bank Concentration." J o u r n a l of Banking a n d Finance, no. 4, 1980,
pp. 353-369.
Mullineaux, Donald J. " E c o n o m i e s of Scale a n d Organization Efficiency
in Banking: A Profit Function Approach." T h e J o u r n a l of F i n a n c e , vol.
33, no. 1, March, 1978, pp. 259-280.
Pardridge, William D. "Sales or Profit Maximization in M a n a g e m e n t
Capitalism." W e s t e r n E c o n o m i c Journal, Spring, 1964, pp. 134-141.
Rhoades, S t e p h e n A "Structure Performance Studies in Banking: A
Summary a n d Evaluation." Staff E c o n o m i c Studies No. 92, Board of
Governors of the Federal Reserve System, Washington, D.C., 1977.
Rhoades, S t e p h e n A a n d Paul Schweitzer. " F o o t h o l d Acquisitions a n d
Bank Market Structure." Staff Economic Studies No. 98, Board of
Governors of the Federal Reserve System, Washington, D C., 1978.
Saunders, Robert J. " O n the Interpretation of M o d e l s Explaining Cross
Sectional Differences A m o n g Commercial Banks." J o u r n a l of Financial
a n d Quantitative Analysis, March, 1969, pp. 25-35.
Saunders, Robert J. "The Sales Maximization Hypothesis a n d the
Behavior of C o m m e r c i a l Banks." Mississippi Valley J o u r n a l of
Business a n d Economics, vol. 6, no. 1, Fall, 1970, pp. 21-32.
Sealey, C. W., Jr. a n d J a m e s T. Lindley. "Inputs, Outputs, a n d a Theory of
Production a n d Cost at Depository Financial Institutions." T h e J o u r n a l
of Finance, vol. 32, no. 4, September, 1977, pp. 1 2 5 1 - 1 2 6 6 .
57
FEDERAL RESERVE BANK O F A T L A N T A
v
*
• '
Future
Payments
System
Technology:
Can Small
Financial
Institutions
Compete?
In payments system technology
where there are significant
economies of scale, small
financial institutions may not
necessarily suffer relative to large
institutions. Shared networks and
services promise to make
sophisticated technology available
to small institutions.
According t o many of the studies cited elsewhere in this
issue, the difference between unit operating costs at large
and small financial institutions has been insignificant in the
recent past Even though small financial institutions appeared
to have slightly lower unit costs for some payments system
services, large institutions appeared t o enjoy a slight unit
cost advantage in others. Taken together, the respective
"comparative advantages" seem to even out, making both
large and small financial institutions formidable competitors.
Do these trends remain in effect? Will the historical trend
of unit operating cost "parity" continue through the rest of
the decade? This article addresses these questions and
develops a model for the most-likely source of payments
system services offered by small financial institutions.*
* This article's focus is not on large financial institutions versus small institutions in all facets of
their operations; instead, it c o n c e n t r a t e s on payments system-related products and services
offered by large a n d small financial institutions. It explores the impact of future technology on
the traditional unit cost parity in payments systems among financial institutions of all sizes.
Generally speaking, this article refers to small financial institutions as commercial banks
with less than $1 50 million in assets, savings, a n d loan institutions with less t h e n $ 2 5 0 million
in assets, a n d credit unions. Large financial institutions generally consist of commercial banks
and savings a n d loan associations with assets in excess of the small financial institutions limits.
This article assumes that references to small banks in their payments system behavior are
also generally applicable t o the behavior of other small financial institutions. It assumes a
similar relationship for large commercial banks a n d their large counterparts in other s e g m e n t s
of the industry.
The term "technology" here refers to computer hardware a n d software, terminal devices, and
electronic c o m m u n i c a t i o n networks.
Finally, the article d o e s not attempt to c o m p a r e large a n d small financial institutions on a
point a n d counterpoint basis The emphasis is on w h e t h e r payments system technology will be
a friend or foe of small financial institutions in the 1980s.
58 N O V E M B E R 1 9 8 2 , E C O N O M I C
REVIEW
The Situation Today
Other articles in this issue suggest that small
banks enjoyed a slight edge in their payments
system unit costs during the 1970s. What kinds
of unit cost differences exist today?
Data in the Federal Reserve System's Functional
Cost Analysis (FCA) show that similar trends
continue. Recently released data for 1981, covering
614 commercial banks nationwide, show that:
Interest-bearing checking accounts were
most profitable at the smaller banks (deposits of $50 million or less), earning
them $11.22 monthly per account....
Medium-sized banks (deposits of $50
million t o $200 million) earned $8.35
each month per account...
The largest banks (more than $200 million
in deposits) earned $5.77 per month on
the accounts....
The cost of administering a N O W account
grew in all size groups over the previous
year. Smaller banks again had the lowest
administrative expenses. The accounts
cost the smallest banks $6.06 monthly
per account t o handle. The medium
banks had expenses of $6.69 per month
per account. And it cost the largest banks
$8.59 per account. 1
A review of other FCA data shows that the
lowest-cost mantle varies between large and
small financial institutions in the other payment
systems. Time and savings deposits functions
show variation too. Thus, when performance in all
of these payments and deposit generating activities
is netted out, the traditional overall parity remains
generally intact.
The historical evidence implies that, so far
anyway, payments system technology has not
given either large or small financial institutions an
insurmountable advantage in the delivery of such
products as checking accounts, savings accounts,
credit cards, and ATMs. Technological change
during the 1970s and early 1980s did not appear
to alter materially the unit cost parity between
large and small financial institutions in payments
system services.
The Status Quo Is Under Attack
During the rest of the 1980s, though, both the
payments system (as now structured) and the
'Carson, Teresa. " I n t e r e s t B e a r i n g A c c o u n t s Gain, a n d So D o e s Their
Profitability," A m e r i c a n B a n k e r ( N e w York), A u g u s t 19, 1 9 8 2 , p. 3
FEDERAL RESERVE BANK O F A T L A N T A 59
traditional unit cost parity among financial institutions are expected t o be altered in several
respects. First, the Federal Reserve System has
begun to charge for its services and will charge
even more as attempts intensify to price all Fed
float. Second, as Regulation Q is phased out,
interest expenses on all kinds of deposits should
escalate. Third, interstate banking is progressing
on a de facto basis and is likely to become a legal
activity before the decade is over. Fourth, savings
and loan associations, mutual savings banks and
credit unions are now providing such products as
checking accounts, credit cards, ATMs and debit
cards. Fifth, new players, offering payment services
of one sort or another, are entering the a r e n a Sears, Merrill Lynch, and American Express to
name a few. Sixth, backroom operations in the
paper-based payment systems are labor and
energy intensive. Costs in paper-based systems
are expected to continue spiraling.
When itemized, these trends may sound foreboding to bankers. Yet such lists usually cite
payments system technology as the salvation of
financial institutions from these threatening trends.
The general thrust of the technology argument is
that computer and communications advances
offer lower cost electronic alternatives t o the
paper-based payment systems and their gloomy
future. Even more exciting, the argument contends
that new, innovative alternatives to today's narrow,
" m e too" product lines can be designed and
marketed electronically, at lower cost and with
higher profit margins.
Explicit or implicit in many of these upbeat,
technology-inspired forecasts is a suggestion that
the future success of financial institutions will not
only require use of this technology, but also use of
large, networked payment systems. In other words,
large financial institutions will be in the best
position to reap the technological windfall and
gain a unit cost superiority.
Many forecasts of this genre imply that electronic
banking concepts are an important weapon in
efforts to improve the nation's payments system.
Such scenarios envision a necessary and desirable
shakeout period as small, inefficient financial
institutions are forced to merge or fold. The
following prediction is typical of those anticipating
much greater concentration in the industry:
The financial services industry of the
future is unlikely to consist of the same
familiar types of institutions that we know
today. It is not ordained that all or most
commercial banks, savings and loans,
mutual savings banks, credit unions, insurance companies, investment bankers
and others of the old forms of financial
institutions will survive. It is more likely
that many of them will not. 2
According t o the shakeout theory, only large
organizations have the capital and technical
expertise t o support large, complex electronic
networks. One disagreement among proponents
of this theory is the rate at which the transition
will occur. In any case, the projected result for
small financial institutions is an inevitable d e a t h fast as with an electric chair or slow as with a
Chinese water torture.
Such forecasts seem logical, tidy, neat and
clean. But another scenario, just as plausible, is
2
Kaufman, George, Larry M o t e a n d Harvey Rosenblum, "Product Lines
in Geographic M a r k e t s " Bankers Monthly Magazine. Volume 9 4
(May 15,1982), p.22. This article, as do others that it is representative of
d o e s not suggest that all small financial institutions are expected to
survive. By contrast, there is another school of thought, which the
divisibility theory supports, that believes that a very large number of
small financial institutions will survive—if they elect to d o so a n d are
well managed.
3
A review of the history of the retail grocery industry provides another
example of the divisibiity theory.
In t h e early years of this century, separate retail outlets typically sold
separate lines of groceries, e.g., meat markets sold meat, dry g o o d s grocers
sold canned/packaged food products, and produce markets sold vegetables
a n d fruits. Many of t h e s e outlets w e r e proprietorships a n d often the o w n e r
lived on premise.
T h e n in the 1 9 3 0 s w h e n the supermarket chain c o n c e p t s began evolving,
many industry forecasters predicted a shakeout of all proprietorships and
specialized s t o r e s The demise was e x p e c t e d to occur b e c a u s e small
retailers w e r e not e x p e c t e d to achieve the economies of scale available to
the supermarket chains with their centralized buying, warehousing a n d
distribution systems.
60
emerging to challenge the shakeout theory. The
concepts embodied in the alternative theory are
not new or unique. They have been evident in
many other industries. 3 The alternative is based
on the ease with which electronic products can
be produced in large quantities for several smaller
customers on a pooled or shared basis.
The divisibility theory, as it will be called here,
suggests that the foreseeable technological trends
are not the private preserve of an elite large few.
Instead, the divisibility features of the new technology could offer even more unit cost competition
between all sizes of financial institutions. More
importantly, the new technology could lead to
greater service differentiation and market segmentation than is now possible.
Likely Technological and
Unit Cost Trends During the 1980s
To visualize fully the impact of payments
system technology on financial institutions during
the rest of this decade, let's review some of the
general technological and cost trends expected
during the 1980s. The review provides a preface
for a more specific discussion of how technology
can impact the payments system services of
small financial institutions.
Inexpensive, powerful, computer hardware.
Computing power will be less expensive and
more accessible to households, small businesses,
and small financial institutions. Whether we look
at trends in the price-performance of large mainframe computers, minicomputers, or microcomputers, the cost of computing per calculation
is declining. This article, for example, is being
written with a microcomputer and word-processing
These forecasts ignored the easy divisibility of these centralized functions
into lots usable by several smaller retailers on a cooperative basis.
Wholesalers a n d cooperatives w e r e established to support i n d e p e n d e n t
supermarkets as well as corner stores or " m o m a n d pop" operativon. The
divisibility theory enabled "independents" to achieve chain store economies of
scale without the massive capital investment of a chain. The pooled
resources of all t h e wholesaler's users/cooperatives's m e m b e r s were sufficient to c o m p e t e with the large chain's economies of scale.
Granted the era d i d see the decline of the corner store concept in most
areas of the country. Ironically another mutation, in the 1 9 6 0 s and 1970s,
revived the corner store concept in a slightly different format and in a chain
structure. The m u t a t i o n is t h e convenience store w h e r e premium prices are
c h a r g e d for access to many supermarket items at locations or during hours
w h e n easy access to a supermarket is not possible.
Today, the retail grocery industry is a mixture of chain supermarkets,
chain convenience stores, independent s u p e r m a r k e t s independent convenience stores, a n d specialty outlets such as meat martkets and produce
m a r k e t s Their c o e x i s t e n c e demonstrates how an easily divisible product,
food, can be provided by organizations with many different organizational
structures, with either similar shelf prices or with extra convenience at a
premium price.
N O V E M B E R 1982, E C O N O M I C REVIEW
"The divisibility theory . . .
suggests that the foreseeable
technological trends are not
the preserve of an elite
few."
package that together cost less than $2,500. The
memory capacity of this microcomputer equals
the combined memory capacity of the IBM 1401
computers in four check reader-sorters, costing
thousands of dollars per year in the early 1970s,
at the Federal Reserve Bank of Atlanta.
Price-performance improvements are being
accompanied by miniaturization. The four readersorters of 1970 required a large room w i t h
special electrical wiring, humidity control and
temperature control. Today, memories of comparable size and power are available in desk-top
and smaller computers requiring none of the
special environmental support of earlier years.
These trends during the 1980s should produce
an exponential growth in the sales of cheap
memory and data storage devices. As a result,
computing power will represent an exception t o
the resource scarcity now being faced with
energy, strategic minerals, and even water. The
surfeit of computing power will provide electronic
payments with a significant price-performance
advantage over more-labor intensive payment
systems.
Inexpensive, user-friendly, computer programs.
Canned, easy-to-use software for general management, as well as for payments products and
services, will be readily available at reasonable
prices. Much current literature on bank operations
points out that programming costs are escalating
rapidly and possibly threatening the economies
that arise from automation and electronic payments.
These concerns are based on a traditional
reliance on the in-house development of software.
The rationale for in-house software development
has been that a particular financial institution is
unique and cannot possibly use software written
for another financial institution. Unfortunately
for those a d h e r i n g t o t h e in-house philosophy,
some small financial institutions are living proof
that several organizations can use the same
software and even share a large computer system.
Instead of owning the entire rock, so t o speak,
small financial institutions are finding ways to
o w n just the pieces of a larger rock that they
need in their organization.
Thus the idea that software development costs
are rising and will continue t o rise needs to be
tempered with the realization that an individual
financial institution may actually reduce software
expenses during the 1980s by moving from
proprietary, in-house software t o canned or shared
software concepts.
Inexpensive electronic communications. Advances in communications technology will lead
to less expensive movement of information between locations. As energy and other air or
surface transportation costs continue to rise,
electronic transmission of information will become
a greater bargain.
Wide-scale networking. Intelligent termials,
costing under $200 a unit, should facilitate electronic access of households and small businesses
t o a w i d e array of products and services. Such
terminals, linked t o inexpensive computer hardware, user-friendly software, and inexpensive
electronic communications networks, will create
an electronic network with inestimable impact.
Among the products and services readily adaptable
t o such a network are those often referred to as
" h o m e banking" services.
New concepts of "branch" banking. The cost
advantages of electronic banking will lead to the
demise of extensive networks of brick-and-mortar,
full-service banking facilities. Many facilities will
be replaced with a wider distribution of ATMs,
home terminals, and point-of-sale (POS) systems.
More sophisticated households, workers, and
small businesses. Over time, the nation's population is being exposed t o a more electronic
world. Today's children, are growing up in a more
computerized world. The work force and household bases of 1990 will be more receptive t o
price-competitive electronic alternatives for existing services, in general, and payments services in
particular.
Tomorrow's small businessman and consumer
will be more knowledgeable and sophisticated
in selecting and using credit, payment, and
investment vehicles. Idle, non-earning balances
left with financial institutions will continue their
movement into easily accessible accounts/investment vehicles. Widespread use of such vehicles
61
FEDERAL RESERVE B A N K O F A T L A N T A
should virtually eliminate demand deposits as a
low-cost source of funds for financial institutions.
Accordingly, financial institutions can be expected
to rely less on spread income and more on fee
income.
Finally, the trend throughout American industry
and trade will continue to be away from blue
collar jobs toward technical and white collar
occupations. In the financial industry, the trend
translates to less reliance on clerical work forces
and more emphasis on technically skilled professional staffs that are comfortable working with
a more computerized environment.
These technological trends will drastically
change the unit cost structure for financial institutions. Donald C. Long, a finance industry consultant with IBM Corporation, recently summarized
the anticipated impact of these technological
trends on the unit cost of several payments
system products. The following unit cost trends
are excerpted from his recent article in the
journal of Bank Retailing:
Branch Automation. In the traditional
office, an average transaction accepted
by a teller over the counter without online capability at the teller station cost61
cents in 1981. At a conservative 6 percent
c o m p o u n d rate of growth, the cost will
be 82 cents in 1986. Providing full function
on-line capability at the teller w i n d o w
could reduce that cost by approximately
21 percent to 48 cents....
Automated Teller Machines (ATMs).
While the figure is not directly comparable
to the above because of differences in
transaction mix, the cost per transaction
of an ATM doing 6,000 transactions per
month exclusive of inquiries is approximately 28 cents . . . .A major additional
consideration is that the very high component of technology involved in this
service delivery mechanism can significantly
reduce the rate of cost growth. Based on
this , I estimate that the same volume
and transaction mix on the ATM in 1986
will average 30 cents per transaction —
Point-of-Sale. At the merchant pointof-sale, the current cost of a check accepted
for goods or services is approximately 39
cents of merchant cost (57 cents general
merchandise retailerand 33 cents supermarket skewed to reflect the majority of
such checks in supermarkets) and 9
cents net bank cost (13 cents handling
62
and processing less 4 cents deposit charges
per item). This POS financial transaction
cost could be reduced to about 31 cents
(27 cents merchant cost and net 4 cents
bank cost) through the use of an on-line
debit card system providing both electronic authorization and data capture....
The Automated Clearinghouse....A recent
study sponsored by the Bank Administration Institute estimated the cost to
the bank of an EFT deposit at 7 cents
versus 24 cents for an over-the-counter
teller deposit and 59 cents for a bank-bymail d e p o s i t Home Banking....The net cost t o the
payor, biller, and bank of a payment
made by mail exceeds 65 cents. Providing
a " M o d e l T" capability, such as telephone
bill payment, can reduce that net cost to
less than 30 cents. 4
Clearly, payments system technology is positioned to play a strong role in the unit costs of
financial services and products as the decade
unfolds. Yet as formidable as these technological
trends and the unit cost projections may seem,
they still skirt the original question: What does
technology hold in store for unit costs at small
financial institutions?
Impact of Payments Technology
On Small Financial Institutions'
Unit Costs
Small financial institutions probably will not
generate sufficient volumes in electronic payment systems to develop proprietary, completely
in-house hardware, software, and communications
functions. But, just as obviously, the divisibility
theory permits shared efforts that can achieve,
collectively, the break-even volumes to be pricecompetitive with larger financial institutions. 5 j
Let's explore some of the implications of the
divisibility theory further.
First, regulators have tended to require small
banks to maintain higher capital ratios than large
banks. One often-stated reason is that small
" L o n g , D o n a l d G. "The B u s i n e s s Case for E l e c t r o n i c Banking," J o u r n a l of
Retail B a n k i n g , V o l u m e 4 (June 1982), pp. 19-20.
5
P l e a s e s e e A p p e n d i x A, T r a n s a c t i o n V o l u m e s a n d Unit Costs, f o r a more
t h o r o u g h d e s c r i p t i o n of t h e c o n c e p t s involved in e c o n o m i e s of scale for
an e l e c t r o n i c p a y m e n t p r o d u c t / s e r v i c e a n d h o w t h e divisibility theory
makes t h e s e e c o n o m i e s available to small f i n a n c i a l institutions.
N O V E M B E R 1982, E C O N O M I C
REVIEW
)
)
Table 1. Primary Source of Computer Processing
Percent of banks by asset size in millions of dollars
Processing source
Under$100
1974
On-premise
operations
Holding co.
arrangement
Correspondent
bank
Joint venture
Facilities
management
Servicing by
non-bank
Other
1977
$100-$500
$500 and above
1980
1974
1977
1980
1974
1977
1980
15%
24%
62%
58%
45%
77%
82%
75%
10
12
12
12
17
19
17
13
18
58
5
52
4
41
2
7
6
7
5
11
4
1
0
0
1
1
1
8
5
6
10
6
9
5
3
4
8
0
10
0
13
2
3
0
9
0
10
2
0
0
1
0
0
1
9%
Source: " O p e r a t i o n s / A u t o m a t i o n Scoresheet: c o m p a r e your bank with its peers," ABA Banking Journal, vol. 74 (Feb. 1982), p. 98.
financial institutions experience more risk because
of their size. However, one risk not usually
discussed is the relative automation investment
of large versus small financial institutions.
Table 1 shows the primary sources of computer
processing for small, medium and large banks as
determined from responses to the American
Bankers Association's Operations and Automation
Surveys in 1974, 1977 and 1980. Large banks
typically use in-house equipment and much inhouse software. Small banks rely much more
frequently on third-party sources. Conversations
with vendor representatives indicate that, with
few exceptions, small banks use canned software
even if they have in-house processing capability.
Exhibit 1 (chart and table) shows the much
larger percentage increase in expenditures for
hardware and software that large banks anticipate
in comparision w i t h small banks. At a time when
banks are experiencing new competitive pressures
and squeezed profit margins, it appears that a
significantly greater proportion of large bank
expense and investment resources will be tied
up in automation efforts. In contrast, small banks
are buying what they need, in the quantity they
need, when they need it. The latter approach
would seem to carry less risk.
FEDERAL RESERVE B A N K O F A T L A N T A
Exhibit 1 . Projected Hardware/Software Expenditures
per Bank - 1982
%
1 0 0 F
|
| software
Computer Equipment
50 25 0l
1
1 1
Under $ 1 0 0
S100-S500
1
*
$ 5 0 0 a n d above
Asset Size (millions of dollars)
Average Hardware/Software Expenditures per Bank
Asset Size (millions of dollars)
Under$100 $100-$500
$ 5 0 0 and
Above
C o m p u t e r Equipment
1980-actual
1981-budgeted
1982-anticipated
Software
1980-actual
1981-budgeted
1982-anticipated
($000s)
39
48
50
($000s)
198
222
242
($000s)
1.978
2,229
2,482
11
11
13
24
33
36
180
258
298
Source: Operations/Automation Scoresheet: C o m p a r e your bank with
its peers," ABA Banking Journal, Vol. 74 (Feb. 1 982), p. 96.
63
Why? A large bank is likely t o be heavily
committed and heavily invested in a software/hardware system that becomes prematurely obsolete
from the rapid innovation spawned by a highly
competitive marketplace. As a result, it will feel
management pressure either to continue offering
an obsolete product or service until the initial
investment has been recouped or t o drop the
incompletely depreciated product taking a heavy
loss on the initial investment. O n the other hand,
a small bank, using third-party suppliers, can
"A large bank is likely to be
heavily committed and heavily
invested in a software/hardware
system that becomes
prematurely obsolete. . .
change products or services as the market dictates
with much less internal financial impact. Divisibility, in a sense, decreases small bank automation
risk and increases small bank ability t o respond
to a rapidly changing marketplace.
Second, there are several indications that the
economies of scale in payment systems now
require volumes larger than are achievable even
at large financial institutions. For example, during
the past year several large financial institutions
have turned their Visa and/or Mastercard backroom operations over to a third party. Almarin
Phillips, Professor of Economics, Law and Public
Policy at the University of Pennsylvania, recently
predicted:
Economies of scale in funds management, distribution, and in the electronic
and mechanical aspects of clearing mean
that many institutions will be unable
independently to enter new markets
with new products, or indeed, competitively t o maintain their old services in
t h e i r o l d markets....In many respects, the
sharing of product offerings, with compatible hardware and software and general
customer recognition is highly procompetitive. It keeps in the marketplace
numbers of firms that would otherwise
disappear; it also makes entry easier if
64
procompetitive, non-exclusionary participations are allowed. 6
Perhaps it is the large financial institutions that
will become more like their small brethren with
respect to automation resources. Perhaps it is the
small institution's approach to harnessing automation resources that kept its unit costs so
competitive during the last decade. If so, the
small financial institution is really the automation
model for the 1980s, not the large financial
institution. If so, the divisibility theory actually
has a broader application than once visualized.
Third, networking opens up markets for smaller
financial institutions that were not profitably
serviceable in the traditional payments system
environment. William S. Anderson, chairman of
NCR Corporation, observes that:
A score of regional EFT networks in the
United States—each capable of providing
retail banking services over a broad geographic area—have now been organized.
It is only a matter of time until full-scale
national networks of this type, as well as
international networks will be in operation.
W h e n that occurs, any bank regardless
of location or size will at least theoretically
have the entire world as its market. 7
I n this respect, technology opens new doors of
opportunity for small financial institutions. Surely
it would be naive to believe that small institutions
can provide mass-market products nationally or
internationally. But it does not seem naive at all
to think that small financial institutions could use
this technological windfall in certain well-defined
market segments.
A good example of how new technology can
be accessed by large and small institutions is the
sweep and invest feature now being marketed
by several large and small institutions in conjunction with their checking accounts for large
balance customers. The size of the financial
institution does not appear to be a deterrent to
offeringthis feature. In fact, the sweep and invest
feature offered by many large and small institutions
is being obtained from the same third-party
source.
Fourth, the literature in support of the shakeout
theory seems to ignore a major question: Where
•Phillips, Alamarin. " F i n a n c i a l I n s t i t u t i o n s in a R e v o l u t i o n a r y Era,"
J o u r n a l of C r e d i t U n i o n M a n a g e m e n t a n d E c o n o m i c s , V o l u m e 2
(Spring 1982), p. 17.
' A n d e r s o n , William S. " E l e c t r o n i c F u n d s T r a n s f e r is R e a c h i n g the Pointof-Sale," A m e r i c a n B a n k e r ( N e w York), J u l y 2 8 , 1982, p. 58.
N O V E M B E R 1982, E C O N O M I C
REVIEW
will large financial institutions obtain the financial
wherewithal to go on a merger binge? Raoul D.
Edwards, senior editor, United States Banker,
suggests that a source is not available. Therefore,
he observes:
What has happened is a new and less
certain economic pattern, marked increasingly by shrinking earnings margins,
escalating labor costs, increasing pressures
on the bottom line—and a consequent
reluctance to make the kind of massive
commitment implicit in major acquisitions.
Some deals will still get made; the joining
of a good sized pair of banks as equals,
where no dilution of value occurs, for
example. But no one in today's environment wants to go out and buy up a
bunch of smaller institutions at bookand-a-half o r t w o - t i m e book, especially if
their o w n stock is selling under book. 8
According to Edwards, a major shakeout of
small financial institutions is unlikely. What is
likely is that technology will be the tool with
which all financial institutions will attempt to
offer products and services equal to or better
than those in the past, but at a lower price and,
hopefully, a better profit margin.
The same article that presented Edwards' scenario
touched on a point that bears amplification here
as a potential advantage for small financial institutions in the competition of the 1980s:
This (trend) means that the vendor of
products will increasingly find his market
opening up at the bottom. Moreover,
the range of services he can sell will
broaden....
The vendor who recognizes this and
prepares for the new market is going to
find it large and growing; the banker
who understands this will find his options
will be far greater, far more useful, than
ever before. 9
If vendors behave in this manner, small financial institutions will find more, not fewer, potential
sources of supply for their hardware, software,
technical, product, and service support in the
1980s than they can find now. If we assume that
more vendors mean more price competition,
"Edwards, R a o u l D. " T h e V e n d o r a n d C h a n g i n g Worlds," U n i t e d S t a t e s
Banker, V o l u m e 9 3 ( M a y 1982), p. 6 8
9
lbid„ pp. 6 8 a n d 71.
then small financial institutions could find more
of a "buyer's market" when shopping for suppliers
than will large financial institutions deeply engrossed in more complex, longer lead time efforts
to develop proprietary products and services. If
so, intense price-performance competition among
vendors will help cap potential cost increases for
small institutions. If so, the divisibility theory
provides them yet another benefit.
Fifth, m i n i c o m p u t e r s — a n d i>ow m i c r o c o m puters—constitute new technological weapons
for small businesses and small financial institutions.
Their full benefit has not been tapped yet by
small institutions. Admittedly, their impact transcends the payments system functions of financial
institutions.
Until the advent of microcomputers, only large
businesses and financial institutions could afford
automated planning and control. Robert H. Long,
president of Long, Inc., and editor of Microbanker, recently wrote in The Southern Banker
that:
The microcomputer is one of the first
pieces of technology that places a potent
competitive weapon in the hands of
community bankers—a piece of technology that can help them competitively
serve the more profitable markets and
reposition themselves for success in a
deregulated environment. Large banks
will use them the same way, but the
effect will not be as dramatic. 10
Stated another way, large financial institutions
achieved the major planning and control software
on their large computer systems during the last
decade. Thus, for large banks, microcomputers
will esentially serve as "fine tuning" devices. But
microcomputers provide the first reasonable
method for small financial institutions to achieve
the management and operations improvement
economies available from scientific planningand
control processes. The " q u a n t u m leap," so to
speak, could help small financial institutions
improve their efforts to control expenses and to
make better product/service decisions.
In the process, the comparative advantages of
sophisticated management processes at large
financial institutions will trickle down to small
' " L o n g , R o b e r t H. " W e l c o m e M i c r o T e c h n o l o g y , " T h e S o u t h e r n B a n k e r ,
V o l u m e 1 5 8 (July 1982), p. 26.
65
FEDERAL RESERVE B A N K O F A T L A N T A
"Small financial institutions
could even enjoy a unit cost
advantage over large
institutions during the 1980s."
institutions. As a result, large financial institutions
would lose one of their significant comparative
advantages in unit cost control. The ability of
small financial institutions t o compete would be
enhanced as this aspect of the divisibility theory
materializes.
The small financial institution's approach is also
more flexible and more capital conservative, no
small considerations in the volatile, unpredictable
marketplace of the 1980s.
On the basis of the qualitative information we ?
have reviewed, it appears that unit cost parity is
possible for small financial institutions in the >
1980s. More significantly, evidence suggests that ,
small financial institutions could even enjoy a
unit cost advantage over large institutions during
the 1980s.
If the number of small financial institutions
contracts during the 1980s, the contraction should
not be caused by a lack of state-of-the-art tech- s
nology at competitive prices for small institutions. !
Other causes will need to be sought if such a
contraction occurs.
»
Will Unit Cost Parity Be Sustained
in the 1980s?
Unfortunately, our research uncovered little
quantitative data that address the question.
M u c h qualitative information was found t o structure a logical argument for or against continued
unit cost parity. Technology, as represented in
the divisibility theory, appears to provide small
financial institutions with an enhanced ability t o
compete. The preceding discussion suggests
that technology in the 1980s will trickle down t o
small financial institutions bringing many of the
beneficial management control processes and
systems once the province of large financial
institutions w i t h large computer installations.
The divisibility theory also suggests that the
sourcing model for financial institutions during
the 1980s will not be the in-house proprietary
route so often favored by large financial institutions
during the 1970s. Instead, the most cost-effective
alternative appears to be the third-party, shared
systems concepts practiced so effectively by
small financial institutions during these years.
The Bottom Line
Future payments system technology appears n
unlikely t o prevent small financial institutions
from competing effectively during the 1980s. In
fact there are several indications that the benefits
of the divisibility theory are so attractive that }
small institution sourcing arrangements will become 1
the norm with many large financial institutions as
well. The available quantitative evidence, albeit '
sparse, indicates that future payments system
technology should not hinder the competitiveness of small institutions.
But any elation over this conclusion needs
strong qualification. Technology will not save a *
financial institution—large or small—that is not •
well managed. Harnessing newtechnology is just $
one of the many responsibilities that management must oversee. Payments system technology
is merely a tool by which an organization can
achieve results in its payments activities. Without
sound management, technological advances will
not achieve the cost benefits potentially available
l
t o all financial institutions.^
—Paul F. Metzker
66
N O V E M B E R 1982, E C O N O M I C REVIEW
APPENDIX A
TRANSACTION VOLUMES AND UNIT COSTS
The following discussion is excerpted from an article
by David A Walker, associate professor, Georgetown
University, titled "Electronic Funds Transfer Issues
and Experience: What Credit Unions Should Consider,"
and published in the Journal of Credit Union Management and Economics, Volume 2 (Spring 1982),
pp. 5-6.
Besides the absolute costs of developing EFT
systems, the per unit costs are a major concern.
The average cost per transaction (total costs
divided by total transactions) over the long run
is used to judge whether or not there are
economies of scale associated with an economic
activity. If average costs decline as output (transactions) increase, economies of scale exist and
the marginal cost per unit (additional cost for an
additional transaction) is below the average
cost in this transaction range.
Two economic approaches have been applied
to developing cost models forfinancial services.
One approach assumes that average costs
decline, or remain constant or increase throughout the relevant output range; and curve is
selected, from among ones shaped like AA', BB',
or CC', respectively, in Figure 1. The relevant
marginal cost relationships for these three cases
are aa', bb', or cc', respectively. The second,
broader approach is to assume that average
costs decline at low output levels (0 to Q*) and
then begin to rise beyond some higher output
level (Q); in this approach, instead of selecting
one of the three possibilities from Figure 1, all
three are presumed to represent parts of the
relationship as shown in Figure 2.
The empirical evidence on the average and
marginal costs per EFT transaction is very
meager.... It appears that average costs per
transactions decline as cash dispenser and
automated teller transactions increase (as shown
in Figure 2). Lower average costs are expected
to be observed until approximately 45,000 transactions per month (Q* in Figure 2) occur at a
particular retail terminal.
The preceding discussion shows how economies of
scale can be measured in an EFT system. Walker's
example pertains to a single cash dispenser or ATM.
The same basic rationale applies to a payment product,
overall, offered by a financial institution. More importantly, using Figure 2 in Walker's discussion, it is
possible to show how the divisibility theory benefits
small financial institutions
A small financial institution quite possibly can only
generate a volume of transactions in the range of 0 to
less than Q*. If so, the small institution is not operating
in the portion of the cost curves that allows its unit
costs to be most competitive with larger competitors.
But, if several small financial institutions use a thirdparty source, their combined transaction volume will
more than likely allow them to operate in the Q* to 0
range of the cost curves. In this range, each of the
small financial institutions will achieve unit costs that
are competitive with larger institutions.
Figure 2
Costs
Average
Marginal
Marginal
Average
Figure 1
O
O
Q*
Q
Output
Q*
Q
Output
O t o Q*
average costs may decrease as ouptut increases
(economies
ol scale);
Q* t o Q
average c o s t s m a y remain c o n s t a n t as o u t p u t
increases
(constant
returns to scale);
above Ö
average costs may increase as output increases
(diseconomies
ol scale).
67
FEDERAL RESERVE BANK O F A T L A N T A
777771
f
T f i r l
FINANCE
SEPT
1982
AUG
1982
SEPT
1981
ANN.
ANN.
%
CHG.
SEPT
1982
AUG
1982
SEPT
1981
534,675
10,649
91,577
433,178
JUL
501,678
15,865
534,363
10,519
91,963
432,781
JUN
503,964
16,753
511,245
6,713
94,014
410,260
JUL
507,767
17,135
+ 5
+ 59
- 3
+ 6
78,877
1,704
11,536
65,809
JUL
69,736
2,981
78,882
1,696
11,558
65,727
JUN
69,968
3,117
74,933
1,025
11,765
62,031
JUL
74,120
3,608
+ 5
+ 66
4,530
91
544
3,926
JUL
3,957
47
4,517
89
546
3,908
JUN
3,946
78
4,339
53
595
3,710
JUL
4,010
94
4
72
9
b
47,661
1,158
7,689
38,810
JUL
41,191
2,345
47,681
1,155
7,693
38,783
JUN
41,364
2,519
45,369
718
7,821
36,648
JUL
45,173
3,041
9,869
193
1,176
8,598
JUL
8,996
167
9,898
190
1,190
8,599
JUN
9,062
171
9,559
107
1,221
8,251
JUL
9,476
140
7,898
110
1,215
6,591
JUL
7,332
281
7,893
111
1,223
6,585
JUN
7,331
229
7,215
62
1,193
5,973
JUL
7,047
222
2,466
52
232
2,197
JUL
2,177
20
2,436
53
228
2,168
JUN
2,180
20
2,387
26
236
2,132
JUL
2,206
34
6,453
100
680
5,687
JUL
6,083
121
6,457
98
678
5,684
JUN
6,085
100
6,064
59
699
5,317
JUL
6,209
77
CHG.
$ millions
Commercial Bank Deposits
Demand
NOW
Savings
Time
Credit Union Deposits
Share D r a f t s
Savings & Time
11
1
31
0
18
30
39
27
Savings & Loans
Total Deposits
NOW
Savings
Time
11
2
33
1
17
31
24
27
Savings & Loans
Total Deposits
NOW
Savings
Time
+ 8
+ 1
+ 32
Savings & Loans
Total Deposits
NOW
Savings
Time
1,170,291 1,163,103 1,051,230
282,892
286,095
287,174
59,257
58,171
45,362
149,974
150,116
150,193
704,138 695,861
594,949
48,930
49,479
37,581
3,153
3,324
2,268
41,962
42,093
33,090
Commercial Bank Deposits
Demand
NOW
Savings
Time
Credit Union Deposits
Share D r a f t s
Savings & Time
124,831
32,456
7,649
14,656
72,434
4,617
302
3,896
124,861
33,180
7,536
14,673
72,160
4,634
330
3,880
112,286
33,025
5,746
14,762
61,659
3,534
244
3,061
Commercial Bank Deposits
13,886
3,300
672
1,557
8,767
837
59
677
13,953
3,439
653
1,557
8,715
815
64
654
12,903
3,279
509
1,564
7,844
551
48
494
40,620
11,298
3,313
6,176
20,349
2,083
165
1,640
40,642
11,605
3,268
6,180
20,293
2,116
183
1,647
37,034
11,875
2,504
6,332
17,142
1,602
139
1,253
+ 10
+
+
+
+
5
32
2
19
30
19
31
17,375
5,772
1,101
1,637
9,656
855
29
775
17,400
5,911
1,089
1,635
9,623
853
32
773
15,150
5,757
835
1,584
7,912
689
19
659
+
+
+
+
+
+
+
+
15
0
32
3
22
24
53
18
Savings & Loans
Total Deposits
NOW
Savings
Time
22,859
5,758
1,071
2,428
13,989
123
9
116
22,758
5,876
1,036
2,448
13,888
126
10
116
20,299
5,855
776
2,395
11,754
95
6
88
+ 13
+
+
+
+
+
+
Savings & Loans
Total Deposits
NOW
Savings
Time
10,375
2,296
555
736
6,999
N.A.
N.A.
N.A.
10,372
2,205
571
733
6,993
N.A.
N.A.
N.A.
9,330
2,239
426
733
6,142
N.A.
N.A.
N.A.
+ 11
+ 3
+ 30
+ 0
+ 14
19,716
4,032
937
2,122
12,674
719
40
19,736
4,144
919
2,120
12,648
724
41
690
17,570
4,020
696
2,154
10,865
597
32
567
+ 12
+ 0
+ 35
NOW
Commercial Bank Deposits
NOW
Credit Union Deposits
Savings & Time
GEORGIA
Commercial Bank Deposits
NOW
Credit Union Deposits
Savings & Time
I.OTTURI ANA
Commercial Bank Deposits
NOW
Credit Union Deposits
Share D r a f t s
Savings & Time
Commercial Bank Deposits
NOW
Credit Union Deposits
TENNESSEE
Commercial Bank Deposits
NOW
Credit Union Deposits
Share D r a f t s
+
+
+
+
+
+
Mortgages Outstanding
Mortgage Commitments
-
+
+
+
+
-
+
-
-
0
12
52
23
37
2
38
1
19
29
50
32
Mortgages Outstanding
Mortgage Commitments
Mortgages Outstanding
Mortgage Commitments
Savings ic Loans
Total Deposits
NOW
Savings
Time
Mortgages Outstanding
Mortgage Commitments
Mortgages Outstanding
Mortgage C o m m i t m e n t s
Mortgages Outstanding
Mortgage Commitments
Savings & Loans
Total Deposits
NOW
Savings
Time
Mortgages Outstanding
Mortgage Commitments
-
+
+
+
+
1
17
20
25
21
Savings k Loans
Total Deposits
NOW
Savings
Time
Mortgages Outstanding
Mortgage Commitments
-
1
7
_
-
2
+
6
-
6
I
- 17
-
1
50
-
-
i>
+ 61
-
+
-
2
6
9
23
3
+ 8U
4
4
-
-
b
19
y
+ TI
+ 2
+ 10
4
+
ri
I*
)
3
+100
2
3
-
-
1
41
6
+ 69
+
3
V
-
2
-
+ bV
Notes:
All deposit data are e x t r a c t e d from the Federal Reserve Report of Transaction Accounts, other Deposits and Vault Cash (FR2900),
\
and are reported for t h e average of the week ending the 1st Wednesday of the month. This data, reported by institutions with
r ",
over $15 million in deposits as of December 31, 1979, represents 95% of deposits in the six s t a t e area. The major differences between f
this report and the "call report" are size, the t r e a t m e n t of interbank deposits, and t h e t r e a t m e n t of f l o a t . The data generated from ~ j
the Report of Transaction Accounts is for banks over $15 million in deposits as of December 31, 1979. The total deposit data generate^
f r o m t h e Report of Transaction Accounts eliminates interbank deposits by reporting the net of deposits "due to" and "due f r o m " other
.
depository institutions. The Report of Transaction Accounts s u b t r a c t s cash in process of collection from demand deposits, while the calif
report does not. Savings and loan mortgage data a r e f r o m the Federal Home Loan Bank Board Selected Balance Sheet Data. The
Southeast data represent the t o t a l of the six s t a t e s . Subcategories were chosen on a selective basis and do not add to t o t a l .
N.A. = fewer than four institutions reporting.
FRASER
Digitized for
http://fraser.stlouisfed.org/
68
Federal Reserve Bank of St. Louis
FEDERAL RESERVE BANK O F A T L A N T A
EMPLOYMENT
ANN.
%
CHG.
AUG
1982
JUL
1982
AUG
1981
Civilian Labor Force - thous.
Total Employed - thous.
Total Unemployed - thous.
Unemployment R a t e - % SA
Insured Unemployment - thous.
Insured Unempl. R a t e - %
Mfg. Avg. Wkly. Hours
Mfg. Avg. Wkly. Earn. - $
111,887
101,177
10,710
9.8
112,526
99,732
11,036
9.8
110,099
102,152
7,947
7.3
39.0
332
39.0
333
39.9
320
Civilian Labor Force - thous.
Total Employed - thous.
Total Unemployed - thous.
Unemployment R a t e - % SA
Insured Unemployment - thous.
Insured Unempl. Rate - %
Mfg. Avg. Wkly. Hours
Mfg. Avg. Wkly. Earn. - $
AL
Civilian Labor Force - thous.
Total Employed - thous.
Total Unemployed - thous.
Unemployment R a t e - % SA
Insured Unemployment - thous.
Insured Unempl. Rate - %
Mfg. Avg. Wkly. Hours
Mfg. Avg. Wkly. Earn. - $
14,329
12,936
1,392
9.7
14,329
12,902
1,428
9.4
13,901
12,844
1,056
7.6
39.1
288
38.8
285
40.4
278
- 3
+ 4
1,690
1,450
240
14.1
1,704
1,454
250
13.6
1,658
1,483
175
10.5
+ 2
39.3
284
38.8
40.1
282
282
+ 1
Civilian Labor Force - thous.
Total Employed - thous.
Total Unemployed - thous.
Unemployment R a t e - % SA
Insured Unemployment - thous.
Insured Unempl. R a t e - %
Mfg. Avg. Wkly. Hours
Mfg. Avg. Wkly. Earn. - $
4,865
4,486
379
7.7
4,854
4,489
365
7.3
4,603
4,294
308
6.4
+ 6
38.6
274
38.3
271
40.4
267
Civilian Labor Force - thous.
Total Employed - thous.
Total Unemployed - thous.
Unemployment R a t e - % SA
Insured Unemployment - thous.
Insured Unempl. Rate - %
Mfg. Avg. Wkly. Hours
Mfg. Avg. Wkly. Earn. - $
2,694
2,494
2,692
2,473
219
7.6
2,610
2,452
158
5.7
+ 3
39.2
265
38.6
262
40.4
257
- 3
+ 3
Civilian Labor Force - thous.
Total Employed - thous.
Total Unemployed - thous.
Unemployment R a t e - % SA
Insured Unemployment - thous.
Insured Unempl. Rate - %
Mfg. Avg. Wkly. Hours
Mfg. Avg. Wkly. Earn. - $
1,907
1,700
207
1,872
1,719
152
8.5
+ 2
- 1
11.0
1,901
1,685
216
11.1
39.4
374
39.6
375
41.8
358
Civilian Labor Force - thous.
Total Employed - thous.
Total Unemployed - thous.
Unemployment R a t e - % SA
Insured Unemployment - thous.
Insured Unempl. R a t e - %
Mfg. Avg. Wkly. Hours
Mfg. Avg. Wkly. Earn. - $
1,052
920
132
12.7
1,064
933
131
11.2
1,048
963
85
8.2
+ 0
39.0
251
38.3
244
39.5
237
- 1
+ 6
Civilian Labor Force - thous.
Total Employed - thous.
Total Unemployed - thous.
Unemployment R a t e - % SA
Insured Unemployment - thous.
Insured Unempl. Rate - %
Mfg. Avg. Wkly. Hours
Mfg. Avg. Wkly. Earn. - $
2,120
2,111
1,933
178
8.4
+ 0
- 2
234
11.4
2,115
1,868
247
11.2
39.3
283
39.2
278
39.9
269
nyär
200
7.2
+ 2
- 1
+35
-
2
+ 4
+ 3
+
1
+32
-
2
+37
-
2
+ 4
+23
+ 3
+ 2
+27
ANN.
%
AUG
1981
JUL
1982
AUG
1982
CHG.
Nonfarm Employment- thous.
Manufacturing
Construction
Trade
Government
Services
Fin., Ins., & Real Est.
Trans. Com. <5c Pub. Util.
89,195
18,793
4,167
20,547
14,902
19,191
5,429
5,048
89,362
18,725
4,149
20,598
15,082
19,209
5,422
5,051
91,087
20,370
4,431
20,664
15,097
18,771
5,374
5,180
Nonfarm Employment- thous.
Manufacturing
Construction
Trade
Government
Services
Fin., Ins., & Real Est.
Trans. Com. & Pub. Util.
11,264
2,154
674
2,669
2,039
2,234
641
697
11,300
2,144
678
2,679
2,063
2,241
643
698
11,386
2,313
746
2,651
2,045
2,142
635
700
Nonfarm Employment- thous.
Manufacturing
Construction
Trade
Government
Services
Fin., Ins., & Real Est.
Trans. Com. & Pub. Util.
1,319
334
63
272
291
213
60
71
1,323
333
63
272
295
214
60
71
1,347
366
67
273
281
211
60
7 2
+
+
Nonfarm Employment- thous.
Manufacturing
Construction
Trade
Government
Services
Fin., Ins., & Real Est.
Trans. Com. & Pub. Util.
3,699
443
255
1,004
572
906
278
231
3,721
440
258
1,011
586
908
279
230
3,660
466
290
973
568
853
272
227
+ 1
- 5
-12
+ 3
+ 1
+6
+ 2
+ 2
Nonfarm Employment- thous.
Manufacturing
Construction
Trade
Government
Services
Fin., Ins., & Real Est.
Trans. Com. & Pub. Util.
2,150
495
100
497
424
368
117
142
2,149
492
100
497
425
368
117
143
2,180
523
104
503
421
362
115
145
- 1
- 5
- 4
- 1
+ 1
+ 2
+2
- 2
Nonfarm Employment- thous.
Manufacturing
Construction
Trade
Government
Services
Fin., Ins., & Real Est.
Trans. Com. & Pub. Util.
1,609
197
133
370
305
297
76
131
1,613
198
134
369
307
296
77
132
1,635
216
159
365
310
284
76
129
- 2
- 9
-16
+1
- 2
+ 5
0
+ 2
Nonfarm Employment- thous.
Manufacturing
Construction
Trade
Government
Services
Fin., Ins., & Real Est.
Trans. Com. & Pub. Util.
783
206
40
163
170
118
33
40
790
207
40
163
173
121
33
40
813
224
44
165
175
118
33
41
4
8
9
1
3
0
0
- 2
Nonfarm Employment- thous.
Manufacturing
Construction
Trade
Government
Services
Fin., Ins., & Real Est.
Trans. Com. <5c Pub. Util.
1,704
479
83
363
277
332
77
82
1,704
474
83
367
277
334
77
82
1,751
518
82
372
290
314
79
86
- 3
- 8
+1
- 2
- 4
+ 6
-3
- 5
-
2
-
8
-
6
- 1
- 1
+ 2
+ 1
- 3
- 1
- 7
-10
+ 1
- 0
+ 4
+1
- 0
2
9
6
0
4
1
0
- 1
A
Notes:
1,886
+36
-
6
+ 4
- 4
+55
+31
-
2
+ 5
-
All labor force d a t a are from Bureau of Labor Statistics reports supplied by s t a t e agencies.
Only the unemployment rate data are seasonally adjusted.
The Southeast data represent the t o t a l of t h e six s t a t e s .
The annual percent change calculation is based on the most recent data over prior year.
http://fraser.stlouisfed.org/
NOVEMBER 1982, E C O N O M I C REVIEW
Federal Reserve Bank of St. Louis
69
CONSTRUCTION
ANN
%
CHG
AUG
1982
JUL
1982
AUG
1981
Nonresidential Building Permits Total Nonresidential
Industrial Bldgs.
Offices
Stores
Hospitals
Schools
$ Mil.
47,160
5,498
13,392
5,458
1,694
861
48,090
5,780
13,884
5,602
1,701
849
52,478
8,394
13,464
6,693
1,425
706
10
35
1
- 18
+ 19
+ 22
Residential Building Permits
Value - $ Mil.
Residential Permits - Thous.
Single-family units
Multi-family units
T o t a l Building Permits
Value - $ Mil.
SOUTHEAST
Nonresidential Building Permits Total Nonresidential
Industrial Bldgs.
Offices
Stores
Hospitals
Schools
$ Mil.
6,275
737
1,334
1,035
212
94
6,489
763
1,378
1,054
272
95
7,359
897
1,342
1,054
260
75
15
18
1
2
- 18
+ 25
Residential Building Permits
Value - $ Mil.
Residential Permits - Thous.
Single-family units
Multi-family units
Total Building Permits
Value - $ Mil.
ALABAMA
Nonresidential Building Permits Total Nonresidential
Industrial Bldgs.
Offices
Stores
Hospitals
Schools
$ Mil.
387
78
55
66
21
8
398
78
54
67
21
8
434
46
62
71
24
5
11
7
- 13
+ 60
Residential Building P e r m i t s
Value - $ Mil.
Residential Permits - Thous.
Single-family units
Multi-family units
Total Building P e r m i t s
Value - $ Mil.
FLORIDA
Nonresidential Building Permits Total Nonresidential
Industrial Bldgs.
Offices
Stores
Hospitals
Schools
$ MiL
3,154
362
624
555
97
18
3,269
381
639
563
157
20
4,189
481
582
593
125
26
25
- 25
+ 7
6
- 22
- 31
Residential Building P e r m i t s
Value - $ MiL
Residential Permits - Thous.
Single-family units
Multi-family units
Total Building Permits
Value - $ MiL
GEORGIA
Nonresidential Building Permits Total Nonresidential
Industrial Bldgs.
Offices
Stores
Hospitals
Schools
$ Mil.
1,020
160
240
103
26
35
1,045
156
247
104
27
34
1,015
177
250
116
21
14
+
0
10
4
- 11
+ 24
+ 150
Residential Building Permits
Value - $ MiL
Residential Permits - Thous.
Single-family units
Multi-family units
Total Building P e r m i t s
Value - $ Mil.
LOUISIANA
Nonresidential Building Permits Total Nonresidential
Industrial Bldgs.
Offices
Stores
Hospitals
Schools
$ Mil.
884
88
265
162
15
25
905
91
263
168
21
25
937
108
305
116
73
21
6
- 19
- 13
+ 40
- 79
+ 19
Residential Building P e r m i t s
Value - $ MiL
Residential Permits - Thous.
Single-family units
Multi-family units
T o t a l Building P e r m i t s
Value - $ MiL
MISSISSIPPI
Nonresidential Building Permits Total Nonresidential
Industrial Bldgs.
Offices
Stores
Hospitals
Schools
$ MiL
170
13
42
38
4
1
174
15
42
39
4
2
177
20
37
37
8
1
4
35
+ 14
+
3
- 50
0
Residential Building Permits
Value - $ MiL
Residential Permits - Thous.
Single-family units
Multi-family units
Total Building P e r m i t s
Value - $ MiL
TENNESSEE
Nonresidential Building Permits Total Nonresidential
Industrial Bldgs.
Offices
Stores
Hospitals
Schools
$ Mil.
660
35
107
110
40
7
698
41
133
114
33
6
607
65
105
120
9
8
+
AUG
1982
JUL
1982
AUG
1981
ANN
%
CHG
12-month Cumulative Rate
-
-
-
-
11
+ 70
-
-
35,018
34,772
47,399
- 26
463.5
395.1
461.5
392.6
681.1
482.4
- 32
- 18
82,178
82,862
99,877
- 18
6,432
6,467
9,890
- 35
93.9
81.3
92.7
83.9
148.5
126.6
- 37
- 36
12,707
12,956
17,259
- 26
221
239
394
- 44
3.9
4.0
4.0
5.2
7.6
8.0
- 49
- 50
607
6 37
827
- 27
3,993
4,062
6,841
- 42
50.0
50.5
49.6
52.6
89.8
89.4
- 44
- 44
7,147
7,332
11,030
- 35
1,118
1,077
1,202
21.4
10.7
20.9
10.0
25.2
9.8
2,137
2,123
2,217
-
7
- 15
+ 9
-
4
_____
-
-
-
9
- 46
+ 2
8
+344
- 13
Residential Building Permits
Value - $ MiL
Residential Permits - Thous.
Single-family units
Multi-family units
Total Building P e r m i t s
Value - $ MiL
580
579
681
- 15
9.2
8.5
9.2
8.5
11.4
9.1
- 19
- 7
1,463
1,483
1,618
- 10
150
142
232
- 35
3.1
2.0
2.8
1.9
4.5
3.7
- 31
- 46
321
315
409
- 22
371
368
541
- 31
6.3
5.6
6.2
5.7
10.0
6.6
- 37
- 15
1,031
1,066
1,158
- 11
_
Data supplied by the U. S. Bureau of the Census, Housing Units Authorized By Building P e r m i t s and Public Contracts, C-40.
Nonresidential data excludes the cost of construction for publicly owned buildings. The southeast data represent the t o t a l of
the six states. The annual percent change calculation is based on the most recent month over prior year. Publication of F. W.
Dodge construction c o n t r a c t s has been discontinued.
http://fraser.stlouisfed.org/
Federal Reserve
Bank of St. Louis
70
FEDERAL RESERVE B A N K O F A T L A N T A
GENERAL
Personal Income-? bil. SAAR
(Dates: 2Q, IQ, 2Q)
Taxable Sales - $ bil.
Plane Pass. Arrivals (thous.) JUL
Petroleum Prod, (thous. bis.)
Consumer Price Index
1967=100
Kilowatt Hours - mils. (MAY)
SOUTHEAST
Personal Income-$ bil. SAAR
(Dates: 2Q, 1Q, 2Q)
Taxable Sales - $ bil.
Plane Pass. Arrivals (thous.) JUL
Petroleum Prod, (thous. bis.)
Consumer Price Index
1967=100
Kilowatt Hours - mils. (MAY)
ALABAMA
Personal Income-? bil. SAAR
(Dates: 2Q, 1Q, 2Q)
Taxable Sales - $ bil. (JUN)
Plane Pass. Arrivals (thous.) JUL
Petroleum Prod, (thous. bis.)
Consumer Price Index
1967=100
Kilowatt Hours - mils. (MAY)
FLORIDA
Personal Income-? bil. SAAR
(Dates: 2Q, 1Q, 2Q)
Taxable Sales - ? bil.
Plane Pass. Arrivals (thous.) JUL
Petroleum Prod, (thous. bis.)
Consumer Price Index - Miami
Nov. 1977 = 100
Kilowatt Hours - mils. (MAY)
GEORGIA
Personal Income-? bil. SAAR
(Dates: 2Q, 1Q, 2Q)
Taxable Sales-? bil. (1Q-4Q-1Q)
Plane Pass. Arrivals (thous.) JUL
Petroleum Prod, (thous. bis.)
Consumer Price Index - Atlanta
1967 = 100
Kilowatt Hours - mils. (MAY)
LOUISIANA
Personal Income-? bil. SAAR
(Dates: 2Q, 1Q, 2Q)
Taxable Sales - ? bil.
Plane Pass. Arrivals (thous.) JUL
Petroleum Prod, (thous. bis.)
Consumer Price Index
1967 = 100
Kilowatt Hours - mils. (MAY)
Personal Income-$ bil. SAAR
(Dates: 2Q, IQ, 2Q)
Taxable Sales - $ bil.
Plane Pass. Arrivals (thous.) JUL
Petroleum Prod, (thous. bis.)
Consumer Price Index
1967 = 100
Kilowatt Hours - mils. (MAY)
Personal Income-$ bil. SAAR
(Dates: 2Q, 1Q, 2Q)
Taxable Sales - $ bil.
Plane Pass. Arrivals (thous.) JUL
Petroleum Prod, (thous. bis.)
Consumer Price Index
1967 = 100
Kilowatt Hours - mils. (MAY)
ANN.
%
CHG.
SEP
1982
AUG
1982
SEP
1981
2,541.5
N.A.
N.A.
8,684.3
2,518.6
N.A.
N.A.
8,669.1
2,370.9
N.A.
N.A.
8,640.2
+ 1
293.2
158.6
292.2
167.4
279.3
160.6
+ 5
- 1
301.8
N.A.
4,353.0
1,386.5
297.0
N.A.
4,192.5
1,387.5
280.5
N.A.
4,292.5
1,421.3
+ 8
N.A.
24.9
N.A.
25.4
N.A.
26.0
- 4
33.6
20.9
107.8
57.0
33.0
20.9
112.9
56.5
31.7
20.2
127.1
60.5
+ 6
+ 3
-15
- 6
N.A.
3.4
N.A.
3.5
N.A.
3.7
- 8
111.3
66.7
2,277.5
73.0
SEP
156.1
7.0
108.7
66.6
2,056.9
75.0
JUL
155.1
6.9
102.1
65.3
1,961.3
97.4
SEP
150.2
7.0
+ 9
+ 2
+ 16
-25
52.5
34.5
1,504.1
N.A.
AUG
295.6
3.7
51.8
34.3
1,564.1
N.A.
JUN
291.1
3.9
49.2
32.1
1,750.8
N.A.
AUG
276.1
3.8
+ 7
+ 8
-14
43.7
N.A.
273.5
1,164.0
43.0
N.A.
259.4
1,164.0
40.4
N.A.
258.0
1,168.0
+ 8
N.A.
4.3
N.A.
4.3
N.A.
4.4
19.7
N.A.
32.8
92.5
18.9
N.A.
33.0
92.0
18.5
N.A.
39.1
95.4
N.A.
1^6
N.A.
U>
N.A.
1J5
41.0
25.5
157.3
N.A.
41.5
25.4
166.2
N.A.
38.6
23.5
156.2
N.A.
N.A.
4.9
N.A.
5.2
N.A.
5.5
+ 7
+ 1
- 2
+ 4
0
+ 7
- 3
+ 6
- 0
- 2
+ 6
-16
- 3
+ 6
+ 9
+ 1
-11
SEP
1982
SEP
1981
AUG (R)
1982
ANN.
%
CHG.
Agriculture
Prices Rec'd by Farmers
136
Index (1977=100)
Broiler Placements (thous.)
78,072
60.00
Calf Prices (? per cwt.)
27.1
Broiler Prices (« per lb.)
5.28
Soybean Prices (? per bu.)
209
Broiler Feed Cost (? per ton)
133
80,612
61.90
26.3
5.59
215
133
77,721
61.40
26.3
6.21
222
+ 2
+ 0
- 2
+ 3
-15
- 6
Agriculture
Prices Rec'd by Farmers
120
Index (1977=100)
Broiler Placements (thous.)
30,677
55.58
Calf Prices (? per cwt.)
26.6
Broiler Prices ($ per lb.)
5.43
Soybean Prices (? per bu.)
204
Broiler Feed Cost (? per ton)
120
31,843
57.84
25.6
5.83
213
125
30,723
56.77
24.9
6.34
219
- 4
- 0
- 2
+ 7
-14
- 7
Agriculture
Farm Cash Receipts - ? mil.
903
(Dates: JUN, JUN)
Broiler Placements (thous.)
9,478
Calf Prices (? per cwt.)
56.50
25.0
Broiler Prices (<t per lb.)
5.54
Soybean Prices (? per bu.)
Broiler Feed Cost (? per ton)
205
9,938
57.20
24.5
5.73
210
904
9,770
55.70
24.0
6.09
235
- 0
- 3
+ 1
+ 4
- 9
-13
Agriculture
Farm Cash Receipts - ? mil.
(Dates: JUN, JUN)
2,905
Broiler Placements (thous.)
1,795
59.70
Calf Prices (? per cwt.)
Broiler Prices (<t per lb.)
27.0
5.54
Soybean Prices (? per bu.)
210
Broiler Feed Cost (? per ton)
1,839
61.10
25.0
5.73
220
2,588
1,800
59.90
25.0
6.09
230
+12
- 0
- 0
+ 8
- 9
- 9
Agriculture
Farm Cash Receipts - ? mil.
1,270
(Dates: JUN, JUN)
Broiler P l a c e m e n t s (thous.)
12,281
49.10
Calf Prices (? per cwt.)
26.5
Broiler Prices ($ per lb.)
5.50
Soybean Prices (? per bu.)
200
Broiler Feed Cost (? per ton)
12,423
54.20
25.0
6.25
215
1,265
12,312
52.50
24.5
6.46
210
+ 0
- 0
- 6
+ 8
-15
- 5
Agriculture
Farm Cash Receipts - ? mil.
561
(Dates: JUN, JUN)
N.A.
Broiler Placements (thous.)
58.50
Calf Prices (? per cwt.)
27.5
Broiler Prices (<t per lb.)
5.51
Soybean Prices (? per bu.)
Broiler Feed Cost (? per ton)
250
N.A.
60.70
27.5
5.84
250
595
N.A.
58.60
26.5
6.57
245
- 6
Agriculture
Farm Cash Receipts - $ mil.
(Dates: JUN, JUN)
839
Broiler P l a c e m e n t s (thous.)
5,927
Calf Prices ($ per cwt.)
57.50
Broiler Prices (<t per lb.)
29.0
Soybean Prices (? per bu.)
5.31
Broiler Feed Cost ($ per ton)
200
805
5,574
58.70
26.5
6.30
205
+ 4
5,973
58.10
28.0
5.83
205
Agriculture
Farm Cash Receipts - $ mil.
713
(Dates: JUN, JUN)
1,217
Broiler Placements (thous.)
51.90
Calf Prices ($ per cwt.)
25.5
Broiler Prices (<t per lb.)
5.36
Soybean Prices ($ per bu.)
Broiler Feed Cost ($ per ton)
176
1,326
55.90
25.5
5.63
181
647
1,266
54.80
25.0
6.28
195
+ 10
- 4
- 5
+ 2
-15
-10
-
- 0
+ 4
-16
+ 2
+ 6
-
-16
- 2
Notes:
Personal Income data supplied by U. S. Department of Commerce. Taxable Sales are reported as a 12-month cumulative total. Plane
Passenger Arrivals are collected from 26 airports. Petroleum Production data supplied by U. S. Bureau of Mines. Consumer Price
Index data supplied by Bureau of Labor Statistics. Agriculture data supplied by U. S. Department of Agriculture. Farm Cash
Receipts data are reported as cumulative for the calendar year through the month shown. Broiler placements are an average weekly
r a t e . The Southeast data represent the t o t a l of the six s t a t e s . N.A. = not available. The annual percent change calculation is based
on most recent data over prior year.
revised.
Digitized Rfor= FRASER
http://fraser.stlouisfed.org/
NOVEMBER 1982, E C O N O M I C
Federal Reserve
Bank of St. Louis
REVIEW
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+ 9
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Federal Reserve Bank of Atlanta
P.O. Box 1731
Atlanta, Georgia 30301
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Address Correction Requested
Atlanta, Ga.
P e r m i t 292
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