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2
I.
T he R egu lation o f B ank Entry
.................................5
Michael C. Keeley
II.
Savings and L oan A sse t C om p osition and the M ortgage
M a r k e t..........................................
14
Frederick T. Furlong
III.
D eterm in in g G eograph ic M arkets for D e p o sit
C om p etition in B a n k in g ............................................................. 25
Michael C. Keeley and Gary C. Zimmerman
IV.
Interest R ate V olatility and A ltern ative M onetary C ontrol
P ro ced u res......................................................................................... 46
Robert H. Rasche
Editorial Committee:
Adrian W. Throop, Frederick T. Furlong, Randall Pozdena, Bharat Trehan and Jack Beebe.
wov e
PS.;?? 4
3
4
The R
This paper analyzes the regulation of entry into banking through
government chartering. Entry regulations are shown to be necessary
for other anticompetitive regulations to succeed in raising industry
profits to above-normal levels. Empirically, we find that although
regulation reduced entry during the 1936-1962 period, entry restrictions appear to have been relaxed since then. If entry has been
unrestricted for some time, the deregulation of deposit rates or other
forms of banking deregulation are unlikely to affect the aggregate
profits of the banking industry, at least in the long-run.
a group have an interest in restricting competition (and thereby generating economic rents),
they would promote regulations that would
eliminate or reduce interbank competition or
reduce competition from nonbank firms that
provide substitute services.
Currently, many of these restrictions on bank
competition are breaking down. Deposit-rate
ceilings essentially have been eliminated on all
but business checking accounts. Geographic restrictions are diminishing through the liberalization of branching laws and through regional
interstate compacts. They are also being
evaded through various legal loopholes such as
"nonbank" banks.! Product-line distinctions
between banks and nondepository financial
firms also are blurring. What will be the impacts of these changes? Is banking becoming
more competitive and less profitable, and will
bank failures consequently mount as profits decline?2 Or, will deregulation merely change the
way banks compete with each other rather than
increase the overall degree of competition?
The answers to these questions depend in
large part on how effective entry regulations
have been in actually reducing entry.3 In general, anticompetitive regulations that fix prices
would be effective in reducing the degree of
competition only if entry also were restricted.
This is because if entry is not limited, the regulation of prices will not be able to suppress
nonprice competition by new entrants. Con-
Commercial banking in the United States is
a highly regulated industry. Banking regulations pervade almost every aspect of the business, including whether, how and where a bank
can do business. Ostensibly, the primary rationale for banking regulation is to protect and promote the safety and soundness of the financial
system. Indeed, recently, as bank failures have
mounted, some have called for increased
regulation.
As a legacy of the 1930s, many banking regulations were implemented that did not deal directly with safety and soundness issues, but instead, restricted competition among banks
themselves and between banks and other financial institutions. For example, various restrictions on entry, such as government control of
chartering, geographic restrictions on branching, and product-line restrictions, at least have
the potential to reduce competition.
Other regulations that do not deal with entry,
such as consumer deposit rate ceilings, also
have the potential to lessen competition. In
fact,some economists have argued that the regulation of entry as well as other anti-competitive measures reflect the "capture" of the regulators by the regulated firms. Since banks as
*Senior Economist, Federal Reserve Bank of
San Francisco. Comments from Fred Furlong,
Gary Zimmerman and the editorial committee,
and research assistance from Joni Whitmore
are appreciated.
5
thereby create economic rents even in the absence of other anticompetitive restrictions. Second, we apply this general analytic framework
to the banking industry. We analyze empirically
how regulation has affected the rate of entry
into banking ··and . whether entry restrictions
have been relaxed recently. Finally, the implications of the current deregulatory trend in
banking are explored in light of our findings
about the regulation of bank entry.
Section I examines how entry restrictions
alone or in conjunction with other regulations
in theory would affect competition in banking.
Then, in Section II, data on bank entry are analyzed to assess whether actual entry has been
limited. Section III presents the summary and
conclusions.
versely,ifentry is restricted, the degree of competition generally will be reduced even without
other anticompetitive restrictions.
Purpose and Organization
The objectives Of this paper are· threefold.
First, we analyze, in general, the effects of the
government regulation of entry into an industry
and the interaction of entry regulation with
other types of regulation. We show that without
entry restrictions, other regulations seeking to
limit competition will be ineffective in the creation of economic rents. However, anticompetitive regulations may very well alter the form of
competition. Conversely, effective entry regulations generally will limit competition and
I. The Theory of Entry and Competition
Entry plays a prominent role in the economic
theory of competition. Free entry is the key
economic force that ensures that there are an
optimal number of firms (from society's viewpoint) in a particular industry and that individual firms charge competitive prices and operate
at optimum scales. 4
In an industry in which individual firms operate independently (that is, they do not collude), the short-run supply curve is the (horizontal) sum of the marginal cost curves of the
firms in the industry (at a particular moment
in time). If, at the price determined by supply
and demand, price is above each firm's average
cost (because individual firms have increasing
marginal costs), new firms will be attracted to
the industry until price is forced down to equal
average cost. Thus, in long-run equilibrium,
the entry of new firms ensures that price equals
(minimum) average cost (which also equals
marginal cost), that an optimal number of firms
are in the industry, and that profits are normal.
If, however, entry were restricted at less than
the socially optimal number of firms, firms
would produce at levels above their minimum
average costs, prices would exceed average
costs, and firms would enjoy above-normal
profits (even in the absence of collusion) unless
firms were able to produce at constant costs. If
firms could produce at constant costs, so that
marginal and average costs were equal, then
restrictions on the number of firms in an industry would have no effects on prices or profits as long as the firms did not collude. Thus,
constant costs of production are equivalent in a
sense to unrestricted entry.
Although there is an empirical literature that
sugge~ts that banking is characterized by constant costs, at least for banks above some minimum size, these econometric results are inconsistent with a wide range of other evidence. s
First, the new theory of firm size, developed
by Rosen (1982), Oi (1983) and others, argues
that each firm may have a U-shaped cost function even though firms of widely differing sizes
appear to have similar measured average costs. 6
According to this theory, any given firm will be
subject to increasing average (and marginal)
costs if it expands output beyond its equilibrium
level, holding managerial talent constant. The
apparent equality of average costs of firms of
different sizes is due to higher levels of managerial talent at larger firms and greater compensation of more able managers.
Second, there is anecdotal evidence that
6
there are very strong economic forces propelling the nation toward interstate banking. This
suggests that there must be important scale
economies, at least in banking. Finally, if banking were characterized by constant costs, it
seems unlikely that such a wide variety ofTeg~
ulations regarding the scale of their operations,
such as merger regulation, chartering, and geographic restrictions would exist since such regulations would have no effect on competition,
interest rates, or the pricing of bank services.
Thus, it seems likely that, in banking, firms do
have V-shaped cost functions.
Entry and the threat of entry are also strong
forces that tend to eliminate cartels. For example, if the firms in an originally competitive
industry (where price equaled average cost)
succeeded in forming a successful cartel that
restricted industry output by allocating output
to members (and consequently raising prices),
new firms would have a strong incentive to enter because of the above-normal profits to be
earned. New firms would continue to enter until price equalled average cost and profits returned to normal levels. Since potential cartel
members are aware of the incentives for entry
caused by a cartel, cartels rarely form if entry
is unrestricted. Thus restrictions on entry are a
necessary precondition for other restrictions on
competition to succeed in raising firms' profits
to above-competitive levels.
tive level. Such an above-competitive price (relative to costs) would make an industry highly
profitable and thus attractive to enter. If price
cutting were permitted, new firms would enter
and force down prices and profits to competitive.tevels ··byincreasing···the· ··quantity .of·· the
product and cutting prices.
However, even if price cutting were prohibited, new firms would still enter and compete
along variousnonprice dimensions. As George
Stigler stressed in his classic 1968a article,
"Wl1en a uniform price is imposed upon, or
agreed to by, an industry, some or all of the
other terms of sale are left unregulated". For
example, competition through quality, advertising, convenience and by providing additional
nonpriced or underpriced services may all be
viable forms of nonprice competition.
Unless nonprice competition is also fully prohibited, something virtually impossible to do
without assuming full control of an industry
(for example, nationalizing it), new firms will
enter and existing firms will expand their level
of nonprice competition until average costs are
driven up to equal price. Thus, without entry
restrictions, firms will compete away any potential economic rents due to regulation
through nonprice competition. With entry restrictions, however, things are much different.
First, consider the effects of entry restrictions
alone. If there were fewer than the socially optimal number of firms in an industry, then firms
would price competitively (price would equal
marginal cost) but price would exceed average
cost and the firms would earn above-normal
profits. If a regulation, such as a minimum
price, were then imposed on the industry (set
to equate industry marginal revenue with industry marginal cost), then the industry would
have the potential to earn even larger (abovenormal) profits depending on whether the potential economic rents were entirely competed
away through nonprice competition. Thus, regulation has the potential to reduce competition
and increase profits only in an industry in which
entry is restricted.
But will economic rents be competed away
through nonprice competition even in an industry in which entry is restricted?
Regulation and Entry Restrictions
A large number of government regulations
are either intended to restrict competition and
thereby raise the regulated firms' profits or
have that effect. However, just as private restrictions on competition (for example, cartels)
will be unsuccessful in restricting competition
unless entry is limited, so will government regulations. Despite the much stronger enforcement tools at the government's disposal, competition can take place along so many
dimensions that it is virtually impossible to prevent it by regulation.
For example, suppose the government attempts to restrict competition in an industry by
imposing a minimum price above the competi-
7
With restricted entry, only eXlstmg firms
would expand the level of nonpriced services
(and goods). Assuming such firms face increasing marginal costs of nonprice competition (as
is likely), existing firms would expand output
tothe pointwhere the total marginal cost of the
product plus the nonpriced services equals demand. Thus, with entry restrictions, abovenormal profits would not be competed away unless nonprice competition can occur at constant
costs-something that seems highly unlikely.
Thus, regulation has the potential to increase
the profits of the regulated firms to above-normal levels, but only if entry is also limited.
Moreover, nonprice competition alone is unlikely to lead to competitive profit levels.
If existing banks could not provide such services and conveniences at constant costs (that
is, if existing firms face increasing marginal
costs of expanding the provision of such services so that marginal costs exceed average
costs), new firms would be attracted to such a
regulated industry. Thus, binding deposit ceilings, as well as other forms of anticompetitive
restrictions, may attract new entrants. Counterbalancing this force would be the overall decline in the industry caused by its increased
costs compared to industries providing substitute products that are not subject to regulation.
With unrestricted entry, deposit ceilings may
affect the type of competition and the number
of firms, but they will not affect the degree of
competition or the profitability (aggregate economic rent) of the industry.
The effects of deposit interest ceilings generally will be very different with restricted entry. First, entry restrictions alone reduce the demand for deposits so that rates paid on deposits
would be below levels that would prevail in the
absence of entry restrictions. Thus, if the number of banks were limited by entry restrictions,
this alone would cause deposit costs to be
lower, loan rates to be higher and, consequently, profits to be higher than normal. Second, if binding ceilings were then imposed on
such an industry, limiting deposit rates to below
the (already low) levels the firms would set
through competition with one another, the existing banks would then expand nonpriced services up to the point where interest plus marginal service costs of deposits equaled their
marginal revenue products.
If individual banks faced increasing marginal
costs of providing nonpriced services, additional services would be provided up to the
point where marginal deposit costs equaled the
value of deposits' marginal products, but average deposit costs would be less. Thus, with entry restrictions, consumer deposit ceilings may
confer economic rents on existing banks.
Since the effects of (nonentry) regulation and
hence deregulation on industry profitability depend in large degree on whether entry was limited, we now turn to an empirical analysis of
the effects of chartering regulation on entry
into banking.
Entry and Deposit Ceilings
As an example of how entry restrictions interact with other regulations, consider the effects of the regulation of deposit interest rates
on consumer accounts. Initially, if a depositrate ceiling were imposed below the market
rate, existing banks would earn supranormal
profits by having lower costs of deposits. This
above-normal level of profits would provide
strong incentives for both new banks to enter
and existing banks to increase levels of cOnvenience or nonpriced services until (average) deposit costs were bid up to competitive levels and
profits returned to normal levels. The effects
of the ceilings, however, would differ if entry
also were restricted.
First, consider the case where entry is unrestricted. As long as new banks could enter at
no cost disadvantage to existing banks, any excess profits would be eliminated in the longrun. This is because firms would continue to
enter and provide various forms of underpriced
conveniences until any excess profits were eliminated. However, such non-priced services
would be expanded beyond the level they
would have attained in the absence of regulation and, consequently, average (and marginal)
deposit costs would be higher because consumers value these services at less than their
costs (that is, from a consumer's viewpoint, services and interest are not perfect substitutes). 7
8
II. Empirical Analysis of Chartering Restrictions
The United States has a "dual" banking system. Currently, persons wishing to start a bank
can apply for a federal charter from the ComptroHer of the Currency or .apply to the .appropriate state banking agency for a state charter.
However, to obtain federal deposit insurance,
newly chartered state banks must either receive
approval directly· from the Federal Deposit· Insurance Corporation (FDIC) or become membersof the Federal Reserve System. (Federally
chartered banks are all members of the Federal
Reserve System and all have federal deposit
insurance. )
In general, competition among chartering
agencies would seem to limit any single agency's power to restrict entry. This is because if
one agency restricted entry severely, firms
seeking charters would go to another agency.
Over time, an agency with an overly restrictive
chartering policy would find itself with few
firms to regulate.
Prior to the creation of the FDIC and the
passage of the Banking Act of 1935, which set
up a federally administered "needs" criteria for
chartering federally insured banks, there was
active competition between the states and the
federal government for chartering banks. However, with the creation of the FDIC, the competition for the chartering of insured banks was
probably reduced since the owners of statechartered banks had to apply either to the
FDIC or the Federal Reserve to obtain federal
deposit insurance. Thus, the federal government could control the number of (federally)
insured banks, although the power to do so was
diffused through three agencies.
As thrifts have gained more bank powers recently, thrift charters may be becoming good
substitutes for bank charters. If so, competition
from the Federal Home Loan Bank Board
(FHLBB), which controls the chartering of federally insured savings and loans, may be introducing a new element of competition among
federal agencies for the chartering of depository institutions.
Although the diffusion of chartering powers
through several federal agencies may have introduced a significant degree of interagency
competition and made entry regulation relativelyineffectiye•• in•• aGtQally restrictingentry,·it
is an empirical question whether and/or to what
degree entry has been limited.
Previous Studies
In a classic study (1965) dealing with the effects of chartering on the rate of bank entry,
Sam Peltzman concluded that chartering redQced. the rate of bank entry by at least .50 percent compared to what would have occurred
without such restrictions. His finding is based
on a comparison of the rate of entry prior to
the passage of the Banking Act of 1935 and the
creation of the FDIC, which he characterizes
as the "free-banking" era, to the 1936-1962period, during which he argues federal-state COmpetition for the chartering of insured banks was
effectively eliminated.
In conducting a study to determine what the
effects of the 1935 Banking Act were, ideally
one would want to control for all factors other
than the passage of the Act that might affect
entry. Especially important would be the profe
itability of the industry because increased profitability would lead to greater entry (and lower
profitability would lead to less entry) all other
things equal. However, to control for variations
in profitability properly is difficult because
profitability itself depends on entry restrictions
(that is, it is endogenous). (In fact, the whole
point of entry restrictions is to increase
profitability. )
Although Peltzman included profitability as
a control variable, he ignored its endogeneity.
Thus, his estimates may have been less reliable
than estimates that ignored potential (exogenous) changes in profitability altogether. Byneglecting the fact that limited entry itself WOQld
increase profitability, he likely overestimated
the effect of the Act on deterring entry.
A more recent (1974) re-analysisof Peltzman's data by Linda and Franklin Edwards tries
to address the endogeneity of profitability. 8
They argue that although Peltzman overstated
9
the effects of chartering restrictions, his conclusion that chartering restrictions substantially
limited the rate of entry is valid.
Below, I take another look at these data and
t=)(tel1cl.tl1t=.al1alysis fr()Il1.1962.. through 1983, the
last year for which complete data are currently
available. I do not attempt to control for the
effects of varying profitability on entry because
of the difficulty in properly controlling (statistically) for the effect of regulation on
profitability.
Chart 1
Entry Rates for Commercial Banks, 1921-1983
Percent
4
I.. Post-Saxon Era
3
Free·Banking
Era
'-1..
Restricted Era
2
A Further Analysis
Although the Banking Act of 1935 did apparently substantially lessen state-federal competition for the chartering of insured banks during the 1936-1962 period, there was still
interagency competition between the FDIC,
the Comptroller, and the Federal Reserve. 9
More recently, as S&Ls have gained more
and more bank-like powers, the FHLBB may
have increased the degree of competition
among federal agencies for chartering. Because
of this actual and potential competition among
chartering agencies, it may well be that chartering would become a less and less effective restriction to entry over time. Below, we look at
entry rates during the post-1962 period in addition to those during the 1921-1962 period
analyzed by Peltzman to see whether entry rates
have remained low or increased.
Entry rates (the number of banks opening in
year t divided by the number of existing banks
at year t-l) are plotted in Chart 1. The sources
of the data used to calculate entry rates are the
same as those used by Peltzman and are described in the Data Appendix. For the freebanking period, 1921-1935, it is somewhat difficult to define entry properly because of the
relatively large number of reopenings of previously suspended banks and the difficulty in
distinguishing new openings from re-openings.
The re-openings of suspended banks was especially high during the 1931-1935 period before FDIC insurance reduced the number of
bank failures.
I have chosen to define entry as simply the
number of banks opening regardless of whether
they were new openings or re-openings, partly
o L..---&_.............JI....--'-_"'---J._..&....--I._...I
1921
1928
1935
1942
1949
1956
1963
1970
1977
1984
because this is the only consistent definition in
the published data across the whole 1921-1983
period, and partly because re-openings also
represent a new source of competition. Because
entry rates might be somewhat overstated by
this procedure, especially during 1933 and 1934
when the number of re-openings was very
large, I have excluded data for these years from
the analysis. This has the effect of reducing the
average entry rate during the free-banking
period.
For the period 1921-1935, the average rate
of entry was about 1. 7 percent per year. In contrast, during the 1936-1962 period, the average
rate of entry declined to only .7 percent a year,
a statistically significant decline (see Chart 1).
This decline of approximately 50 percent is approximately the same magnitude found by
Peltzman using his more complex but flawed
statistical procedure. Thus, the evidence supports the notion that there was a significant decline in the rate of bank entry during the period
following the passage of the Banking Act of
1935 until 1962.
On November 15,1961, James Saxon was appointed Comptroller of the Currency. He was
widely regarded as a proponent of the national
banking system and was viewed as being much
more liberal than his predecessors in his chartering policies. The data in Chart 1 suggest that
initially his policies did have a significant effect
10
on raising entry rates. However, by the last year
of his tenure (1966), entry rates had fallen back
to. the pre-Saxon level. Then, beginning in
1968,entry rates again began a sharp upward
ris~.al1cl<:Ql1til111.~(jJQJgllgwa cy<:1i<:a1. patt~m
unique to the post-1962 period.
Looking at the 1962-1983 period as a whole,
entry rates averaged essentially the same as
during the 1921-1935 period. Thus, itilPpears
that Saxon began an era where entry into banking was no more difficult than during the "freebanking" era. If correct, this means that banking has been a more competitive industry, at
least since 1962. 10 . However, another interpretation of the data in Chart 1 would be that entry
restrictions were gradually relaxed beginning
perhaps as early as 1950 since the data ,:"ould
not be inconsistent with an upward trend m entry rates starting then. In either event, entry
now does not appear to be significantly restricted, at least compared to the free-banking
era.
Looking at entry in banking only in terms of
entry by new banking organizations probably
understates entry because of the possibility of
entry through branching, entry by S&Ls, and
increased competition by nondepository institutions (such as Merrill Lynch). For example,
although the total number of banking and S&L
offices was relatively constant from 1934 to the
early 1950s, the number of offices has almost
tripled since then (see Chart 2), and the number of offices per real deposit dollar has shown
an upward trend since 1962 (although it has not
reached anywhere near the level of the 1920s
and 1930s).
The recent deregulation of banking, specifically the removal of consumer deposit-rate ceilings, appears to be taking place in an environ-
m.
90,000
Chart 2
Total Banking & Savings Association Offices,
1920-1982
80,000
70,000
60,000
30,000
20,00q920 1927 193419411948 1955 1962 1969 1976 1983
ment in which entry restrictions have been
effectively eliminated or at least have been substantially relaxed. If so, deposit-rate deregulation should have little or no long-run effects on
the profitability of the banking industry as a
whole because free entry ensures that, in the
long-run, profitability will be at normal, competitive levels.
However, individual banks may have different experiences as they make the transition
from nonprice to price competition. 11 Further,
if entry restrictigns. had been effectively removed prior to cleregulation, then deregulation, by eliminating the inefficiencies inherent
in nonprice competition, should have led to an
expansion of the.banking industry relative to its
nonbank competitors and this in turn would increase incentives for entry. The effects of deregulation may explain the very high entry rates
of the last few years shown in Chart 1. They
are also consistent with anecdotal evidence that
there has been a recent surge in new bank startups (see Brannigan 1985).
Conclusions
The data on bank entry suggest that the regulation of entry through chartering has been
much less restrictive in the post-Saxon era.
Since 1962, entry rates have on average been
equal to those before 1936, a period d~ring
which, it is argued, entry was relatively
unrestricted.
If, in fact, bank entry has been unrestricted
since 1962, then various anticompetitive regulations, such as deposit rate ceilings, would not
have been effective in reducing the degree of
competition in banking. (They would, however,
have made the banking industry less efficient.)
This in turn means that bank profits were
11
not enhanced (or at least are not currently
being .enhanced)by •. these anticompetitive
restrictions.
If the degree of competition and banking
pr()fitshave been atthelevelthey\Vo\ll(j have
been without entry restrictions, then deregulation of consumer deposit rates is .unlikely to af-
fect banking profits or the degree of competition, at least in the long-run. Thus, the current
calls to reregulate banking-to reduce competition and bolster bank profits-to stem the recent spate of bank failures are not focusing on
the real causes of these failures.
Data Appendix
All commercial banking data except those so
noted, including the number of· banks and
branches 1 in existence in a given year, the number of new "primary" qrganizations and the total deposits data:2,come from publications of
the Board of Governors (BOG) of the Federal
Reserve System (FRS).
Stfries for the 1921-1940 period3 come from
the U.S. BOG of the FRS, Supplement to
Banking qnd Monetary Stqtistics, Se.ction I,
1962. (Note: This supplement was originally released in Sections in 1943 as a revised version
of available data frorn the period 1914-1941. It
was published in 1962.)
The 1941-1970 series. are from the U.S. BOG
of the FRS ..Banking and Monetary Statistics,
1941-1970, 1976.
Data for·the197D-1979 period were taken
from the Annual Statistical Digest, 1970-1979,
published jl) 1981 by the BOG.
Since 1979, the Annual Statistical Digest has
been published yearly, and they were used on
a yearly basis from 1980 through 1982.
Data for 1983 for commen:ial banks,
branches, new openings, and total deposits
were obtained directly from the BOG; 1983
data on savings and loans was obtained directly
from the FHLBB.
Although these data areJrom several differentpublications . (of primarily the ..·same
sources), all series are consistently defined,
with the exception of those indicated.
1 Commercial bank branch· data for the year 1920-1934
were obtained from the Historical Statistics of the United
States, Colonial Times to 1970,Patt 2, U.S. Department of
Commerce, Bureau of the Census, 1975.
Branch data for thrifts was collected ffom the SaVings and
Home Financing Source Book, 1952-1955, U.S. Federal
Home Loan Bank Board, and the Savings and Loan Fact
Book, 1962, 1965, 1980, U.S. League of Savings Association, and represent total insureq (federal- and state-chartered) savings and loan associations.
Total deposits dat<i for s<ivings <ind loan associations were
t<iken from the Source Book (see <ibove citing;), 1955, Feder<il Horne Loan Bank BO<ird, for the years prior to 1955.
Citib<isewas used from 1955 to 1983 (actually from BOG
FRB Table 1.7).
Total Real Deposits were c<iJcul<ited using an implicit price
deflator (wholesale) from the Historical Statistics of the
United States, Colonial Times to 1957 (see <ibove).
Total Offices per r.eal deposit. dollar W<iS c<iJcul<itedby dividing tot<ilbank <ind thrift offices by the sum of their .tot<il
re<il deposits.
2
The 1921-1940 portion of the tot<il number of commerci<il
b<inks in existence (<it ye<ir-end) series W<iS multiplied by a
factor of 1.003919373 to correct for <i ch<inge in the series
definition from "All Incorpor<ited" to "All Commercial"
b<inks after 1940.
3
12
FOOTNOTES
REFERENCES
1. The legal status ofnonbank banks was unclear at the
time this article· went to •press.
Brannigan, Martha. "OeregulationSpawns a· Wealth of
Small Banks", The Wall StreetJournal, Vol. CXII, No.
88., May 6, 1985.
2. Failures are less likely in an industry where firms are
earning above normal profits (Elc;:onomic rents). In such inQustries;.ittakesal€lrQElrrandQmshocktoreduclOdemand
or increase costs to make earnings (or net worth) negative
and drive the firm out of business.
Dwyer, Geralg P., Jr. "The Effects of the Banking Acts of
1~33and19350nCapitai .lnvestmerttinCommefcial
Banking", Journal of Money Credit and Banking, Vol.
13, No.2, May 1981.
3. Chartering regulation, branching restrictions, and producHne regulation are. aU forms of entry regulation.
Edwards, Linda N. and Franklin R. Edwards. "Measuring
the EffectivenElss of Regulation: The Case of Bank
Entry ··Regulation,"· Journal of Law and Economics,
Volume 17, No.2, October 1974.
4. Throughout this paper, I use the definition ofa barrier
to Elntry that was first formul(lted by George Stigler (1968b):
"A barrier to entry may be defined as a cost of producing
(at some or every rate of Output) which must be borne by
a firm which seeks to enter an industry but is not borne by
firms already in the industry."
Gilbert,A. Alton. "Bank Market Structure and Competition",
Journal of Money Credit and Banking, Vol XVI, No.4,
Pt.2, November 1984.
KeeIElY, Mic;:hael C ..''The Economics of Firm Size: Implications from Labor Market Studies", Economic Review, Federal Reserve Bank of San Francisco, Winter
1984.
Free or unrestricted entry means there are no barriers to
entry. This concept of a barrier to entry contrasts sharply
with the view that any cost of doing business is a cost of
entry. That.is, I do not view capital requirements (or land
or labor requirements for that matter) as costs of entry per
se, as opposed to costs of doing business.
Keeley, Michael C' and Gary C' Zimmerman. "Competition
for Money Market Deposit Accounts", Economic Review, Federal Reserve Bank of San Francisco, Spring
1985.
5. See Gilbert (1984) for a review of this literature.
Oi, Walter. "Heterogeneous Firms and the Organization of
Production", Economic Inquiry, Vol. XXI, No.2, April
1983.
6. See Keeley (1984) for evidence supporting this notion.
7. See Keeley and Zimmerman (1985) for an elaboration
of this argumElnt.
Peltzman, Sam. "Entry into Commercial Banking", Journal
of Law and Economics, Vol. 8, No. 11, October 1965.
____. "Capital Investment in Corrimercial Banking
and Its Relationship to Portfolio Regulation", Journal
of Political Economy, Vol. 78, No.1, January/February
1970.
_ _ _. "Bank I;:ntry Regulation: Its Impact and Purpose", The National Banking Review, Vol. 3, No.1,
September 1965.
8. However, they do not employ a simultaneous equations
technique. Thus,one may also question the validity of their
estimates.
9. See Kenneth Scott (1979).
10. An alternative hypothesis consistent with these data is
that some other force, such as an exogenous increase in
banking profitability, caused the rate of entry to increase
during these yea~s. However, it seems unlikely that an increase in profitability would persist over a 20-year period.
Rosen, Sherwin. "Authority, Control and the Distribution of
Earnings", The Bell Journalof Economics, Vol. 13, No.
2, Autumn 1982.
11. It is conceivable that deregulation might have a shortrUn negative effect on profitability as specific capital us~d
to support nonprice competition depreciates in value. However, this factor would have no lasting effect if entry had
been unrestricted prior to deregulation.
Scott, Kenneth. "Bureaucratic Competition and the. Stru.cture of Bank RElgulation", in Issues in Financial Regulation, edited by Franklin R. Edwards, New York:
McGraw-Hill, 1979.
Stigler, George. "Price and Nonprice.Competition", Journal
of Political Economy, Vol. LXXII, No.1, February
1968a.
____. The Organization of Industry. Homewood, Illinois: Richard D.lrwin, 1968b.
Throop, Adrian W. "Capital Investment and Entry in Commercial Banking", Journal of Money Credit and Banking, Vol. 7, May 1975.
13
vings and Loan A
Com
ket
Frederick T. Furlong*
Over the past several years, savings and loan associations have
diversified their asset portfolios by increasing the share of nonmortgage investments. New asset powers, along with poor earnings
and deposit deregulation, have provided the impetus for this change
with its important implications for the survival of savings and loans
as effective competitors in financial markets. However, contrary to
the concerns of some, savings and loans have not diversified their
portfolios to the detriment of the mortgage market.
Savings and loan associations traditionally
have been highly specialized financial institutions. I As they entered the 1980s, they held
over 85 percent of their assets in mortgage
loans and mortgage-backed securities. This
concentration of assets in mortgages stemmed
not only from regulations restricting investment
activities but also from the tax benefits available to thrifts from holding mortgages. In such
an environment, asset management for savings
and loans primarily entailed using liquid assets
as a buffer against fluctuations in flows to deposit accounts subject to interest rate ceilings.
In more recent years, expanded asset powers
have opened new opportunities for thrifts to
invest in nonmortgage assets, while the extremely poor performance of earnings among
thrifts has diluted the appeal of the tax incentives attached to mortgage lending. In addition,
factors affecting liabilities at savings and loans
have led to changes in the composition of their
assets. As a result, savings and loans have increased substantially the share of their funds
allocated to non mortgage assets.
The greater use of asset management and the
diversification into nonmortgage activities by
savings and loans is seen by many as necessary
for them to survive in today's interconnected
financial system. However, the apparent re"
duced emphasis on mortgage lending also has
raised some concerns. One of these is that more
aggressive pursuit of nonmortgage activities by
savings and loans will curtail the flow of funds
to finance housing. 2 This concern is related to
the longstanding belief that the volume of mortgage credit is tied to deposit flows at thrifts.
Much of the public policy regarding savings and
loans has been founded on this belief, including
the differential on interest rate ceilings which
for many years allowed thrifts to pay a higher
explicit return on deposits than commercial
banks.
This paper provides a perspective on the reasons for the increased asset portfolio diversification at savings and loans and the implications
greater diversification may have for the mortgage market. The section, "Asset Diversification," examines how and why the mix of savings
and loan assets has changed during the past several years. It argues that, while the easing of
asset restrictions has had some bearing on
changes in asset mix, tax effects and factors affecting liabilities management also have been
instrumental in determining the asset composition at thrifts. The second section investigates
whether the move to nonmortgage investments
by savings and loans has affected mortgage interest rates and the allocation of funds to mort-
*Economist, Federal Reserve Bank of San
Francisco.
14
gages. The findings in that section do not support the view that the change in asset mix at
savings and loans has had a noticeable impact
on the mortgage market. General comments
and conclusions are presented in the last
section.
I. Asset Diversification
and mortgage-backed secuntIes at FSLIC-insured savings institutions fell from 85 1/2 percent
of total assets at the end of 1979 to a little more
than 73 percentin December 1984. As Chart 1
shows, the drop in the ratio of mortgages to
assets at savings and loans was particularly pronounced between mid-1981 and mid-1983.
Historically, regulations have
options for savings and loans to invest directly in
nonmortgage assets. The regulatory restrictions
have been effectively reinforced by a tax code
that provides strong incentives for thrifts to
hold residential mortgages in the form of loans
and mortgage-backed securities. By holding at
least 60 percent of its assets in specified categories, a depository institution qualifies as a
thrift and is eligible for special tax benefits. 3
Among the "qualifying assets," mortgages are
generally the highest yielding since most of the
other qualifying assets are government obligations. Once meeting the test of a savings and
loan, an institution can defer taxes on a portion
of its income by placing retained earnings in
special loan loss reserve accounts. 4 The maximum proportion of income that can be sheltered in this way is 40 percent. To protect the
maximum amount of income possible, a savings
and loan has to hold at least 82 percent of its
assets in qualifying assets.
These regulatory "restrictions" and tax benefits clearly determined the choice of assets for
savings and loans. Nevertheless, within these
constraints, the asset composition for savings
and loans also has been affected by limitations
they faced in managing liabilities. Having relied
heavily on small-denomination deposits subject
to interest rate ceilings and limited access to
"purchased" funds, savings and loans generally
were not active liability managers. Consequently, asset management at these thrifts consisted mainly of a "passive" adjustment of
short-term asset holdings to absorb swings in
small-denomination deposits.
Through the late 1970s, the interplay of
forces determining the asset composition of
savings and loans resulted in an industry that
held a more or less stable proportion of its assets in mortgages. Over the past several years,
however, the asset mix at savings and loans has
changed dramatically. Combined, mortgages
Asset Restrictions
A natural starting point for explaining this
marked portfolio shift is the change in regulations governing the investment options for savings and loans. In 1980, the Depository Institutions Deregulation and Monetary Control
Act (MCA) broadened asset powers for thrift
institutions, widening their scope to invest in
nonmortgage assets. s Under the Act, federally
chartered savings and loans were permitted to
allocate up to 20 percent of assets to consumer
loans, commercial paper, and other corporate
securities. Federally chartered savings and
loans were allowed to invest in shares of certain
open-end investment companies, to issue credit
Chart 1
Mortgages at FSLlC-lnsured Savings Institutions
as a Share of Their Assets
(quarterly)
Percent
87
85
83
81
79
77
75
73
71 ' - - _......._ ......._ ' - - _.......1976
15
1977
1978
1979
1980
1981
.......- ' -......
1982
1983
1984
cards, to exercise trust and fiduciary powers
similar to those of nationally chartered commercial banks, and to invest up to 5 percent of
assets in education loans and community development and unsecured construction loans. 6
For the most part, this set of new asset powers for savings and loans was adopted to complement the deposit interest rate deregulation
called for in MCA. The decision to phase out
rate ceilings on deposits, rather than to remove
them immediately, was intended mainly to allow thrifts time to diversify and to shorten the
effective maturity of their asset portfolios by
using their new powers.
These regulatory changes were necessary
conditions for meaningful asset diversification
for many savings and loans. However, given the
importance of the tax incentives associated with
mortgage lending, the regulatory measures
were probably not sufficient conditions. In the
past, the ability to make deferred contributions
to reserves provided a compelling incentive for
savings and loans to hold mortgage-related assets irrespective of other regulations. For example, long before MCA, some state-chartered
savings and loans had considerably broader
powers to engage in nonmortgage lending than
their federally chartered counterparts. They did
not exploit this apparent advantage to any real
extent, however, mainly because the tax benefits associated with residential mortgage lending overwhelmed the gains associated with diversifying into nonmortgage assets.
Particularly weak earnings in recent years
have diluted the appeal of the special tax treatment connected with mortgage lending. In the
latter part of 1981 and the first part of 1982,
over three-fourths of the federally insured savings institutions had negative net income. It was
during this period that the most dramatic asset
portfolio adjustments took place. In the last
two years, lower market interest rates have allowed the savings and loan industry as a whole
to post positive net earnings. Nevertheless, by
mid-1984, the proportion of savings institutions
insured by the Federal Savings and Loan Insurance Corporation posting losses still was
about one out of four.
With both the regulatory and tax constraints
to asset diversification relaxed, it is not sur-
TABLE
1
Portfolio Changes at FSLlC-lnsured Savings Institutions
Percent of assets as of December
1979 1980 1981
Change in share of assets
from 1979 to 1984
1982 1983 1984
(percentage points)
Assets
Mortgages and mortgagebacked securities
Cash and securities
Consumer and commercial
loans
Other assets
85.4
8.9
84.0
9.8
82.8
10.1
77.5
12.0
75.2
13.4
73.3
13.3
12.1
4.4
2.8
2.9
3.0
3.2
2.8
4.3
2.9
7.6
3.4
8.0
4.5
8.9
1.7
6.0
-'
~------~,~
,""--",~,~,-------.-,~,"~--~-"-~"",,,,~_._-----
Liabilities
Managed liabilities 1
1
14.4
16.8
20.9
22.3
21.9
26.0
11.6
Include large-denomination CDs, Federal Home Loan Bank advances and other borrowed
funds.
16
prising that we saw a change in the asset composition of savings and loans. Indeed, from
Chart 1, it might appear that the easing of "constraints" on assets was the dominant influence
on the portfolio changes. However, further
ancllvS1S suggests a somewhat more temperate
assessment of the importance of the change in
asset powers and the decline in earnings.
First, only a small portion of the drop in the
ratio of mortgages to assets at savings and loans
was related to an increase in nonmortgage
loans. From 1979 to December 1984, consumer
and commercial loans accounted for only 1.7
percentage points of the 12.1 percentage rise in
the ratio of nonmortgage assets to total assets
at FSLICinsured institutions (Table 1).7 Moreover, the ratio of consumer and commercial
loans to total assets was virtually unchanged
from 1979 to 1982; it rose in 1983 and 1984 after
most of the adjustment in the ratio of mortgages to assets had already taken place.
;J1J'~"'l'C" factors also account for much of the
change in "other assets" shown in Table 1. For
example, induded in "other assets" is "goodwill
and other tangible assets." The value of this
asset category was boosted considerably
through the purchase accounting procedures
used in savings and loan mergers. About 2.3
percentage points of the rise in "other assets"
as a share of total assets from 1979 to 1984 can
be attributed to the rise of goodwill alone. Of
the remaining 3.7 percentage points rise in the
ratio of "other assets," about one-third can be
explained by the increase in FSLIC-insured institutions' equity investments in their service
corporations, something they were allowed to
do before MCA. s
be used by thrifts to qualify for special tax
treatment.
The increase in the relative holdings of "cash
and securities" could reflect factors affecting
small-denomination deposits at thrift institutions. A possible connection
in cash and securities were accumulated in the
face of deposit-rate deregulation which stimulated strong small-denomination deposit flows.
Such a response by savings and loans would be
in keeping with their traditional passive approach to managing liquid assets.
In this context, the quantity of these so-called
"core deposits," which represent the main
source of funding for savings and loans, is difficult to control in the short-run. With limited
use of managed liabilities (which include Federal Home Loan Bank advances, large-denomination CDs, RPs, and mortgage-backed
bonds), most savings and loans have relied to
a large extent on liquid assets, such as those
included in cash and securities, as a buffer for
variations in small-denomination deposit flows.
Under this passive asset and liability management arrangement, there tends to be a positive
correlation between changes in liquid asset
holdings and core deposit flows at savings and
loans.
This characterization of savings and loan
management of liquid assets would seem to be
particularly appropriate in the post-1982 period. Chart 2 shows that with the onset of full
deposit deregulation-the introduction of the
ceiling-free money market deposit account
(MMDA) in late 1982-flows of deposit excluding large CDs surged in early 1983 and remained relatively strong through 1984. 9
Savings and loans responded to a flood of
core deposits in early 1983 by building up their
holdings of cash and securities. In fact, virtually
all of the rise in the ratio of cash and securities
to total assets in 1983 (shown in Table 1) occurred in the first half of the year. 10 After mid1983, that ratio varied some from quarter to
quarter, but on balance did not change much
through the end of 1984.
The changes in managed liabilities at savings
and loans in early 1983 mirrored that of liquid
assets. Following the introduction of the
Increased liquidity
The growth in "cash and securities" over the
past several years also indicates that the relaxation of asset restrictions was not the only influence on the asset mix at thrifts. The bulk of
these assets are federal government or federally
sponsored agency securities, bank CDs and federal funds, which savings and loans were empowered to hold even before MCA. And, as
mentioned earlier, some of these securities can
17
Chart 2
Thrift Deposits
(quarterly)
Percent
Percent
35
54
30
52
25
50
20
48
15
46
10
44
5
42
0
40
~5
1978
1979
1980
1981
1982
thrifts over that for commercial banks was removed whenever the six-month Treasury bill
rate was 9 percent or higher. The impact of the
loss of the differential on the popular MMC is
illustrated in Chart 2. The purple line shows
that, after the loss of the differential on the
MMC, savings and loans and other thrifts lost
ground to commercial banks during the phaseout of deposit ceilings. Thrifts' share of total
deposits fell more or less steadily between mid1979 and the end of 1982, and the drop was
reflected in generally weak core deposit flows.
On balance then, the deregulation of deposit
interest rate ceilings, with its impact on flows
to core deposits, probably contributed to the
rise in the holdings of cash and securities at
savings and loans. However, the observation
that reliance on both liquid assets and managed
liabilities has increased, suggests that the increase in liquid assets at savings and loans probably reflected a higher demand of thrifts for
liquidity rather than only strong flows of smalldenomination deposits.
During the phase-out of deposit interest rate
ceilings, which was marked by the loss of the
bank/thrift differential on the popular MMC as
well as high and variable market interest rates,
the increased demand for liquid assets probably
was due to a deterioration in the outlook for
the stability and the overall availability of
small-denomination deposit balances at savings
and loans. The persistence of a relatively high
ratio of cash and securities to total assets more
recently may have two causes: a continued demand for liquidity in the face of the shortening
overall maturity of core deposits that has accompanied deposit deregulation, and/or the
greater amount of intermediation carried out
through savings and loans in recent years. II
1983
1984
38
MMDA, savings and loans ran off a considerable volume of managed liabilities. This is reflected in Table 1 as a decline in the ratio of
liabilities to total assets for 1983.
Ho,we~ver. the upward trend in savings and loan
reliance on managed liabilities before 1983,
which continued in 1984, suggests that thrifts
may not have been reacting only to strong core
deposit flows over the past several years. InChart 2 indicates that, from 1979 through
the growth of core deposits was relatively
weak despite the introduction of market-rate
deposit accounts.
One reason that core deposits did not perform "better" prior to 1983 is that, during the
phase-out of deposit ceilings, deregulation represented a two-edged sword for savings and
loans. The six-month money market certificate
(MMC) , for example, allowed thrifts to compete more effectively with issuers of nondeposit
instruments and dampened for a while the impact of higher market interest rates on flows to
thrifts. (This account was introduced in mid1978 and had a variable-ceiling indexed to the
six-month Treasury bill rate.) However, with
the other edge of the sword, the effectiveness
of the MMC as an instrument for thrifts to compete against commercial banks was reduced
considerably in March 1979. At that time, the
25 basis point differential on the ceiling rate for
Conclusion
The decline in the relative importance of
mortgages at savings and loans in recent years
has been the result of several factors in addition
to the provisions of the MCA. These include
the methods used by regulators to manage thrift
crises, increased equity investments in thrifts'
service corporations, and a dramatically
changed financial environment.
18
in financial markets, and will prclbablv
hold relatively more
assets.
however, earnings should ;tnnrr"rp
provement should reduce the Impetus to move
away from mortgage assets.
In the future, some savings institutions probably will further diversify given the virtually unlimited scope of activities now open to them.
They will be able to compete on a broader basis
II. Implications for the Mortgage
This section examines the implications that
the changes in savings and loan asset composition have for the mortgage market. The proposition that a link exists between the asset mix
of savings and loans and the allocation of credit
to housing is a variant of the one that ties the
volume of mortgage credit to deposit growth at
thrifts. Presumably, in the latter case, for a
given volume of total credit, the larger the
share of the funds channeled through thrifts,
the higher the proportion of credit allocated to
mortgages. If this were true, it follows that if
thrifts reduce their propensity to invest in mortgage-related assets, then, all else equal, a
smaller fraction of credit will go to mortgages
and mortgage rates will rise relative to other
market rates.
For deposit flows at thrifts and their mix of
assets to have an impact on the allocation of
credit to the mortgage market requires not only
some separation of the mortgage market from
the rest of the capital market, but also some
segmentation within the mortgage market itself. That is, changes in mortgage lending by
savings and loans, owing to developments specific to those institutions, must not be offset by
other lenders.
Some degree of separation in financial markets might be expected in the short-run if institutional arrangements for channeling funds
in the credit market are costly to adjust and the
market disruptions are viewed as only temporary. However, it seems reasonable to expect
that a permanent change in the propensity of
thrifts to extend mortgage loans would induce
adjustments by other lenders. This is particularly true given the increased importance of
mortgaged-backed securities. In evaluating the
impact of deposit interest rate ceilings, King
(1979) suggests that regulation of thrifts is likely
to affect the channels for mortgage credit rather
than the volume of such credit. This holds as
well for regulations affecting the cOlmp'OSJlticm
of assets at savings and loans.
The plausibility of the
that
participants in the capital market would
is only one reason that a changing asset
thrifts should not affect the allocation of credit.
The idea that the asset mix at thrifts affects
housing credit also is based on the qu,cs!ronablc
presumption that thrifts
substitute nonmortgage assets for mortgages. This presumption ignores the fact that asset
should be related to liability
and
the deregulation of
which to~~etl1er
feet the overall flow of funds to
and
loans.
In the previous section, it was
out
that deposit deregulation contributed to the rebound of savings institutions as intermediaries.
This has been
evident
couple of years, during which the
formance of savings and loans was tied
the
re-intermediation of small-denomination deposits foliowing the lifting of del)OSllt C(;:lllng:s.
The removal of deposit
lowered the
overall cost of deposits,
intermediation
more efficient. To the extent that funds acquired by thrifts had been allocated to nonmortgage uses, such as in commercial paper
held by money market mutual
the investment of those funds
thrifts in similar instruments would have no
on the allocation of credit.
In addition, as discussed
tion carried out by savings and loans in recent
years has been boosted
their
reliance on large-denomination
and
other nondeposit funds. This has been
ularly true in the past
of years. After
initial surge in small-denomination aeposlt
growth following the introduction of JVlJHL/I~.,.
19
FSLIC-insured savings institutions once again
picked up their issuance of managed liabilities.
Some institutions have been particularly aggressive in issuing large CDs, apparently as part
of a strategy to use liability management to increase asset growth. 12
As a result of stronger managed liabilities,
savings and loans have been able to extend a
large volume of mortgage credit and simultaneously increase their relative holdings of nonmortgage assets. In 1984, for example, their
mortgage holdings increased by about 15 1/2 percent and total assets expanded by almost 20 percent. Thus, since the changing mix of assets was
accompanied by rapid growth in assets, the
nonmortgage activity at thrifts has complemented, rather than substituted for, mortgage
lending.
Chart 3 provides evidence that is consistent
with the view that changes in the mix of assets
at FSLIC-insured savings institutions have not
affected the allocation of funds to mortgages.
The purple line in the chart represents the
quarterly change in mortgages at FSLIC-insured institutions as a percent of the change in
their assets, while the black line shows total
mortgages flows-that is, net extensions of
mortgages by all lenders, including households-as a share of private domestic nonfinancial borrowing.
The shaded region in the chart sets off the
period in which the shift to nonmortgage assets
at savings and loans was most pronounced.
During that period, the ratios of mortgages to
private domestic nonfinancial borrowing varied
but, on balance, tended to rise, not fall. The
movement of the ratio of total mortgage lending to private borrowing in the early 1980s appears to reflect changes in interest rates rather
than portfolio adjustments at savings institutions. The peak in the 1980 credit control period aside, the ratio of mortgages to private
borrowing fell in late 1980 and early 1981 as
market interest rates rose. The ratio remained
low, relative to the late 1970s, until the second
half of 1982 when market rates began falling
sharply.
As net mortgage flows at FSLIC-insured institutions (measured as a share of the change in
Chart 3
Share of Funds Allocated to Mortgages
(quarterly)
Percent
Percent
MeA
120
100
80
60
40
20
o
-20
-40
-60
80
-100
120
•
Mortgage Borrowing as a
Share of Total Private
Nonfinancial Borrowing
~
140 1..1-97-6 '&-19--77-'-19--7-81..1-97-9.&-L.19-80"""-'1981
1982
1983
1984
assets) stabilized between mid-1983 and the
third quarter of 1984, the ratios of total mortgages to the volume of aggregate private borrowing fell. The two ratios did decline in the
last quarter of 1984. However, on balance, it
does not appear that there has been a consistent
positive (or negative) relation between changes
in the relative allocation of funds to mortgages
by savings institutions and the share of aggregate borrowing accounted for by mortgages.
Another way of investigating the impact of
the change in the asset mix at savings institutions on the mortgage market is to examine the
behavior of mortgage interest rates. In keeping
with several past studies on the determination
of mortgage interest rates (see for example Jaffee and Rosen, 1979; Pyle, 1982; Anoako-Ada
and Ben-Zion, 1983), it is assumed that mortgage rates can be modeled as a partial adjustment process such that,
Rt
-
Rt -
I
=
X.(R t * - R t
I)'
(1)
In equation 1, R is the actual mortgage rate,
R* is the equilibrium mortgage rate, and X.
measures the speed at which the mortgage rate
adjusts to its equilibrium value. The equilibrium mortgage rate is assumed to be determined by the marginal cost of funds at savings
institutions (C). 13 For the purpose of this paper,
the marginal cost is taken to be the rate on a
lO-year Treasury bond.
20
itively related to the spread between the mortgage rate and the marginal cost of funds. This
positive relation is just the opposite of what
would be predicted under the "supply shock"
hypothesis being tested in equation 3. Under
that hypothesis, a greater allocation of funds to
mortgages would tend to narrow the spread between the mortgage rate and the marginal cost
of funds.
If both of these channels of influence come
into play (the mortgage rate being affected by
the flow of funds at savings and loans allocated
to mortgages and vice versa), a single equation
approach to estimating equation 3 would generate a biased estimate of 132' Accordingly, a
two-stage estimation approach is used. In the
first stage, an instrumental variable is derived
for M. 15 The second stage involves an ordinary
least squares estimation of equation 3 in which
the instrumental variable values for Mare
included.
The estimation results for equation 3 (with
the instrumental variables included) are reported in Table 2. 16 Equation I in the table is
estimated using the commitment rate on mortgages from a survey conducted by the U.S. Department of Housing and Urban Development
(HUD). In that equation, the estimated coefficient for M is not significantly different from
zero. This result does not support the hypoth-
To test whether changes in the composition
of assets at savings and loans affect the rate on
mortgages, the share of the flow of funds at
FSLIC-insured savings institutions allocated to
mortgages (M) is included as a determinant of
the equilibrium mortgage rate. Also,· to allow
for the possibility that the flow of funds to savings and loans has repercussions on the mortgage rate,the equilibrium mortgage rate is expressed as a function of the percent change in
small-denomination deposits at savings and
loans (D).14
With these assumptions, the change in the
mortgage rate can be expressed as a linear
function:
Rt
Rt - I =
A[ao + alC t + a2 M t + a3 D t
(2)
-
Rt
d
This can be restated in the standard regression
form:
R t = 130 + f3l C t + f32 M t
(3)
+ f33 D t+ f34 R t I + £t
Based on portfolio theory, the use of simple
regression analysis and equation 3 to investigate the relation between the mortgage rate and
the asset mix at savings and loans may be unsatisfactory. Within a simple portfolio model,
the fraction of funds allocated to mortgages by
savings and loans would be expected to be pos-
TABLE
2
Coefficients and Statistics for the Mortgage Rate Equation
(quarterly, 1978:2-1984:4)
Dependent
Variable
Independent Variables
Constant
Ct
Mt
Dt
Rt -
-2
1
R
SE
OW
p
0.32
( -1.60)
I. HUD
Commitment
Rate
1.26
0.57
(3.90)*
-0.11
( -0.14)
0.10
( -1.37)
0.45
(3.23)*
0.87
0.66
1.95
II. GNMA Rate
1.63
0.88
(15.05)*
-0.06
(-0.13)
-0.04
(- t.48)
0.08
(0.99)
0.99
0.23
1.92
t-statistics in parentheses.
*Significantly different from zero at the one percent level.
21
0.79
(6.54)*
ing the rate on GNMA securities as the dependent variable. The findings in equation II
indicate that the secondary mortgage market
rate is not influenced by changes in the asset
mix or the flow of funds at savings institutions.
One difference between the estimates for equations I and II is the more rapid adjustment of
the secondary mortgage market rate. This, of
course, is consistent with the secondary market
being more fully integrated with the rest of the
capital market.
From a theoretical perspective, in the longrun, adjustments within the capital market
would be expected to eliminate any potential
for an impact on the mortgage market stemming from a permanent change in the propensity of savings institutions to channel funds to
mortgage borrowers. Even in the short-run, to
the extent that asset restructuring by thrifts
came about as a result of an increase in the level
of intermediation at these institutions, the allocation of funds to the mortgage market would
not be affected. Indeed, the empirical evidence
is consistent with the view that the shift by savings institutions to holding a greater share of
their assets in non mortgage assets has not had
an effect on mortgage rates or the allocation of
funds to the mortgage market.
esis that
m the asset mIX at FSLICinsured institutions have had any significant
contt~mporarle()Us impact on the primary mortgage market interest rate in recent years. The
fm'dlllgs are confirmed when equation 3 is esvalues of M instead of
the values of the instrumental variable. 17
The results for
I in Table 2 also
the estimated coefficient for D is not
statistically different from zero at the conventional levels of significance, although the t-statistic for the coefficient for D is larger than that
M. This
suggests that, in the primary
market, the growth rate of
small-denomination deposits at savings institutions has not had an impact on mortgage rates
in recent years. Jaffee and Rosen (1979), in
contrast, showed that the ratio of the change in
the level of
and loan deposits to the
value of new single-family homes had a negative and
significant relation to interest rates in the
mortgage market
to 1979. The evidence in Table 2 is consistent with the view that financial markets have
over time. 19
become more
EquatIOn II in Table 2 tests for the impact of
"".lnl.. l" shocks" at savings institutions on intermortgage market usest rates in the
III. Conclusion
tors in financial markets. They also will change
the operation of the mortgage market. For example, there is an ever-growing tendency toward the use of mortgage-backed securities.
Greater diversification does not, however, appear to have significantly altered the flow of
funds to the mortgage market or the relation
between mortgage rates and other market
rates. In part, the greater interconnection of
deposit and mortgage markets with money and
capital markets probably has muted any potential impact stemming frem asset changes at
thrifts. Also, given the exceptionally rapid
growth of savings and loan assets in the past
two years, it is likely that the nonmortgage activityat savings and loans has been a complement to, rather than a substitute for, their traditional mortgage lending.
In recent years, savings and loans have been
allowed to venture to a greater extent into nonrnr,rt'T'H'0 activities. Since 1980, their new pow,""uunnu,""u with poor earnings have encourdiversification in their asset
portfolios, thereby decreasing the relative role
of mortgage-related assets in their portfolios.
the relaxing of asset restrictions does
not appear to be the only stimulus to thrifts
Se(;kIng arr,,,t,'r diversification. Changes affectliabilities likely also have influenced the
cOlnposItlon of
and loan assets. In the
ear'nillgs improve, the tax incentives
have made mortgage lending
attractive to thrifts will reassert
themselves.
The initiatives taken by savings and loans to
balance their portfolios have important implications for their survival as effective competi22
FOOTNOTES
13. A number of studies have examined the issue of
whether mortgage interest rates are determined by marginal cost or average cost: Jaffee and Rosen, 1979; Pyle,
1982; Anoako-Adu and Ben-Zion, 1983; and Mayer and
Nathan; 1983. There. is· little dispute over the fact thi'lt,. on
theoretical grounds, marginal cost pricing is the preferable
approach for modeling the behavor of financial institutions.
However, the empirical evidence is mixed. The average
cost of funds (or deposits) at mortgage lending institutions
has. b/:len found to be significant in explaining mortgage
interest rates when some measures of the marginal cost
of funds, but not others, are used in mortgage rate regressions. Nevertheless, on balance, the emprical evid/:lnceindicates that,of the two depictions of behavior, marginal
cost pricing is more appropriate.
1. Throughout the paper, the term "savings and loan associations" refers to all savings institutions insured by the
Federal Savings and Loan Insurance Corporation (FSLlC),
which includes both savings and loans and certain savings
banks.
2. At another level, there is the worry that increased nonmortgage investments would expose the Federal Savings
and Loan Insurance Corporation to greater risk. There also
is concern that, if savings and loans were to shed their
traditional role as mortgage l/:lnders, they would be subject
to the sarne regulations that apply to banks and bank holding companies. Such regulations generally are more stringent than those forthrifts and.. their holding compani E3 s.
3. See Guide to Federal Income Taxes for Savings
Institutions.
4. Depository institutions that do not meet the thrift test
can make tax-sheltered contributions to loan loss reserves
that are based on actual losses incurred in the past.
14. Since the testis whether exogenous shocks to the flow
of funds at savings and loans affect the mortgage rate, it
is more appropriate to use the small-denomination deposits
than some broader measure of liabilities over which these
thrifts have greater control.
5. The Garn-St Germain Act of 1982 also provides for
some additional mortgage powers. For a description, see
Federal Reserve Bank of Chicago, Leveling the Playing
Field, A Review of the OIDMCA of 1980 and the Gam-St
Germain Act of 1982.
15. The instrumental variable for M is derived from an
equation with the marginal cost of funds, the lagged mortgage rate, the return on assets at FSLlC-insured institutions, the lagged ratio of the stock of mortgages to assets
at FSLlC-insured institutions, and the percent change in
total financial assets included as the right-hand-side variables. The adjusted R2 for this estimated equation was
6. For a discussion of these powers and those given to
federally chartered savings banks under MCA, see Federal
Reserve Bank of Chicago, Ibid.
0.77.
7. The behavior of savings banks not insured by the FSLlC
has been different from that of the FSLlC-insured savings
institutions. The former markedly increased the proportion
of assets held in nonmortgage loans (see Mahoney, Patrick
I. and Alice P. White. "The Thrift Industry in Transition."
Federal Reserve Bulletin, March 1985, pp. 137-156).
16. To control for the possible effects of the 1980 credit
control period on the constant term, equation 3 also was
estimated using a bivariate (0,1) dummy for the 1980:2 to
1980:3 period. The coefficient for this variable was not significantly different from zero, and the variable was not included in the estimations reported in Table 2.
8. Savings and loans also can engage in nonmortgage
activities through service corporations. The activities of
such subsidiaries are not reflected in the data shown in
Table 1.
17. Based on the discussion in Section I, the composition
of savings and loan assets would tend to be tied to core
deposit flows. Given the potential for the interrelation between asset and liability management to affect the statistical findings regarding the relation of M to the mortgage
rate, equation 3 was estimated with the variable D excluded. However, the estimated coefficient for M still was
not significantly different from zero when either the actual
or the instrumental values for M were used in the
estimation.
9. In addition to the lifting of deposit ceilings, the sharp
drop in interest rates in the second half of 1982 likely was
a crucial factor in the revival of thrift deposit flows.
10. For a discussion of the changes in assets and liabilities
at thrift institutions and commercial banks brought on by
the introduction of the money market deposit account, see
Furlong (1983).
18. In keeping with the comment in the previous footnote,
equation 3 was estimated with the variable M excluded.
The findings regarding the impact of D on the mortgage
rate were not materially changed.
11. The highly liquid MMDA, which by far is the most popular of the deregulated deposit accounts, allows up to six
automatic transfers per month (up to three of these by
check) and an unlimited number of withdrawals when they
are made in person. The overall maturity of deposits at
savings and loans also has been shortened as a result of
the introduction of nationwide NOW accounts in 1981.
NOW accounts are fully transactional.
It is also possible that savings and loans do attempt to
manage small-denomination deposits to some degree.
Consequently, the growth rate of small-denomination deposits may be affected by the mortgage rate given the
opportunity cost. For example, if mortgage rates for some
reason were high relative to other market rates, savings
and loans might attempt to attract a larger volume of smalldenomination deposits. If this were the case, 0 would not
be independent of the error term in equation 3. Accordingly,
equation 3 was estimated using an instrumental variable
approach similar to that used for M. In this case, the coefficient for D once again was not significantly different from
zero.
12. Keeley (1984) points out that deposit deregulation affected the liability structure of commercial banks by causing the substitution of smaller-denomination deposits for
large certificates of deposits. For savings and loans, deregulation may have reduced their comparative advantage
in attracting small-denomination deposits. This lost comparative advantage may account for some of their increased reliance on large CDs.
23
19. The conclusions regarding the relation between mortgage rates and small-denomination deposit flows at savings and loans have to be tempered some, based on evidence not shown in Table 2. A series on commitment rates
at savings and loans is available from the Federal Home
Loan Bank Board (FHLBB). This series was not used in
Table 2 because the FHLBB used interest rates on both
fixed and variable-rate mortgages through September
1983. The HUD series is based on data for fixed-rate loans.
When equation 3 is estimated using the FHLBB series, the
results concerning the relation between Rand M are essentially the same as those reported using the HUD series.
However, when either the actual or the instrumental variable values for M and D are used, the growth rate in smalldenomination deposits has a small negative impact on the
mortgage rate, and the effect is statistically significant. The
problem is that it is unclear to what extent the mixing of
variable- and fixed-rate yields accounts for these results.
REFERENCES
Anoako-Adu, Ben and Uri Ben-Zion. "Deposit Costs and
Mortgage Rates: American and Canadian Empirical
Evidence." Housing Finance Review, January 1983.
Keeley, Michael C. "Interest Rate Deregulation," Weekly
Letter. San Francisco, CA: Federal Reserve Bank of
San Francisco, January 13,1984.
Federal Reserve Bank of Chicago, Leveling the Playing
Field, A Review of DIDMCA of 1980 and the Garn-St
Germain Act of 1982.
King, Frank B. "Deposit Flows and The Supply of Mortgage
Credit: Are They Related Anymore?", Economic Review. Atlanta, GA: Federal Reserve Bank of Atlanta,
May/June 1975.
Furlong, Frederick 1. "New Deposit Instruments." Federal
Reserve Bulletin, vol. 69 (May 1983).
Guide to Federal Income Taxes for Savings Institutions,
Ernst and Whinney, 1982.
Mahoney, Patrick I. and Alice P. White. "The Thrift Industry
in Transition," Federal Reserve Bulletin, vol. 71 (March
1985).
Jaffee, Dwight M. and Kenneth F. Rosen. "Mortgage Credit
Availability and Residential Construction." Brookings
Papers on Economic Activity, No.2, 1979.
Mayer, Thomas and Harold Nathan. "Mortgage Rates and
Regulation Q," Journal of Money Credit and Banking,
February 1983.
Pyle, David P. "Deposit Costs and Mortgage Rates," Housing Finance Review, January 1982.
24
Determining Geographic Markets for
D.ep.osit Com.petition in Banking
Michael C. Keeley
and
Gary C. Zimmerman*
This article provides empirical evidence on the geographic extent
of the markets for money market deposit accounts (MMDAs) and
Super NOW accounts. Three tests focusing on deposit interest rates
were used: an analysis of the cross-sectional variance of rates within
as compared to among regions, an analysis of the correlations of
rates over time within compared to among regions, and a test of
the structure-performance hypothesis using concentration indexes
measured with different market geographies.
For the MMDA, no evidence of local markets is found, although
all three tests suggest that markets for this account are no larger
than states. For the Super NOVY, we find evidence of both statewide
and local markets, although there is apparently a much higher degree of competition among the local markets than among the states.
Thus, knowing the geographic extent of the
markets in which banks compete is useful information for the analysis of banking.
We analyze the geographic extent of the markets for money market deposit accounts
(MMDAs) and Super NOWs, two liquid market-return deposit accounts offered by banks
and thrifts, which now account for about 21 and
2 percent of total domestic deposits, respectively. Although several different empirical
methods are used, all focus on deposit interest
rates (prices) to define the markets for these
two accounts. Until recently, such an approach
was problematic because deposit-rate regulation resulted in (more or less) uniform rates,
making interest rate comparisons meaningless. 1
However, now that almost all deposit-rate ceilings have been removed and time-series data
on rates at different banks are available, such
a study is possible.
This paper is organized as follows. In Section
I, a brief review of the theoretical definition of
an economic market is provided along with a
In this paper, we provide empirical evidence
on the extent of the geographic markets in
which competition for banking deposits takes
place. This evidence is important for several
reasons. First, for antitrust purposes, the competitive effects of proposed bank mergers must
be assessed and this cannot be done without
knowing the geographic markets for deposits,
loans, and other services that banks provide. In
particular, the scope of the geographic market
is of paramount importance in determining
whether a particular proposed merger will have
anticompetitive effects. Second, at a more fundamentallevel, market definition is at the core
of economic theory. No economic phenomenon
can be properly analyzed without first determining the market in which it takes place.
*Senior Economist and Economist, respectively, Federal Reserve Bank of San Francisco.
Research assistance from Joni Whitmore and
Maureen O'Byrne and comments from the review committee are much appreciated.
25
discussion of the empirical implications of the
theory for actually delineating markets. Section
II describes our empirical tests and results. Fi-
nally, Section III presents the summary and
conclusions.
I. The Theoretical Definition ofaMarkefanditsMeasurernent
A geographic market is a region in which
suppliers and demanders trade and thereby determine prices and quantities. A literal interpretation of this definition would imply that in
a given market there is a uniform price. However, in virtually all noncentralized exchanges,
goods trade simultaneously at slightly different
prices. Part of the reason is that various characteristics (for example, quality) of goods differ
and part is because of transportation, transaction and information (search) costs.
A more practical definition of a market
might include all suppliers and demanders that
determine price. For example, if for a buyer at
location A, suppliers at locations Band C were
equally good substitutes, then locations A, B
and C would be in the same market. This definition suggests a procedure for assessing
whether a particular supplier was in a particular
geographic market. One would analyze
whether the demanders in the market found the
supplier to be a good substitute for other suppliers in the market. Similarly, in determining
whether a particular demander was in the market, one would analyze whether suppliers in the
market found that demander to be a good substitute for other demanders in the market.
Thus, both demand and supply "substitutability" play key roles in defining markets. This
means that to determine the boundaries of a
market, one could continue to expand the market geographically, including more suppliers
and more demanders, until there was a significant discrete fall in both demand-side and supply-side substitutability;
As this definition suggests, there is no fixed
a priori condition determining the geographic
extent of a market. In some cases, demand- and
supply-side substitutability may gradually diminish as distance from the center of a market
increases. In other cases, there may be more
than one discrete decline. Thus, a particular
geographic area may be somewhat isolated
from another even though there is a significant
(but not infinite) cross-elasticity of supply or
demand between the two areas.
In applying these concepts of market definition to the deposit market, depository institutions (SUCh as banks, savings and loans, and
credit unions) may be considered to be demanders of deposits, and individuals, governments and firms, suppliers of deposits. 2 For
some types of deposits (such as those with a
large transaction service component), a depositor may consider only depositories within a
small region to be good substitutes. 3 That is,
the supply of these types of deposits may be
local. However, as the above discussion implies, a local supply of deposits alone does not
mean the deposit market necessarily is local
since one needs to consider demand-side substitutability as well. For example, entry and the
threat of entry by depository institutions not
currently in the area, entry of nondepository
institutions offering substitute services, or competition by institutions on the border of a region
may effectively make the market much larger.
As discussed in the introduction, a key policy
reason for interest in the scope of deposit markets is concern about the competitive effects of
mergers and acquisitions on deposit competition. That is, without adequate competition,
firms may be able to exert monopsony power
and thereby pay below-competitive rates on deposits (and/or provide below-competitive levels
of deposit services). The potential degree of
monopsony power of a group of depository institutions (acting to maximize profits jointly)
depends (inversely) on the elasticity of supply
of deposits facing them. 4
The elasticity of supply of deposits facing a
group of firms in turn depends directly on the
elasticity of supply of their actual and potential
depositors and inversely on the elasticity of de-
26
held, there would be no significant geographic
differences in deposit rates.
mand by other firms for those depositors' deposits. Thus, this elasticity is determined by the
same supply and demand substitutability factors determining the market for deposits.
Moreover, supply and demand elasticities,
which are at the heart of market definition, also
determine the actual market power of a group
of colluding firms as well as the potential gains
from collusion. In particular, if the elasticity of
supply of deposits facing a group of firms is
very high, then these firms do not constitute a
separate market nor do they have the potential
to gain from collusion by paying below-competitive rates. 5
In considering the demand-side elasticities
that determine geographic markets, one needs
to account for the fact that the demand for deposits is primarily a factor demand (to produce
loans). It is possible, however, for the loan and
deposit markets to have different geographic
scopes. For example, suppose the loan market
were national (or even international) in scope.
Then, for each individual bank, the loan rate
would be fixed and determined exogenously.
However, if depositors found it economically
infeasible to make deposits outside their local
areas and depositories found it infeasible to relocate in order to attract deposits from areas
other than their current location, then deposit
markets would be local. If some local areas
were characterized by monopsony power, or if
other factor costs (labor, land, etc.) differed,
then deposit rates could differ among localities.
Thus, significant geographic differences in deposit rates would be evidence of local deposit
markets even if there were no geographic differences in loan rates.
However, if all other factor costs were identical and if all deposit markets were competitive, then a national loan market would result
in uniform deposit rates nationwide. This is because the value of the marginal product of deposits (in producing loans) would be equated
to the rate paid on deposits (at the bank level)
to maximize profits. Because the value of the
marginal product of deposits would be the same
in all markets, the rate paid on deposits would
be the same in all markets. If such conditions
Empirical Tests
If demand or supply cross-elasticities be-
tween two geographic areas were high, then
prices in the areas would be similar. This means
that differences in prices between two areas is
strong evidence that the areas are not in the
same markets. That is, significant differences
in deposit rates could persist in two areas only
if they were in separate markets. There are,
however, several difficulties in implementing
this test empirically.
First, the data we have contains a measure of
only the pecuniary deposit rate; the implicit service flow, that is, quality of service, is not observed. We may therefore observe differences
in pecuniary deposit rates even though there
are no differences in the total (pecuniary plus
nonpecuniary) deposit rate or vice versa. This
problem is likely to be much more important
for the Super NOW account than the MMDA
because the Super NOW's unlimited checking
feature means that it will be more widely used
for transaction purposes than the limited checking MMDA. In other words, the (unmeasured)
service flow from the Super NOW is likely to
be much larger than that from the MMDA.
Second, even pecuniary deposit rates are
measured with error (due to differences in compounding, tiered rate structures, reporting errors, or differences in required minimum balances).6 This too could lead to differences in
measured deposit rates when none exist. Finally, we would expect to find some dispersion
of true total deposit rates even within a market. 7 This is because information about deposit
rates (or any retail price) is costly for depositors
to obtain. In fact, significant dispersions of the
prices of virtually all retail goods are observed
within markets although, as Stigler (1961)
found, the dispersion is smaller for goods for
which search costs are lower.
All three factors suggest that measured deposit rates have a stochastic component and
therefore that the appropriate test to determine
the geographic scope of a market is to analyze
27
supply functions would likely have different
elasticities in different markets and this would
lead to less highly correlated differences in
rates in different markets than in the same
market.
Finally, rates may also vary over time due to
shifts in the supply of deposits. Since supply
shifts in different markets would not be perfectly correlated, this too would lead to a higher
correlation of rates over time within markets
than among markets. Thus, significant differences in the correlations of deposit rates within
and among geographic areas can exist only if
those geographic areas are separate markets.
A third approach to market definition is
based on the structure-performance hypothesis.
This hypothesis holds that there is less competition in more concentrated markets, presumably because collusion is easier in more concentrated markets. Thus, we should observe banks
in concentrated deposit markets paying lower
deposit rates. This relationship can be used to
delineate markets by testing the strength of
the relationship under different market definitions. Presumably, if a market were defined
properly, the predicted relationship between
market structure and performance would be
stronger than if a market were defined improperly. The usefulness of this test, however, depends on the validity of the structure-performance hypothesis. 8
Although other tests for defining geographic
markets have been suggested, many have serious flaws. 9 For example, some have suggested
analysis of shipment flows. Although two areas
that do have significant shipments between
them are likely to be in the same market, areas
with no shipments between them also may be
in the same market. For example, if there were
no shipments between locations A and B, but
a large number of commonly located buyers in
location C are receiving significant shipments
from A and B, those buyers will tend to force
prices in A and B to identical levels. Any price
differential between A and B would cause the
buyers in location C to shift all their purchases
to the area with the lower price. This would
tend to drive down the higher price and raise
the lower price until equality is restored.
statistically the vanations in rates within as
compared to across areas. Within a market,
rates should vary less than across markets. Similarly, statistical tests can be used to determine
whether differences in the average rates in two
areas are due to chance.
As long as the error in the measured deposit
rate is uncorrelated with the geographic measure of the market being used, standard analysis
of variance techniques will be unbiased. It is
likely that measurement errors of pecuniary deposit rates are independent of geography. However, quality (implicit service flows) may depend on geography both because of differences
in competition as well as differences in the costs
of providing quality. Similarly, search costs may
be different in different areas because of differences in the cost of time or the quality of
transportation services. Analyses of the differences in the level of deposit rates in different
areas therefore could be biased. However, neither search costs nor quality are likely to vary
over short periods of time, at least relative to
the variation in deposit rates. This suggests that
another way to measure the geographic extent
of a market is to analyze correlations of rates
over time.
Rates within a given geographic market
should be highly correlated with one another
over time and should be more highly correlated
with one another than with rates in other geographic markets. This is because shifts in supply
or demand in a market will have similar effects
on all prices in a given market but will have less
of an effect on prices in other markets.
However, deposit rates might be highly correlated with one another in truly different geographic deposit markets if the loan market were
national. This is because movements in loan
rates, and hence the demand for deposits,
would be common in different deposit markets.
Even so, rates within markets should be more
highly correlated with each other than with
rates in different markets. For one thing, deposit supply conditions might differ in different
markets due to differences in competition. For
example, in a monopsonistic market, rates
would vary less than in a competitive market
with a similar supply of deposits. Moreover,
28
Another widely used method of defining
markets is to delineate the customers of a business in the so-called service area. The concept
of using service areas is flawed for the same
reason as the shipment-analysis method. It may
be true that all consumers shop within only a
few miles of home, but a large metropolitan
area will be integrated into one large market
because of the existence of consumers on the
margins between service areas.
on deposits at all branches and this suggests that
even if there were differences in the degree of
competition in local markets, banks do not find
it worthwhile or possible to exploit them bydifferences in explicit pricing. One reason it may
not be worthwhile to pay different rates at .differel1t branches is that a depositor could then
open an account at the branch with the highest
rate but still receive deposit and transaction services at the most convenient branch. 10
Uniform pricing by several of the large banks
with branches in virtually all local areas in a
state makes it inopportune for other banks to
price differently. However, since branching
across state lines is not currently permitted, and
since entry may not be fully market-determined, markets in different states may be somewhat insulated from one another.
What We Expected
Most previous analyses (see Heggestad,
1979) of competition in retail banking have assumed that the relevant market was local. However, there are reasons, at least in states that
permit branching, why competition may take
place in statewide markets. Virtually all multiple-branch banks in the West pay common rates
II. Empirical Analysis
Data on the geographic locations in which
banks have branches and market concentration
come from the Federal Deposit Insurance Corporation's (FDIC's) June 1983 Summary of Deposits Tape.
Our empirical analysis of the scope of geographic markets for bank deposits uses data on
two different deposit categories: Money Market
Deposit Accounts (MMDAs) and Super NOW
Accounts. These accounts are well-suited to our
study because both have been free of interest
rate ceilings since their introductions on December 14, 1982 and January 5, 1983, respectively. Also, they provide an interesting comparison of a transaction account (the Super
NOW) to a liquid savings account (the
MMDA).
These data have several limitations. First,
banks report only the most common interest
rates paid on the largest dollar volume of deposits (of a given type) issued during the sevenday period ending on the last Wednesday of the
month. II Second, deposit rates are reported for
banks, not branches. However, as mentioned
above, we have verified that these banks did
not offer different deposit rates at different
In this section, we use the first three empirical methods described in the previous section
(analysis of the levels of rates, correlations of
rates over time, and the structure-performance
hypothesis) to provide evidence about the
scope of geographic deposit markets in the
West. It should be emphasized that we are only
analyzing deposit markets and that loan markets may well have different geographic scopes.
Further, the markets for different types of deposits may well have different geographic
scopes depending, for example, on their transaction service component.
We do not attempt to determine actual deposit markets, rather, we use the data to determine if there is evidence of statewide markets
and/or local markets. Local markets are defined as either counties or Rand McNally Metropolitan Areas (RMAs) because such local
market definitions are most commonly accepted as valid and because data defining these
markets are readily available.
The data for our study are from a monthly
Federal Reserve survey (FR2042) of interest
rates and deposit quantities at 59 different
banks in the Twelfth Federal Reserve District.
29
month). However, in the synthetic data set,
there is only one observation for each bank in
each county (or RMA) regardless of the num
ber of branches that bank has in a county (or
RMA).
In Chart 1, we present evidence that the
mean rates on MMDAs (across banks) within
each state differ fairly substantially across the
states in our sample (Nevada is excluded be
cause our sample contains only one bank in that
state). These differences in means suggest that
different states are in different markets since if
the states were in the same market, rates would
be more similar.14 Hawaii, especially, appears
to be in a different market since MMDA rates
there are very different from the rates in other
states in our sample.
In Chart 2, we present a similar plot of mean
Super NOW rates by state. For Super NOWs,
differences among the states are even more pro
nounced, both in terms of the levels of the rates
and their time patterns. Although differences
in the levels of the rates might be explained by
differences in the levels of fees or nonpriced
services, the dramatic differences in the time
pattern of the rates cannot be explained by
these factors because fees and nonpriced ser
vices do not vary rapidly over time.
branches. Third, the sample size is relatively
small. Only in California, in which we have 29
banks, do we have a relatively large sample
size.12
In the statistical analysis that follows, we not
only use survey observations directly, but we
also use a synthetic data base to test for local
markets. The basic unit of observation from the
survey is a deposit rate of a bank in a month.
By combining this bank rate information with
structural data (from the FDIC’s 1983 Summary
of Deposits Tape) on the location of banks’
branches, it is possible to create a synthetic data
set.
This synthetic data base contains observa
tions on the rates each bank pays in each local
geographic “market” area where the bank has
a branch. One data base is created for RMAs
and another is created for all counties including
counties in RMAs. Such synthetic data bases
can be created since each bank pays the same
rate at all its branches.13
In some of the analysis that follows, the bank
itself is the unit of observation (that is, one ob
servation per bank per month). In other anal
yses, the synthetic data are used to make banks
in counties (or RMAs) the unit of analysis (one
observation per bank per county, or RMA, per
Chart 1
Mean MMDA Rates by State
Chart 2
Mean Super NOW Rates by State
Percent
Percent
30
= b 7 = O. That is, we should be able to reject
the hypothesis that there are no statistically significant differences among the states in the
rates paid on given deposit types. Conversely,
significant differences among the states means
that variances within the states are lower than
the overall variance of rates across states and
suggests that deposit markets are no larger than
states.
The results of such tests are presented in Table 1. For both deposit types, we can reject the
hypothesis at the 1 percent level or better that
the rates do not depend on state. 16 Time also
has a significant influence on rates. This suggests that some common factor across all states
is influencing either the supply or demand for
deposits or both. A likely source of this common movement would be common movements
in the demand for deposits due to a common
movement in the demand for loans. This result,
however, also might be due to nationwide competition from the money funds for MMDA deposits. A study by Keeley and Zimmerman
(1985) finds that the short-run cross-elasticity
between MMDA deposits and the money fund
rate is small but statistically significant, and that
the long-run cross-elasticity is large. Thus, nationwide movements in money fund rates could
explain some of this common movement in
MMDA rates over time.
These regression results confirm that state is
a much more powerful explanatory factor for
Super NOWs (where it explains 59 percent of
the variance) than for MMDAs (where it explains 9 percent of the variance). Similarly,
these regressions indicate that common factors
varying over time are much more important for
the MMDA than the Super NOW. (Time explains 61 percent of the variance of MMDA
rates but only 9 percent of the variance of Super
NOW rates.)
The magnitude of the estimated state differences for MMDAs is fairly large, with a maximum difference of 83 basis points between Hawaii and Utah. For Super NOWs, interstate
differences in rates are staggering, with a maximum difference of 231 basis points between
Nevada and Utah. These very large estimated
differences in rates among states suggest very
Comparisons of the level of Rates
To determine whether the differences in
banks' deposit rates among the states are statistically significant, we analyzed the variances
of the rates across banks in different states.
Much like the plots in Charts 1 and 2, the idea
underlying this comparison is that the prices of
competitors within a particular market should
be more similar than prices across markets.
Thus, if the states do, in fact, represent markets
at any moment in time, the variance in rates
across banks within each state should be much
lower than the overall variance of rates across
banks in all states. However, if the markets
were smaller geographic areas than states and
if these local markets were interconnected, then
variances within states might still be lower than
the overall variance across states. Thus\, a finding of significant state differences would mean
that markets were no larger than states and that
cross elasticities between states were lower than
within states, but it would not necessarily mean
that cross elasticities between local areas (such
as RMAs or counties) were not also lower than
cross elasticities within counties or RMAs.
The analysis-of-variance model used to test
for state differences is:
R it
=
a + b1S lit +
+ a1T lit +
+ b 7S7it
+ aNTNit+Eit
(1)
where:
Rit
Sj,
Tj,
, S7
, TN
the rate paid on
deposits (of a given
type) by bank i
at time t
state dummy variables
Monthly time dummy
variables
parameters to be
estimated
random error term.
In this model, the variance in the rates paid
by individual banks on a given deposit type is
decomposed additively into the variance due to
state and time. IS Thus, in this analysis, a bank
in a month is the unit of observation. If the
states were in separate markets, we should be
able to reject the null hypothesis that b l = . . .
31
TABLE
1
Statistical Tests of Differences in Banks'Rates Across States: Bank-level Data
(Standard Errors in Parentheses)
MMDA Rate (in basis points)
Number of Observations
Minimum of Dependent Variable
Maximum of Dependent Variable
Mean of Dependent Variable
R2
1475
725
1300
852
.71
State Coefficients (California is the omitted state)
AZ
7*
(3)
HI
-66***
(4)
NV
- 55***
(7)
ID
-19***
(4)
F-test for state differences = 65***
(% of Variance Explained by State
=
OR
-10***
(3)
UT
17***
(4)
WA
-15***
(3)
9%)
F-test for time differences = 126***
(% of Variance Explained by Time = 61%)
Super NOW Rate (in basis points)
Number of Observations
Minimum of Dependent Variable
Maximum of Dependent Variable
Mean of Dependent Variable
R2
1334
552
975
704
.69
State Coefficients (California is the omitted state)
AZ
9***
(4)
HI
- 15***
(4)
----
NV
-110***
(7)
ID
30***
(4)
F-test for state differences = 354***
(% of Variance Explained by State = 59%)
F-test for time differences = 17***
(% of Variance Explained by Time
=
9%)
***Significant at the 1% level
**Significant at the 5% level
*Significant at the 10% level
32
OR
-64***
(4)
UT
121 ***
(4)
WA
- 83***
(3)
strongly that Super NOW deposit markets are
not larger than states.
Similar tests also were performed to determine if there are significant differences across
counties (or RMAs) in deposit rates. In these
tests, we used our synthetic data base in which
the unit of observation is the rate paid by a
given bank in a county (or RMA) in a given
month. The data from all the states is pooled,
and the model estimated is:
+ b]Shjt + . . . + b7S7ijt
+ 'Y]C 1ijt +
+ 'YMC Mijt
+ ajTjijt +
anTnijt + E ijt
a
where:
R ijt
S],
T],
Cj,
, S7
, Tn
, CM
are provided in local markets since the Super
NOW has a much higher transaction service
component than the MMDA. Because a large
transaction service component is likely to be
associated with a more local supply of deposits,
it would not be surprising to find that Super
NOW deposit markets were local while MMDA
markets were statewide.
However, the. percentage of the variance of
Super NOW rates explained by RMA or county
is about 1I20th of that explained by state. Thus,
the local differences in rates are generally much
smaller than interstate differences. Further, the
largest estimated difference in Super NOW
rates between two RMAs after controlling for
state effects is only 37 basis points, a small difference compared to the over 200 basis point
maxiumum difference found between two
states. This suggests that cross-elasticities
among counties or RMAs are much larger than
among states.
To a certain extent, the results in Table 2 are
dominated by large banks with numerous
branches. Since in the synthetic data base each
large bank contributes many observations with
identical rates (in any given month), such a
large number of identical rates virtually guarantees that there will not be large estimated
differences in rates among local areas within a
state. To determine how sensitive our results in
Table 2 are to the inclusion of large, multibranch banks, we reestimated the model
(Equation 2) for California only, both with and
without the 5 largest California banks.
As expected for the MMDA, estimated mean
inter-RMA differences in rates are somewhat
larger when the 5 largest banks are excluded.
Further, we can reject the hypothesis that rates
do not differ among the RMAs at the 1 percent
level. However, whereas the largest difference
in rates betwen two RMAs is 25 basis points,
most of the estimated differences are very small
and most inter-RMA differences are not significant (the results are essentially driven by one
RMA).
Furthermore, when we perform the same
analysis at the county level, we cannot reject
the null hypothesis of no differences in MMDA
rates among counties. Thus, at the county level,
(2)
the rate paid on
deposits (of a given
type) by bank i in
county j (or RMA j) at
time t.
state dummy variables
time dummy variables
county (or RMA)
dummy variables
parameters to be
estimated
a random error term.
The results of these regressions, reported in
Table 2, show that for the MMDA, we cannot
reject the hypothesis that rates do not differ
across RMAs or counties once we control for
state differences. Thus, for the MMDA, this
test provides no evidence of local markets.
In these regressions, state explains a much
smaller percent of the overall variance than in
the bank-level regressions because a much
larger proportion of the observations in the synthetic data base are in California. However, the
estimated state differences are still significant
at the 1 percent level and are approximately the
same magnitude as those reported in Table 1.
Thus, these results also suggest that MMDA
deposit markets are not larger than states.
For Super NOWs, we can reject at the 1 percent level the null hypothesis of no local differences in rates. Thus, for the Super NOW, there
is evidence of local markets. This result is consistent with the notion that transaction services
33
TABLE
2
Statistical Tests of·State, RMA, and County Differences: Synthetic Data
(Standard Errors in Parentheses)
MMDARate (in basis points)
RMA DATA
77***
1%
F-Tests
% of Variance
RMA
TIME
.54
0%
1342***
80%
7750
725
1300
857
.81
Number of Observations
Minimum of Dependent Variable
Maximum of Dependent Variable
Mean of Dependent Variable
R2
State Coefficients
AZ
7**
(3)
HI
- 66***
(4)
ID
-17***
(4)
NV
-55***
(6)
OR
11 ***
(3)
------
UT
6
(4)
WA
-5
(4)
COUNTY DATA
F-Tests
% of Variance
STATE
COUNTY
TIME
60***
1%
.83
0%
2004***
71%
19050
725
1300
854
.73
Number of Observations
Minimum of Dependent Variable
Maximum of Dependent Variable
Mean of Dependent Variable
R2
State Coefficients
5*
HI
65***
(3)
(4)
AZ
ID
-17***
NV
-54***
OR
-20***
---
UT
WA
._,,--------
3
-5
(4)
(7)
(5)
(7)
(4)
34
Super NOW Rate (in basis points)
RMA DATA
F-Tests
%of Variance
Number of Observations
Minimum of Dependent Variable
Maximum of Dependent Variable
Mean of Dependent Variable
R2
STATE
RMA
439***
19%
5***
1%
TIME
233***
34%
7322
552
975
700
.73
State Coefficients
AZ
-10***
(3)
HI
-15***
(4)
NV
-111 ***
(6)
30***
(4)
- OR
--93***
(4)
UT
124***
(4)
WA
-93***
(4)
COUNTY DATA
F-Tests
% of Variance
Number of Observations
Minimum of Dependent Variable
Maximum of Dependent Variable
Mean of Dependent Variable
R2
STATE
COUNTY
TIME
219***
7%
3***
3%
271 ***
30%
18044
552
975
694
.75
State Coefficients
AZ
-15***
(3)
HI
-16***
(4)
ID
29***
(4)
NV
-112***
(7)
***Significant at the 1% level
**Significant at the 5% level
*Significant at the 10% level
35
OR
-110***
(5)
UT
118***
(7)
WA
-70***
(4)
the MMDA results do not depend upon the inclusion of the five largest banks. This means
that there is no evidence of local markets for
MMDAs using county data even when the 5
largest banks are excluded. However, if the 5
la.rgest banks were not in almost all local areas
and paying uniform statewide rates, local areas
might indeed be more insulated from one
another.
The results for the Super NOW are similar.
They show larger, statistically significant, inter:
RMA (and inter-county) differences in California and a doubling from one to two percent of
the percentage of variance explained by RMA
when the five largest banks are excluded. However, for the Super NOW, the maximum difference in rates between RMAs is only 40 basis
points (25 basis points between counties). This
is very small compared to the inter-state differences. Thus, the five largest banks do not appear to be driving these results.
To summarize the results of Tables 1 and 2,
we find no significant differences in MMDA
rates among counties or RMAs, but we do find
significant differences among states. Thus,
there is evidence that the state and not the
RMA or county is the market in which competition for MMDAs takes place. For the Super
NOW, there are significant differences at the
state, county and RMA levels, although neither
county nor RMA explains a very large part of
the variance in rates (not due to time). Thus,
there is evidence of discrete changes in supply
and demand substitutability at both the local
(county or RMA) and state levels, with a larger
change at the state level.
the simple average of the rates paid by the
banks with branches in the county. Second, we
focused on California because it contains more
banks (thus giving us better estimates of the
rates in different counties) and also because the
presence of several banks with large statewide
branches would suggest that California is likely
to be a deposit market. For each county (or
RMA) in California, we computed the correlation over time of the mean rate in that county
(or RMA) with mean rates in every other
county (or RMA). This resulted in a matrix
with (n2 - n)/2 correlation coefficients where n
is the number of counties (or RMAs).
Next, we computed similar correlation matrices of California counties with counties in
other states for each of the other states separately. This resulted in 7 matrices of n x mj
correlation coefficients, where n is the number
of counties (RMAs) in California and mj is the
number of counties (or RMAs) in state j. Finally, we computed summary statistics over
these eight matricies of correlation coefficients.
If our hypothesis that California is a single deposit market were correct, we would expect the
means of the correlations of counties (or
RMAs) in California with each other to be significantly greater than the means of the correlations of California counties (RMAs) with
other states' counties (or RMAs).
The results in Table 3 indicate that both mean
MMDA and Super NOW deposit rates in each
California county (RMA) are very highly correlated with mean MMDA and Super NOW
rates, respectively, in every other California
county (RMA). The mean CA-CA correlation
is .997 for MMDAs and .988 for Super NOWs
using RMA data. Correlations of rates over
counties is also large, but smaller than the correlations over RMAs. This might be expected
since RMAs, being metropolitan areas, are
more homogeneous than counties, which include both urban as well as rural areas.
The results in Table 3 also show that for both
the MMDA and Super NOW, correlations of
counties within California are much higher than
correlations of California counties with out-ofstate counties. This same result also is found
when using RMA data. All differences in the
Correlations of Rates Over Time
Another test of the extent of geographic deposit markets is to compare within-area correlations to across-area correlations. If a given
geographic region were a market, then rates
within that area should be more highly correlated with one another than with rates in other
areas.
In Table 3, we present the results of just such
a test. First, we calculated a mean rate for each
county (or RMA) in our sample. The mean is
36
TABLE 3
Mlaans of Within and Cross-State Correlation: Synthetic Data
(Standard Deviations in Parentheses)
CA~CA
CA-ID
CA-AZ
CA-HI
.752*
(.027)
.867*
(.015)
812
232
2204
.973
.666
.828
1.000
.809
.907
CA~NV
CA-OR
CA-UT
CA-WA
.588*
(.027)
.669*
(.040)
638
2088
1218
.813*
('034)
2146
.306
.809
.503
.477
.667
.463
.894
.675
.779
.888
.848*
(.018)
.627*
(.053)
.715*
(.035)
.825*
(.028)
MMDA Rate
COUNTY DATA
mean
.995
(.004)
N
1653
min
max
.392*
(.029)
.846*
(.020)
RMA DATA
mean
.997
(.002)
.735*
(.011 )
.864*
(.011 )
.408*
(.023)
N
378
84
28
84
56
140
84
224
min
.987
.717
.827
.360
.813
.582
.675
.748
max
1.000
.769
.880
.450
.878
.756
.784
.882
.690*
(.265)
- .290*
(.062)
-.004*
(.364)
2088
1218
2146
Super NOW Rate
COUNTY DATA
mean
.981
(.023)
N
1653
-.272*
(.059)
.959*
(.015)
- .132*
(.077)
.940*
(.041 )
812
232
2204
638
min
.859
.469
.908
.365
.795
0
- .430
-.637
max
1.000
-.104
.977
.036
.982
.950
.007
.828
.955*
(.024)
.652*
(.053)
.205*
(.082)
- .046*
(.217)
RMA DATA
.988
(.012)
- .257*
(.059)
N
378
84
min
.925
-.394
.927
max
1.000
-.122
.983
mean
.964*
(.011 )
28
- .171 *
(.075)
56
140
84
224
-.253
.892
.498
-.312
-.604
.037
.985
.752
- .011
.387
84
*Mean significantly different from the CA-CA mean at the 1% level
37
banks' rates than are California banks' rates
with out-of-state banks' rates. Such tests are reported in Table 4, The results confirm that the
time patterns of rates of California banks are
significantly more similar to each other than
they are to non-California banks. Thus, the
data at the bank level also support the hypothesis of statewide MMDA and Super NOW deposit markets for California.
means are statistically significant at the 1 percent level or better. Thus, thisevidencesuggests that markets are not larger than states.
This same type of test could be performed to
determine whether the correlation of rates
witliina county (01" RMA) was larg¢r·than the
correlation of rates in that county (or RMA)
with rates in other counties (or RMAs). However, given the very high .RMA-RMA correlations (in California) reported in Table 3 (.998
for the MMDA), the correlations of rates
within particular RMAs cannot be much
higher. Further, since correlations of rates in
California counties or RMAs with counties or
RMAs outside the state are generally considerably lower than the within-California correlations, the very high within-state correlations
cannot be due solely to common nationwide
movements in the demand for loans.
These results, however, may be partly due to
the existence of many multiple-branch banks
(with branches in only one state) that price uniformly within states. An alternative test is to
see if banks in California have rates that are
more highly correlated with other California
Structure..Performance Tests
The final method of investigating the geographic scope of ba.nking deposit markets
employed in this paper tests the structureperformance hypothesis at different levels of
geographic market definition. It measures market concentration (and hence competitiveness)
using the Herfindahl index (the sum of the
squares of each bank's market share) at two
different market levels-one assuming markets
are statewide and the other assuming markets
are local. The first index, the state Herfindahl 17 , is simply a measure of concentration at
the state level; the local Herfindahl is a similar
number defined separately for each local "mar-
TABLE 4
Means of Within and Cross-State Correlations: Individual Bank Rate Data
(Standard Deviations in Parentheses)
CA-CA
CA-Other States
MMDA Rate
Mean
N
min
max
.899
.659*
(.127)
(.184)
406
.332
870
.043
.997
.950
.655
.167*
(.446)
Super NOW Rate
mean
(.337)
N
Min
Max
378
-.549
.999
*Mean significantly different from the CA-CA mean at the 1% level.
38
784
.988
1.000
and therefore could pay correspondingly lower
explicit rates on deposits.
Weqlso included as control variables the percent of large, $100,000 and over, Certificates of
Deposit (CDs) (as of November 30, 1982) and
the growth rate of total deposits from November 1981 to November 1982. Banks with a
larger percentage of CDs may be more risky,
or they may be more aggressive seekers of deposits generally, or they may have greater incentives to substitute less costly MMDAs for
CDs. In all three cases, they would either have
to or be willing to pay higher rates on MMDAs.
Banks in rapidly growing deposit markets, however, would be able to pay lower deposit rates
because an exogenous increase in the supply of
deposits relative to demand would drive down
deposit rates.
The final two control variables were measured contemporaneously with the MMDA and
Super NOW rate. One is a linear time trend
and the other is the national average rate on
money market mutual funds. Presumably, deposit rates should follow a national open-market rate, at least to some extent, because of
common nationwide movements in the demand
for loans or because of nationwide competition
for deposits from the money funds.
The results of these analyses are presented in
Table 5. For the MMDA, the state Herfindahl
but not the local Herfindahl is significantly negatively related to rates, as expected. This suggests that for the MMDA, deposit markets are
statewide and not local in scope. However, the
magnitude of the state Herfindahl coefficient is
not large. For the county model, the estimated
coefficient of - .0067 implies a difference of
only 67 basis points between a perfectly competitive market and a perfectly monopsonistic
market. Thus, MMDA markets may be even
larger than states because such a small differ~
ence in rates among states implies a very elastic
supply of deposits on a statewide basis.
For the MMDA, we also find significant negative effects of banks' state market shares on
rates. The coefficient in the RMA model, for
example, implies that a bank with 100 percent
of the state market would pay 41 basis points
ket", either county or RMA. Both concentration measures were obtained from our 1983
FDIC Summary of Deposits Tape.
According to the structure-performance hypothesis, rates in more concentrated, and hence
less competitive markets, are expected to be
lower. Thus, if the state were the relevant market, we would expect the state Herfindahl to
be negatively related to deposit rates, whereas
if the county or RMA were the relevant market, the local Herfindahl should be negatively
related to deposit rates.
To test these hypotheses, we used our syn·
thetic database in which an observation is a
bank in a county (or RMA) in a month, so that
we could directly enter both the local and state
Herfindahl indexes in our regression model. In
addition to entering these two measures of concentration in our regressions, we included a
number of other variables to control for other
factors influencing banks' deposit rates.
Two key control variables are a bank's deposits as a percentage of total deposits of all
banks in the state and its percentage of local
deposits in a county or RMA (as of June 30,
1983). These variables were included primarily
because a study by Smirlock (1985) found that
they were significantly related to bank profitability in a model that included market concentration (Herfindahl) measures. He argued that
concentration was a proxy for market share and
that a higher market share, in turn, was
achieved by better operated, more efficient
(and thus more profitable) banks. It is unclear,
however, whether banks with larger market
shares would pay lower deposit rates, although
it is plausible they would if they achieved their
larger market shares by offering better quality
services. In contrast, if they were more profitable because of superior lending abilities, they
might pay higher rates on deposits.
Other control variables include the number
of branches, both in the state and in the local
area, as well as a dummy if the bank had 5 or
fewer branches in the state. Presumably, the
number of branches is positively related to the
level of convenience. If so, banks with more
branches would be paying higher implicit rates
39
TABLE
5
Test of the Structure-PertormanceHypothesis: Synthetic Data
(Standard. Errors· in Parentheses)
MMDARate
RMA
N
mean
R2
SEE
Intercept
COUNTY
7750
19,050
856.66
853.61
7322
699.59
COUNTY
18,044
693.85
.28
.30
.27
.18
52.83
46.42
56.74
424.32***
413.89***
- .0038*
(.0022)
- .0067***
(.00097)
Local Herfindahl
-.00082
(.0015)
.00055
(.00044)
# of Branches
-.00015
(.017)
.013
(.022)
# of Branches in State
RMA
55.06
State Herfindahl
5 or Fewer Branches in State
Super NOW Ra.te
-11.93***
(3.96)
-5.47*
(3.19)
.016***
(.0028)
.016***
(.0016)
690.06***
628.36***
.054***
(.0019)
.046***
(.0011)
.0087***
(.0013)
.00094*
(.00049)
- .042***
(.014)
27.69***
(3.85)
.063***
(.0024)
-.035
(.024)
44.97***
(4.25)
.045***
(.0018)
Deposit Growth
37.80***
(6.05)
Percent CDs
6.78
(5.17)
9.16***
(3.27)
47.63***
(4.49)
-85.25***
(4.00)
55.47***
(3.61 )
- 6.51 ***
(.14)
-5.51***
(.088)
- 2.43***
(.13)
-2.02***
(.10)
Money Fund Rate
.64***
(.012)
Percent of State Deposits
.41 ***
(.10)
.63***
(.0073)
- .28***
(.053)
Percent of Local Deposits
.022
(.090)
.073*
(.039)
Time
-35.83
(3.64)
***Significant at the 1% level
**Significant at the 5% level
*Significant at the 10% level
40
-98.51 ***
(5.23)
.072***
(.010)
- 2.19***
(.091 )
.40***
(.078)
.11 ***
(.0080)
-1.35***
(.058)
-.025
(.043)
less than one with a zero market share. Again,
this is not a large effect, but it is consistent with
Smirlock's findings that banks with larger market shares are more profitable. 18
The estimated coefficients of the number-ofbranches variables are not as expected. Banks
with more branches in the state actually pay
higher rates and banks with 5 or fewer branches
pay lower rates. Perhaps banks with fewer
branches offer some more-than-compensating
high-quality service, such as personalized attenthat might account for these findings.
We do find that, as expected, banks in more
nu,irl'lu growing markets pay lower rates, and
that banks with larger percentages of CDs pay
higher rates. MMDA rates also track the money
fund rate but on less than a point-for-point basis
estimated coefficient is approximately
.6). This strong correlation of MMDA rates
with money fund rates might be due to common
movements in the demand for loans, and hence
de!pos,its, to competition for deposits from the
money funds, or to both.
For the Super NOW, the coefficients on the
Herfindahl variables are puzzling. Although
the coefficients of the state Herfindahls are statistically significant, they are positive, not negative as expected. Thus, the state differences in
the level of Super NOW rates are not explained
by the concentration-competition hypothesis.
H()w(~ve:r. in the RMA model, the local Herfindahl coefficient is negative and significant, alth" .. ~,h in the county model, it is positive and
significant at the 10 percent level. Thus, the
structure-performance tests for the Super NOW
nr,nui:dp conflicting evidence for the local market hypothesis.
These tests also do not support the state market hypothesis. The positive Herfindahls may
be proxying for some other variable, like service quality. Quality of service is likely to be
much more important for the Super NOW, with
its large transaction component, than the
MMDA which has only limited transaction features. For example, if more highly concentrated
markets were also markets where providing
quality service is expensive, then keeping deposits in such markets (assuming they are comwould require higher explicit rates to
compensate for the lower quality of services.
Consistent with a high service component,
we find that Super NOW rates do not respond
to open-markets rates to anywhere near the
same extent as do MMDA rates. The coeffion
money-fund-rate variable is
1/9 to 1/6 as large as the coefficients in the
MMDA model, depending on whether county
or RMA estimates are compared. This low correlation also suggests that neither common
movements in the demand for loans nor nationwide competition from the money funds drives
Super NOW rates. Also consistent with the
pothesis of a high service component connected
with Super NOW accounts is the much larger
effect of a bank's market share for Super NOWs
than MMDAs-the effect is over 4 times as
large. The estimated effects of deposit growth
are negative, as expected, and percent of CDs
has a positive effect on the Super NOW rate. 19
Unlike the MMDA results, banks with five
or fewer branches pay higher Super NOW
rates, as one might expect, although the total
number of branches in the state has a positive
although small coefficient. Also, unlike the
MMDA results, the number of branches in the
RMA does have a significant negative, although
effect and this is consistent with
the idea that Super NOWs have a large service
component that depends on the number of
branches in a local area. In summary, the structure-performance results for the Super NOW
are consistent with the account's much larger
service component (compared to the MMDA),
but they provide no direct information on
whether the markets for Super NOWs are local
or statewide.
Qualifications Due to Unmeasured Quali1:v
Competition
All three of these tests are based solely on
measures of explicit interest rates. Implicit interest (in the form of transactions services, for
example) may be quantitatively important especially for the Super NOW. Below, we consider how the inability to measure nonpecuniary returns could affect our results.
First, as mentioned previously, if quality
(that is, implicit interest) were unrelated to
41
(for example, by laws that restricted branching
or that limited banking hours). If such areas
were in competition with unregulated areas or
areas with lower costs of providing quality, it is
likely there would be compensating differences
in explicit rates. Thus, compensating explicit
rates also might cause us to conclude that markets are smaller than they are in reality.
A third possibility is that, because of the
difficulty (that was mentioned previously) of
paying different explicit rates in different
geographic locations within a state with unrestricted branching, banks would compete
through quality competition. If this were correct, true rates would exhibit larger differences
than explicit rates. This would bias our results
toward finding no differences in rates among
local markets when they actually do exist.
Although both the analysis-of-variance and
structure-performance tests are likely to be
biased by unmeasured quality differences (although the sign and magnitude of the bias are
unknown), the correlation analysis is not biased
as long as the provision of quality does not vary
over time. (If quality varies much less than explicit rates then the bias is likely to be small.)
This is because adding constants to the rates in
two areas (reflecting different quality components) does not affect correlations of the rates
over time.
geographic area, our results would be unbiased
because the error term in both the analysis-ofvariance and structure-performance models
would capture the quality component and be
uncorrelated with the explanatory variables.
However, if quality were correlated with geographic area, both models would be biased, although the correlation analysis, under certain
assumptions, would not be similarly affected.
Below, we consider two hypotheses of how
quality might be related to geographic area.
First, consider Stigler's (1964) theory of quality competition that within non-competitive
markets competition takes place along various
quality dimensions. Within such markets, we
would observe uniform explicit rates that were
below competitive levels even though true
rates, including the quality component, were
higher and perhaps more variable. Thus, this
type of quality competition would tend to bias
the results of both the analysis-of-variance and
structure-performance tests toward a finding of
larger geographic differences in rates than actually existed. This in turn could lead us to conclude that markets are smaller than they are in
reality.
Another possible correlation of quality with
geographic area would exist if the provision of
quality were more expensive in some areas or
if it were kept below market levels by regulation
III. Summary and Conciusions
For the Super NOW, we find statistically significant and large state differences in the level
of rates. This suggests that Super NOW deposit
markets are not larger than states and that competition within states differs from that across
states possibly because of prohibitions on interstate branching. The correlation analysis
also points to Super NOW deposit markets no
larger than states since Super NOW rates in
counties (or RMAs) in California are much
more highly correlated with each other than
with rates in counties (or RMAs) in other
states.
There is also evidence of statistically significant differences in the level of rates among
20
RMAs (or counties) within states. These significant inter-RMA or inter-county rate differences within the states suggests local Super
NOW deposit markets that are smaller than
states. However, the magnitude of the differences in Super NOW rates among counties or
RMAs is small compared to inter-state differences. So, although there may be distinct local
markets for Super NOWs, there is apparently a
much higher degree of competition among the
local markets within states than among the
states.
The structure-performance tests yield unexpected results for the Super NOW-rates are
positively, not, as expected, negatively related
42
to the Herfindahl measure of concentration.
This result may be due to the high (unmeasured) service component of the Super NOW
yield.
Not only is the service component of the
Super NOW yield likely large, but differing service charges and minimum balance requirements also may account for some of the observed differences in explicit rates. However, it
is unclear whether and how such factors would
be correlated with geographic area and, hence,
how they could be biasing our results.
For the MMDA, the results of all three
tests-analysis of variance, correlations over
time, and the structure-performance hypothesis-provide consistent evidence that MMDA
markets are not larger than states.
In addition, we do not find significantly different MMDA rates among RMAs or counties.
Also, mean rates on MMDAs among counties
or RMAs within California are almost perfectly
correlated with one another and are more
highly correlated with one another than with
counties or RMAs in other states. Moreover,
although MMDA rates are negatively related to
concentration levels measured on a statewide
basis, they are not related to concentration
measured on the county or RMA level.
Thus, none of these tests provides support
for the hypothesis of local MMDA deposit markets, at least within California. This may not
be surprising given the statewide branch banking in the 12th District and the uniform pricing
by multiple branch banks within a state. In California especially, where the 5 largest banks
have huge branch networks and are represented
in virtually all of the RMAs or counties, it is
almost a foregone conclusion that mean rates
in all RMAs or counties would be similar. 21
If unrestricted branching within a state does
in fact lead to statewide MMDA deposit markets, then regional or national branching may
lead to regional or nationwide MMDA deposit
markets. Thus, as interstate banking progresses
we would expect to see MMDA deposit markets
expand geographically.
These MMDA results also demonstrate how
misleading conclusions drawn from the socalled service area method of defining deposit
markets may be. It is likely that most banks'
MMDA deposits come from a relatively small
geographic area near the bank, but there is very
little doubt that MMDA deposit markets are
much larger.
FOOTNOTES
1. See Garcia (1983) for an early attempt to analyze geographic deposit rate differentials to determine the geographic markets for MMDAs. Also. see Wall and· Ford
(1984) and Watro (1985) for examples of studies that also
analyze deposit rate levels in different geographic areas to
determine the geographic extent of a market.
congruence between supply and demand elasticities and
market definition. His discussion focuses on the market
power of sellers rather than buyers, however.
6... There is some error in measuring interest rates because
information on the method of compounding is not available
in our data set. However, different compounding methods
have relatively small effects on interest rates for short-term
accounts (such as the MMDA and Super NOW) where interest is usually paid monthly and sometimes weekly.
Another difficulty in measuring interest rates comes from
the fees many banks charge for maintaining accounts. For
Super NOWs, this is likely to be an especially important
problem since the fees are significant. Unfortunately, our
survey data contain no information on fees. However, in a
study in which such fee data were obtained, Watro (1985)
does not find a statistically significant relationship between
service charges and deposit rates.
2. Depository institutions may also be considered to be
suppliers of deposit services, such as check clearing and
the exchange of currency for deposits. However, since
banks pay net interest on most deposits, the value of deposits as inputs into the production of loans must exceed
the cost of deposit services. Thus, depository institutions
may be viewed as net demanders of deposits.
3. Time and convenience factors associated with check
clearing and cashing may lead depositors to prefer local
banks.
4. The ratio of the deposit rate ina market with a single
buyer to the rate in a competitive market is 1/(1 + 1/E 8 ),
where E 8 is the elasticity of supply of deposits. For example,
if the elasticity is 2, the rate in the monopsonistic market
will only be 2/3 of what it would be in a competitive market.
Another difficulty in measuring interest rates is that some
banks use "tiered" structures in which the rates depend on
deposit quantities. This introduces another source of error
into our measure of deposit rates. A closely related difficulty in measuring rates properly is that different banks
have different minimum balance requirements. However,
5. See Posner (1976) for an interesting discussion of the
43
Watro (1985) does not find a statistically significant relationship between minimum balance requirements and the
level of rates.
7. See Wall (1984) for evidence that deposit rates differ
with markets.
15. A model with state and time interactions also was estimated. However, the hypothesis that the state-time interactions had no effect on the rate could not be rejected.
Thus, only the results from the simpler additive model are
reported.
8. See Gilbert (1984) for an extremely critical review of the
structure-performance literature. See Heggestad (1979) for
a more supportive summary of the findings.
16. We also estimated the model without Hawaii to see if
there Were significant differences among the other sta.tes.
For both deposit types, excluding Hawaii, we can also reject the hypothesis (at the 1 percent level or better) that
rates do not depend on state.
9. See Wolken (1984) for a comprehensive review of the
literature on geographic markets in banking.
17. The state Herfindahl values are Arizona = 2704, California = 1596, Hawaii = 2896, Idaho
2189, Nevada
= 3332, Oregon
2329, Utah = 1505, Washington
1195.
10. Evidence supporting the hypothesis that it is not some
administrative cost burden that leads banks to pay uniform
rates within states is the fact that the two bank holdinQ
companies in our sample with banks in different states pay
different rates in different states.
18. In the RMA model, when the percentage of state and
percentage of RMA deposit variables were excluded, the
state Herfindahl variable was negative, statistically significant, and larger in magnitude (- .0071 vs. - .0038). The
local Herfindahl was not statistically significant. In the
county model, the coefficient of the state Herfindahl variable behaved similarly when the two market share variables were excluded. However, the local Herfindahl was
statistically significant, but small in magnitude ( .00099).
19. In the RMA model, when the percent of state and percent of RMA deposit variables were excluded, the state
Herfindahl and RMA Herfindahl's are still positive and negative, respectively, and are significant. In the county model,
when the market share variables are excluded, the coefficient of the state Herfindahl variable is not appreciably
changed, but the coefficient of the county Herfindahl becomes negative (- .0033) and statistically significant.
11. Some banks pay different rates on personal and nonpersonal MMDA accounts, generally with higher rates on
personal accounts. We discovered that some banks In our
sample are reporting the average rate on both types of
accounts rather than the most common rate. This introduces another source of error into our measurement of
MMDA rates.
12. Out of a total of 59 banks, the numbers by state are
as follows: Arizona, 5; California, 29; Hawaii, 4; Idaho, 4;
Utah, 4; Nevada, 1; Oregon, 5; Washington, 7. However,
although sample sizes are small, the banks included hold
over 80 percent of all bank deposits in the Twelfth Federal
Reserve District. See the Data Appendix in Keeley and
Zimmerman (1985) for a more detailed description of the
FR 2042 data.
13. The synthetic data bases contain the same data information that could have been obtained by directly sampling
one branch in each "market" area of each of the banks in
our sample. However, since we had determined that all
banks in our sample paid the same rate at all branches,
sampling each bank instead of its branches was far more
economical. The results should not depend on which of
these two ways the sample was drawn as long as both
samples were random.
14. Mean rates in this chart are weighted means across
banks (using bank-level data) with the number of branches
of a bank being the weight. Thus, these rates represent
the expected rate a depositor would be paid at a randomly
selected branch.
20. All conclusions are based on our empirical findings,
which depend on the sample and data we used. See the
beginning of Section II and footnotes 6, 11, 12, and 13 for
a discussion of the limitations of the sample and data.
21. Two other studies of MMDA markets by Watro (1985)
and Wall and Ford (1984), unlike this study, do find significant local differences in MMDA rates. However, both of
these studies ignore the markets of the branches of multibranch banks. Instead of including observations for all the
branches of multibranch banks, they include only one observation for the home office and use the home office's
location to define the geographic market in which that bank
is participating. Further, in the Wall and Ford study, SMSA
differences are estimated without controlling for state differences. Thus, the results of these two studies are not
directly comparable to ours.
44
REFERENCES
Garcia, Gillian. "The Pricing of Regulatory Innovations: The
MMDA and Super NOW Account Experience," Proceedings of the 1983 Conference on Bank Structure
and Competition. Chicago, IL: Federal Reserve Bank
of Chicago, 1983.
Smirlock, Michael. "Evidence on the (Non) Relationship
between Concentration and Profitability in Banking,"
Journal of Money Credit and Banking, Vol. 17, No.1
(February 1985).
Gilbert, R. Alton. "Bank Market Structure and Competition:
A Survey," Journal of Money, Credit and Banking, Vol.
XVI, No.4, Part 2 (November 1984).
Stigler, George. "The Economics of Information," Journal
of Political Economy, Vol. LXIX, NO.3 (June 1961).
____ . "A Theory of Oligopoly," The Journal of Political
Economy, Vol. LXXII, No.1 (February 1964).
Heggestad, Arnold A. "A Survey of Studies on Banking
Competition and Performance," in Franklin R. Edwards, ed., Issues in Financial Regulation. New York:
McGraw-Hili, 1979.
Wall, Larry D. and Harold D. Ford. "Money Market Account
Competition," Economic Review. Atlanta, GA: Federal
Reserve Bank of Atlanta, December 1984.
Watro, Paul R. "Deposit Rates and Local Markets;' Economic Commentary. Cleveland, OH: Federal Reserve
Bank of Cleveland, February 15, 1985.
Keeley, Michael C. and Gary C. Zimmerman. "Competition
for Money Market Deposit Accounts," Economic Review. San Francisco: Federal Reserve Bank of San
Francisco, Spring 1985, Number 2.
Wolken, John D. Geographic Market Delineation: A Review
of the Literature. Staff Study 140. Washington, D.C.:
Board of Governors of the Federal Reserve System,
Posner, Richard A. Antitrust Law: An Economic Perspective. Chicago: The University of Chicago Press, 1976.
October 1984.
45
I
Ra
Alternative
Pr
I
Robert H. Rasche*
This study examines the volatility of short-term interest rates during three sample periods each corresponding to the use of different
operating guides for monetary policy: the 1970s, October 1979
through September 1982, and October 1982 through December
1984. Interest rate volatility was highest in the 1979-1982 period
although the experience was not homogeneous. Since October 1982,
short-run interest rate volatility has been the same as that experienced in the 1970s. Based on these data and a standard money
demand/supply model, some comparisons are made of the various
monetary policy operating regimes.
During the past decade, the Federal Open
Market Committee has employed three different operating procedures to implement its
stated policy of a gradual return to noninflationary growth rates for the monetary aggregates Ml, M2, and M3. Prior to October 1979,
monetary policy was conducted by setting
short-run targets for the federal funds rate.
During the period from October 1979 until the
fall of 1982, the FOMC placed more emphasis
on controlling the supply of nonborrowed reserves to the banking system. Since the fall of
1982, the FOMC has implemented monetary
policy in terms of targets for borrowed reserves. The differences among these various
procedures have been discussed extensively (including Wallich, 1984, Axilrod, 1985, and Gilbert, 1985).
Each of these operating procedures has different implications for interest rate volatility. A
graphical analysis of these implications can be
found in Gilbert (1985). It is a widely, if not
universally, accepted proposition that the implication of a change to a reserve-oriented operating procedure-such as that implemented
by the FOMC in October 1979-is an increase
in the short-term variability of interest rates,
particularly very short-term interest rates. The
rationale for this proposition is that under the
federal funds rate operating procedure in effect
during the 1970s, the various stochastic shocks
to financial markets originating in the private
sector of the economy were not allowed to affect interest rates in the short-run because they
were offset through appropriate open market
operations. With a reserve aggregate operating
procedure, however, the reserve aggregate is
maintained at a constant value in the face of
*Professor, Michigan State University, and Visiting Scholar, Federal Reserve Bank of San
Francisco.
46
A second purpose of this study is to compare
the results of the federal funds rate operating
procedure with the borrowings procedure employed since late 1982. Wallich indicates that
the latter was introduced to avoid uncertainties
associated with targeting nonborrowed reserves
in a period of rapid financial innovation, and,
at the same time, to allow interest rates more
responsiveness (such as the federal funds rate
to market forces) than existed under the pre1979 procedures.
We show that the standard money demandmoney supply framework used for analyzing
monetary control problems indicates that increased volatility of interest rates does not imply a reduction in the short-term variability of
money around a target value when switching
from a federal funds rate control procedure to
a borrowings control procedure. Furthermore,
the interest rate volatility observed under
either of these operating procedures is a measure of the lack of precision in short-run monetary control, given a stable money demand
function and constant precision in forecasting
the income variables in the money demand
function.
Finally, we compare the volatility of interest
rates and borrowings in the 1969-79 period
with the respective measures for the sample
from the fall of 1982 through January 1984. The
data suggest that there has been little, if any,
change in the volatility of either the federal
funds rate or borrowings from the Federal Reserve under the two regimes. This suggests that
the borrowing procedure in effect since the fall
of 1982 shares the monetary control problems
that were encountered during the 1970s with
the federal funds rate control procedure.
In Section I, the question of an appropriate
measure of interest rate volatility is discussed.
In Section II, comparisons of interest rate volatility are presented in samples drawn from different operating procedures. In Section III, the
behavior of interest rates and monetary aggregates under federal funds rate and borrowings
targeting procedures are compared, and the
similarity of behavior across the two regimes is
documented. Conclusions are stated in Section
IV.
such shocks, and prices (interest rates) function
as the market equilibrating mechanism in the
short-run.
One of the traditional concerns raised in opp,osition to a reserve aggregate operating procedure is that the interest rate variability under
such a regime would be so large that it would
interfere with the efficient functioning of financial markets. Consequently, one of the pressing
questions in any evaluation of the 1979-82
monetary experiment is the extent to which the
non borrowed reserves operating procedures
imposed additional volatility upon market interest rates. An extensive study of interest rate
behavior in the 1970s compared to interest rate
behavior during 1979-80 is available in the
work of Dana Johnson, et at. (1981).
One purpose of this paper is to reexamine
Johnson's investigation in light of what we
know from the structure of various money market models such as those constructed by the
staffs of the Board of Governors of the Federal
Reserve and the Federal Reserve Bank of San
Francisco, and to extend the examination of interest rate volatility into the period since the
fall of 1980.
The latter is important since there are at least
two reasons to believe that the experience in
1979-80 may not represent interest rate variability under an established reserve control procedure. First, the 1979 switch to the nonborrowed reserves procedure was one without
precedent in the history of the Federal Reserve
System, and it may have prompted a considerable period of learning for market participants.
Second, in March 1980, a significant external
shock was imposed upon financial markets with
the implementation of credit controls. The results presented below suggest that the increase
in interest rate volatility experienced during
1979-80 was not sustained uniformly throughout the nonborrowed reserves operating experiment (1979-82) and that alternative, and more
appropriate, measures of interest rate volatility
show considerably smaller increases during the
1979-82 period relative to the previous experience than do the measures used by Johnson,
et at.
47
I. Appropriate Measures of Interest Rate Volatility
et al. focus on the standard deviam', supply of money balances
Johnson,
tion of levels and changes in various interest
rates, including the federal funds rate and
on various maturities of
securities averaged over one-week periods. They
observe increases in volatility (standard deviaof weekly average first differences of the
federal funds rates of more than 250 pel'cellt
cornp::lnrlg thc October 1979 through September 1980 period with the period of January 1968
thr,oug;h September 1979.
They also attempt to remove the effect of
large cyclical swings in the funds rate (presumlow frequency) movements by focusing on
deviations from centered moving averages of
various lengths. Using these measures, they
find increases in federal funds rate volatility of
280 to 460 percent under the reserve aggregate
operating procedures.
There is reason to believe that these measures overstate the increase in volatility that
should be attributed to the change in operating
procedures. There was a considerable change
in the level of the funds rate from the earlier
period to the 1979-80 period. During the 196979 period, the funds rate averaged 7.05 percent,
while during 1979-80 it averaged 12.78 percent. Thus, any first difference in interest rates
in the later period corresponds to a smaller percentage change. This means that the difference
in the levels of interest rates between the two
samples is a significant factor in biasing the
comparison of the behavior of interest rates under the two operating procedures.
Consider the following model of the demand
and supply for money:
'Yo
Inmi
+
+
"IJ
Iml
Inmp
(3)
Inm,
where
<Po
<P2
=
=
d=
=
'Yo -_~Q. <p_'Yl __
'Y2 + 'Y2' 1
"12 + 02'
03
fLl - fL2
- - - - . 'Il
-----------. (J.
'Y2 + 02' I
'Y2 + 02'"
01
'Y2
+ 02
Now consider percentage changes of the federal funds rate over very short periods of time
during which the income variable can be assumed unchanged, the discount rate is
constant, and the nonborrowed reserves
is not changed. Under these circumstances:
Inrl_ 1
=
('Ilt
'It -
d
Thus, the implication of such a model is that
over very short intervals, the percentage
in the federal funds rate under a reserve aggregate control procedure should have a constant
variance (that is, be homoskedastic). This conclusion suggests that if volatility of the first difference of the federal funds rate with a reserve
aggregate control procedure when the level of
where
mp
Y,
+ <Pl lnY I + <h Imp
- <P3 InRU , + 'Ill
= <Po
Ind
(2)
=
This model is borrowed from Pierce and Thomson (1972), but respecified in log-linear terms.
The respecification is broadly consistent with
the observed structure of econometric money
market models (Tinsley, et at., 1982; Judd and
Scadding, 1981; Anderson and 1"\.<1:,,_11''',
that are very close to log-linear over a broad
range of shocks. Questions of speed of
ment to equilibrium are not
for the
question being addressed here, so the model in
equations 1-3 has been specified in '""1'","'Ul
form for simplicity.
Consider the reduced form
for
federal funds rate derived from this model under a nonborrowed reserves
procedure (RU exogenous):
fLl
00 + 0 1 InRU b + 02 Iml
+ 03 Imp + fL2
Inmi
nonborrowed reserves
discount rate
stochastic disturbances.
demand for money balances
income measure
fed funds rate
48
the funds rate is relatively low is compared with
its volatility under the same operating procedure when the level of the funds rate is relatively high, then the latter regime would exhibit
greater volatility by this measure than the former even though the variances of the structural
disturbances are the same in the two situations.
Since the available econometric evidence suggests that log-linearity is a better approximation
to the structure of U.S. financial markets than
linearity, the comparisons presented in Johnson, et al. may have inadvertently been biased.
The argument presented above concerns the
appropriate interpretation of observed interest
rate behavior in a macroeconomic context. But
the fundamental concern with interest rate volatility is motivated by microeconomic questions, namely that interest rate changes cause
capital gains or losses for bond holders. There
are reasons to believe that arithmetic changes
in interest rates do not provide a good measure
of capital gains or losses accruing to bondholders, and that percentage changes in interest
rates may be a preferable measure of the magnitude of the wealth effects that will occur as a
result of monetary policy actions.
Consider the impact of equal arithmetic
changes in interest rates from a low initial level
of rates compared with a high initial level of
rates. It is well known that bond prices move
inversely with yields to maturity (the first partial derivative of prices with respect to yields is
negative) and that the size of the price change
increases for a given change in yield as the maturity of the bond increases.
It is also true that for a given maturity, the
size of the price change for a given arithmetic
change in yield varies with the base from which
the yield changes. In particular, the higher the
initial level of the yield to maturity, the smaller
will be the absolute value of the bond price
change for a given arithmetic change in the
yield (Malkiel, 1966, Theorem 4, p. 55).2
Hence if the major cause for concern about
interest rate changes is the dollar value of the
capital gain or loss accruing to bondholders, the
arithmetic change does not give a good measure
of the relative size of the problem when the
level of yields is different.
In contrast, percentage changes in interest
rates may give a good measure of relative capital gains or losses to bondholders, particularly
if we are concerned with such gains or losses in
percentage terms. The general formula is complicated, and it is easier to see the rationale for
this conclusion by focusing on securities at opposite ends of the maturity spectrum, as shown
in Table 1.
TABLE 1
Measuring Gains and Losses to Bondholders
Percentage Change in Interest Rates
One period discount bond
P = (l
alnp
=
aim
r)F
_-_r__
(1 - r)
a21nP
-alm 2
P
i =
C
F =
r =
-
One period coupon bond
P
=
CF
(l + Cl!'
(l + i)
iJlnP
1
iJ 21nP
iJlni 2 =
(1-+
bond price
yield to maturity
coupon rate
face value
discount rate
49
-1
+i
iJlni
CansoI
-1
ij2
o
At the very longest maturity, the elasticity of
bond prices with respect to yield to maturity is
constant. At the short end of the maturity spectrum -one period bonds or discount securities
(bills), the elasticity of security prices with respect to the yield to maturity varies considerably relative to its own magnitude, but the elas-
ticity is so small that the implied capital gains
or losses are not very large .. For example, for
three-month bills with discounts at annual rates
inthe range of four to ten percent, the elasticity
of bill prices with respect to the discount is in
the range of .01 to .025.
II. Volatility of Rates Under Different Operating Procedures
The basic tests in Tables 4-9 of the Johnson,
et al. study have been reconstructed in Table 2;
but using logs of the various interest rates instead of levels. 3 The only significant difference
in the data is that the sample from January 1968
through September 1979 used by Johnson, et
al. has been truncated to January 1969 through
September 1979 because the 1968 data were not
readily available. The omission of 1968 is also
preferable since the original change from contemporaneous to lagged reserve accounting occurred during that year. We recalculated all of
the standard deviations reported in the original
study and were able to replicate the reported
numbers to within one or two basis points.
These comparisons are available in Appendix
B.
The results in Table 2 are quite remarkable. 4
The comparison of the 1969-79 period with the
sample for October 1979 through September
1980 differs considerably when measured in
percentage changes. The standard deviation of
the week-to-week percentage changes in the
latter sample is from 1.8 to 2.2 times as large
as the corresponding standard deviation in the
former sample, depending on the rate being
compared. The larger increases in the standard
deviations tend to be at the longer end of the
maturity spectrum. The corresponding ratios of
standard deviations measured in terms of arithmetic changes is 2.6 to 3.5. Thus, the choice of
units of measurement for interest rate volatility
is a substantial factor in assessing how much of
an increase actually occurred in 1969-79. However, the use of percentage changes does not
alter the conclusion that interest rate volatility
increased during the 1979-80 period over what
had been previously experienced.
The interesting experiment is to extend the
analysis beyond the fall of 1980. Four separate
TABLE
2
Standard Deviations of Percentage Change of Various Interest Rates (Weekly Data)
Sample
Fed funds rate
3-Mo. Bill
6-Mo. Bill
52 Wk. Bill
3-Year Note
5-Year Note
10-Year Note
20- Year Note
Fed
Funds
Rate
Regime
Nonborrowed Reserves
Regime
Borrowed Reserves
Regime
Jan. 69Sept. 79
Oct. 79Sept. 80
Oct. 80Sept. 81
Oct. 81Sept. 82
Oct. 79Sept. 82
Oct. 82Jan. 84
Feb. 84Dec. 84
Oct. 82Dec. 84
.039
.033
.028
.026
.021
.017
.013
.012
.071
.059
.053
.047
.042
.037
.029
.025
.053
.047
.041
.033
.028
.032
.023
.022
.049
.052
.041
.036
.028
.025
.025
.023
.059
.054
.046
.040
.034
.032
.026
.024
.046
.022
.025
.023
.021
.019
.018
.017
.038
.019
.017
.016
.015
.015
.014
.013
.042
'{l21
.022
.021
.019
.017
.016
.015
50
samples are identified for this purpose: October 1980 through September 1981, October
1981 through September 1982, October 1982
through January 1984, and February 1984
through December 1984. The first two of these
samples are drawn from the era·. of •nonborrowed reserve control procedure and allow observation of changes in interest rate behavior
as the period progressed and markets gained
experience with the new regime (they also
avoid the contamination of the experiment with
credit controls). The third sample covers the
period from the abandonment of nonborrowed
reserves control in favor of borrowed reserves
targets (Wallich 1984, Axilrod 1985, Gilbert
1985) to the end of lagged reserve requirements; and the fourth sample covers the period
of contemporaneous reserve requirements with
borrowed reserves targets.
The volatility of interest rates remains
higher, relative to the experience of 1969-79,
throughout the three years of the nonborrowed
reserve operating procedure experiment. However, interest rate volatility over this three-year
period is not constant. There is a reduction in
volatility of interest rates uniformly across the
maturity spectrum from the 1979-80 period to
the 1980-81 period measured as the standard
deviation of week-to-week percentage changes.
During the latter period, the volatility measure
was from 1.2 to 1.9 times the corresponding
measure in the 1969-79 base period.
Across the maturity spectrum, the volatility
dropped by 15 to 33 percent of the observation
f6}"1979---80 ... The observed volatility in the
1980-81 sample appears to be repeated in the
1981-82 sample. In some cases, the computed
volatility in the 1981-82 sample is slightly
higher than in the 1980-81 sample; in other
cases, exactly the reverse is observed. The
changes appear to be quite random across the
maturity spectrum, suggesting a constant variance (homoskedasticity) during the two-year
period.
The .introduction of borrowed reserves targets appears to have altered rate volatility once
again. The standard deviations of the week-toweek percentage change in rates decline uniformly after September 1982. In the case of
short- and intermediate-term rates, the volatility measure returns to the pre-1979 level, although the 10- and 20-year maturities continue
to exhibit volatility on the order of 1.5 times
the pre-1979 observations in the 1982-84 period. After the return to contemporaneous reserve accounting in February 1984, interest rate
volatility across the maturity spectrum is no
greater than that observed prior to 1979, and,
in the case of three- and six-month Treasury
TABLE 3
F-Statistics for Equality of Variance Compared
to 1969-79 Sample
Interest Rates
Sample Periods
1979-80
1980-81
1981-82
1982-84
1984
Federal Funds
3-Month T. Bills
6-Month T. Bills
52-Week T. Bills
3-Year T. Note
5-Year T. Note
lO-Year T. Note
20-Year T. Bond
3.35*
3.38*
3.54*
3.31 *
4.29*
4.73*
4.91*
4.76*
1.86*
2.18*
2.17*
1.63*
1.88*
3.53*
3.30*
3.66*
1.54*
2.62*
2.15*
1.90'
1.93*
2.74'
3.52*
3.94*
1.35
.94
.33
.37
.39
.58
.73
1.17
1.22
df( 1969-79 = 559)
5% Critical F
51
1.38
51
1.38
51
69
1.38
1.34
*Significant at 5% level
51
.46
.77
.78
1.00
1.22
1.82*
1.99*
47
1.39
biHs,volatility seems to have declined sharply
in the· most recent period.
These observations suggest several hypotheses. First, it appears that in the 1980-82
period, interest rates were less· volatile than
during 1979"-80,but, second,il.lterestrates exhibited more volatility in that period than under the federaLfunds rate control regime. A
third hypothesis is that, in terms of interest rate
volatility, the borrowings control procedure
pursued since the fall of 1982 is no different
than the pre-1979 control regime. These. hypotheses will be tested below.
One very simple procedure to test these hypotheses is to test the idea that the variance of
the various percentage changes in interest rates
is constant among different sample periods.
The 1969-79 sample is used as an initial base
for such comparisons. The relevant F statistics
are presented in Table 3. The results presented
there indicate that, for the three samples drawn
during the nonborrowed reserves control period, interest rate volatility increased significantly across the maturity spectrum. For the
two samples subsequent to the "deemphasis" of
M1, the statistics in Table 3 generally support
the conclusion that interest rate volatility is not
significantly greater than it was during the
1970s. The exceptions to this general statement
are the very longest maturities in the sample
period from 1982 to January 1984.
These results. are consist(:mt with. the second
and third hypotheses above. Since the standard
deviations in the 1982-January 1984 sample are
larger than those in the 1969--79 sal11plefoI"all
rates except the three-month, six-month and
52-week bill rates. (although not generally significantly so), it is interesting to base the tests
for equality of varianceonthe interest rate volatility observed after the nonborrowed reserves
control experiment. This procedure determines
whether there was a significant reduction in interest rate volatility after thC'!fall of 1982. The
F-statistics for these tests are presented in Table
4.
The results for the federal funds rate here are
somewhat surprising. The test statistics suggest
that the volatility of the federal funds rate in
the 1980-82 period was not significantly
greater than that observed from the fall of 1982
through January 1984. In spite of thisconclusion, the evidence suggests that volatility at all
other points on the maturity spectrum declined
significantly after the end of the nonborrowed
reserves control experiment.
Finally, a test of the first hypothesis that interest rate volatility in 1980-82 is significantly
lower than that experienced in 1979-80 is re-
TABLE
4
F-Statistics for Equality of Variance Compared
to 1982-January 1984 Sample
Interest Rate
Federal Funds
3-Month T. Bills
6-Month T. Bills
52-Week T. Bills
3-Year T. Note
5-Year T. Note
lO-Year T. Note
20-Year T. Bond
df(1982-84
=
69)
Sample Periods
1979-80
1980-81
1981-82
Feb-Dec
1984
2.48*
7.42*
4.58*
4.22*
4.28*
3.88*
2.70'
2.42*
1.38
3.65*
2.81 *
2.08*
1.88*
2.90'
1.82*
1.86*
1.14
3.61 '
2.78*
2.49*
1.92*
1.83'
1.93*
2.01 *
.69
.73
.47
.50
.55
.60
.64
.62
51
51
51
---~--~_.,-"'---,---
47
"---_._----"-~
*Significant at 5% Level
52
ported in TableS, The results ofthis test support the hypothesis that a significantreduction
in the volatility of short-term and intermediateterm rates occurred between 1979--80 and
1980-82,
Several.col1dtisioris·· appear' to be warranted
from this analysis, First, the period of reserve
aggregate operating guides was accompanied
by an increase in volatility that wasnotas large
as has been previously measured because of differences in the level of interest rates before and
after October 1979, and because the twelve
months subsequent to 1979 appear to beinfluenced by special factors,
Nevertheless, it is not appropriate to use the
volatility observed in 1980-82 as a measure of
the increased interest rate volatility that would
be observed under a pure reserve aggregate
control regime, On the one hand, these observations are probably biased downward since the
1979-81 operation procedure was not a regime
in which fixed reserve paths were maintained
but one in which gradual adjustment was made
back to such paths when deviations occurred,
On the other hand, the interest rate volatility
observ~d during this period may be biased upward. compared to what could be achieved under a fixed reserve path operating guide because lagged reserve accounting •was in •effect
throughout the period,
A third conclusion is that it is probably inappropriate to regard changes in the volatility
of very short~term rates as necessarily affecting
the volatility of longer term rates, Certainly
volatility increased uniformly across the maturity spectrum in 1979, However, when the volatility of the funds rate dropped dramatically
starting in late 1980, longer term rate volatility
did not immediately follow, Furthermore, in
the period since February 1984, it appears that
the volatility of Treasury bill rates of various
maturities has been reduced significantly below
the volatility of the same rates prior to October
1979, even though the volatility of the federal
funds rate in the two sample periods is
unchanged,
TABLE
5
F-Statistics for Equality of Variance
Compared to 1980-82 Sample
Interest Rates
Sample Period
1979-80
Federal Funds
3-Month T. Bills
6-Month T. Bills
52-Week T. Bills
3-Year T. Note
5-Year T. Note
lO-Year T. Note
20-Year T. Note
1.95*
1.38
1.61 *
1.84*
2.19*
1.61 *
1.40
1.22
------------~.
df(1980-82 = 103)
51
- - - -~--------~---------
'Significant at 5% Level
53
---
III. Are the New Operating/Procedures Different
From Those of· the .1970s?
The iQformation presented in Tables 2 .....5 suggests •that there is considerable similarity be,
tweelithev()latility of interest rates across the
maturity spectrum during the 1970s and in.the
period since the fall of 1982. Federal Reserve
officials are on record as indicating that the
pre;sentprocedures are not a return to the techniques of the •1970s:
Since the fall of 1982, the nonborrowedreserves strategy and its automaticity have
given way to a technique that allows the
funds rate to be determined by the market, through the targetting of discount
window borrowing from one reserve
maintenance period to the next, implemented by allowing a flexible nonborrowed-reserves path....The relation of
the borrowing level to the funds rate,
which has been one of the most familiar
features of the money market, always has
been relatively loose. Since a chosen level
of borrowings is consistent with any of a
range of values of the funds rate, current
operating procedures cannot be regarded
as a form of rate-pegging (Wallich, 1984,
p.26).
In spite of assertions such as this, short-run
interest rate pegging and borrowings targeting
areifuJ:1damentally similar. monetarycQntrOI
procel;!ures. This can be seen from Figures 1
and 2.which illustrate a federal funds rate target
procedure (the practice of the 1970s) and a borr()wel;! reserves target procedure (the practice
silice· faU. 1982), respectively, 5 The •curve .labelel;! . M D in the left hand side of the figure
represents a short-run money demand function,
while the curve labeled B D in the right hand
side of the figure represents the demand for
borrowed reserves by depository institutions.
Both are drawn as functions of the federal
funds rate (r), and it is assumed that the demand for borrowed reserves is zero when the
federal funds rate is less than the discount· rate
(rD ) , . These are simplifying assumptions for
purposes of illustration.
The exact positions of both the money demand curve and the demand for borrowed reserves curve are not known with certainty by
the monetary authorities, nor are they constant. Rather, both fluctuate randomly over
time. 6 It is assumed that those fluctuations occur within the ranges defined by the dotted
Figure 1
Federal Funds Rate Target Procedure
Federal Funds Rate
Federal Funds Rate
r
8~
---M,
M
8,
Money
82
Borrowed Reserves
54
8
curves M? and M~andby B?andB~. These
ranges of fluctuation are assumed the same for
both operating procedures.
With a federal funds rate operating procedure, the monetary authorities, in principle,
keep the federal funds rate within a sIl1aUinterval around the rate (F) that they believe is
consistent with their monetary objective (M*).
This range is represented by r1 and rz. 7 With
the federal funds rate constrained to the range
rerz, the money stock will be observed to fluctuate in the range M1 to Mz in the short-run,
and borrowed reserves will be observed fluctuating in the range B 1 to Bz, with the specific
outcomes dependent upon the size of the random fluctuations to MD and BD. 8 Movements
of the federal funds rate outside the range r1rz are prevented by the monetary authorities
through injections or withdrawals using open
market· operations of whatever nonborrowed
reserves are required to keep the funds rate
within the specified range.
When a target is established for borrowed
reserves, the operating procedure works in fundamentally the same fashion, except in this case
the range of funds rate fluctuation is implicitly
determined by the random fluctuations in the
demand for borrowings rather than being explicitly stated in the operating procedure.
AssulIlethat the monetary authorities establish>and exactly achieve a target for borrowed
reserves 13 {Figure 2). With this fixed supply of
borrowed reserves to depository institutions,
the federal funds rate will be observed to fluctl.lateillth¢ iailgerFr4 withthe "«,rtf"·,,!>,...
come dependent only upon the size of the randam fluctuation in the demand for borrowed
reserves.
The observed interest rate within the (r3-r4)
range is not affected by random fluctuations in
the demand for money under this operating
procedure. The observed outcome in terms of
money stock, M, will be in the range M F M4
depending on the particular random fluctuations to the demand for borrowed reserves and
the demand for money. Under the assumption
of exact control of the amount of aggregate borrowed reserves available to depository institutions, the funds rate can fluctuate outside the
range r3-r4 only by a deviation of borrowed reserves from 13. If borrowed reserves were to
deviate from 13, the monetary authorities would
inject or withdraw nonborrowed reserves to
maintain borrowings at 13, and, implicitly, to
maintain the federal funds rate in the range rF
r4'
In practice the monetary authorities probably
cannot achieve the borrowed reserve target exactly, but can keep the supply of borrowed re-
Figure 2
Borrowed Reserves Target Procedure
Federal Funds Rate
B
B
Borrowed Reserves
Money
55
serves within a small range around B. The addition of such "noise" to the operating
procedure does not affect the conclusion drawn
from Figure 2 in any fundamental way. For
given random shocks to the demand for borr()wedreserves(B?....B~), the implied range of
interest rate fluctuations (rrr4) will be larger
the larger the "noise" around the borrowed reserves target. 9 Nevertheless, the establishment
of· a •borrowed reserves target implies the establishmentof a permissible range of fluctuation forthe funds rate, and that range is maintained by the automatic provision or withdrawal
of nonborrowed reserves through open market
operations whenever market forces attempt to
drive the rate outside the implicit range. lO
The ranges of federal funds rate fluctuation
in Figures 1 and 2 represent the degree of funds
rate volatility that will be observed under the
two operating procedures. The size of this
range is explicitly set as part of the federal
funds rate operating procedures. ll With a borrowed reserves operating procedure, the size of
this range can be influenced, above some minimal amount determined by random shocks to
the demand for borrowed reserves, by the
amount of random fluctuation in borrowed reserves that is permitted around the target
value. 12 The implication of the volatility measures computed in Section II is that the volatility of the funds rate implicit in the borrowed
reserve operating procedure since the fall of
1982 has been basically the same as the volatility of the federal funds rate explicitly permitted
under the 1970s operating procedure.
What are the implications of this conclusion
for the short-run volatility of the monetary aggregates? Figure 3 examines the implications
for the volatility of monetary aggregates of operating procedures that establish ranges of fluctuation for the funds rate, whether explicit or
implicit (as with a borrowed reserves target).
First, consider the implication of widening
the permissible range of funds rate fluctuation
from r1-r2 to rrr4' as indicated in Figure 3.
With an unchanged range of fluctuation of the
short-run money demand function (M? to M~),
more short-run volatility would be observed in
Figure 3
The Short-Run Relation
of Funds Rate Volatility to the
Monetary Aggregates
Federal Funds Rate
the monetary aggregates the wider the range of
funds rate fluctuation. In Figure 3, the wider
range of funds rate fluctuation (rrr4) implies
fluctuations of the money stock in the range M3
to M4 compared with fluctuations in the range
M1 to M 2 with the funds rate restricted to the
narrower range (r1-r2)' Thus, if the borrowed
reserves control procedure had introduced
more volatility into the funds rate, it could have
been expected to introduce more short-run volatility into the monetary aggregates. 13
This comparison of funds rates and borrowed
reserves operating procedures stands in contrast to the results obtained from a comparison
of a funds rate and nonborrowed reserves operating procedure. In the latter case, the monetary authorities would allow more interest rate
volatility by not automatically conducting open
market operations to change the stock of nonborrowed reserves. In the extreme, nonborrowed reserves would be fixed regardless of observed fluctuations in interest rates.
Generally, as operating procedures move towards a smaller response of the supply of nonborrowed reserves to interest rate fluctuations,
rate stability decreases (volatility increases)
56
and the precision of short-run monetary control
increases. Thus, in moving from a federal funds
rate operating procedure toward a pure nonborrowed reserves operating procedure, a
trade-off exists between interest rate volatility
and the precision· of shorHunmbnetary cone
trol. 14 This trade-off does not exist when comparing federal funds rate operating procedures
with borrowed reserves operating procedures
because both of those operating procedures allow the automatic changes in the supply of nonborrowed reserves to depository institutions in
response to any shock that pushes the target
variable to an extreme of the predetermined
range of fluctuation.
mental criticism of the historical interest rate
and free reserves (borrowings) targeting regimes: unless the monetary authorities are prepared to adjust the target variables quickly and
correctly in response to new information, deviationsfrom the desired path of the monetary
aggregates are likely to persist.
The results discussed above suggest that a
simple indicator of the short-run precision of
monetary control with either an interest rate
operating guide ora· borrowed reserves operating guide is the short-run volatility of interest
rates. With the same money demand function
for the two control procedures, the larger the
variability of interest rates, the worse the precision of short-run monetary control. The data
on federal funds rate volatility during the periods 1969-79 and 1982-84 suggest that shortrun monetary control is unlikely to improve under the procedures used by the FOMC since the
fall of 1982 compared to the experience of the
1970s. If the proposition that the stability of the
short-run money demand function has deteriorated in the 1980s were correct, then a strong
case could be made that the operating procedure in effect since fall 1982 will produce less
precise short-run monetary control than did the
procedures implemented in the 1970s.
If it is assumed that the random shocks to the
demand for borrowings are uncorrelated with
the random errors in interest rates under the
interest rate operating procedure, and that they
are also uncorrelated with the random errors in
the supply of borrowings under the borrowings
control procedure, then the volatility of observed borrowings gives an equivalent measure
of the precision of monetary control. Under
these assumptions, and with a stable demand
function for borrowed reserves under the two
procedures, equal volatility of interest rates implies equal volatility of borrowings.
This conclusion appears to be supported by
the data. The standard deviation of week to
week percentage changes in adjustment borrowings (seasonal plus adjustment borrowings)
for those weeks when the federal funds rate exceeded the discount rate is .513 (.493) in 196979 and .664 (.556) in October 1982-January
1984.
Inertia in Adjusting Policy Guides
Although federal funds rate operating procedures as implemented in the 1970s and borrowed reserves operating procedures as implemented since fall 1982 may appear virtually the
same from the perspective of their effects on
short-run interest rate volatility and the shortrun precision of monetary control, it is possible
that the longer run precision of monetary control could improve from the switch. It could
improve if there were less inertia in adjusting
the operating guide under the borrowed reserves control procedure than under the federal
funds rate control procedure.
The presence of inertia in adjusting the operating guides, whether interest rate or borrowings, introduces positive serial correlation into
deviations of the money stock from its target
value. IS This positive serial correlation is
stronger the more infrequent the adjustment of
the target value for the operating guide and,
conversely, weaker the more frequent the adjustment of the target value for the operating
guide. Consequently, a change in operating
procedure that did not affect the precision of
short-run monetary control but that reduced
the serial correlation in the deviations of the
money stock from its target value would reduce
the longer run variation of average money stock
measures around the longer run average target
value.
The inertia in adjusting the target value of
the operating guide is the source of the funda57
rate are strikingly different among the sample
periods discussed above, for which the variance
of weekly changes is similar. There is clearly a
distinct change associated with the introduction
of contemporaneous reserve requirements, but
the strong second order moving average term
in the post-January 1984 sample appears consistent. with the change to a two-week reserve
averaging period.
The difference between the 1969-79 sample
and the 1982-84 sample, however, is not as
great as· it appears. The latter sample exhibits
more seasonality at approximately three-month
intervals as indicated by the large twelfth order
moving average factor. However, when the log
of the federal funds rate is written in moving
average form, the impact of innovations is remarkably similar for at least the first six weeks.
The first terms of the moving average polynomials for the two sample periods for the log of
the federal funds rate are:
It is possible, despite the experience with the
post-1982 borrowed reserves operating procedure which suggests no improvement for shortrun monetary control over that experienced under the federal funds rate control procedure of
th~1970s, that intermediate-run or .longer run
monetary control is improved by a reduction in
the inertia in adjusting the operating guide.
Changes in the precision of intermediate-run
monetary control (one- to six-months) should
be~videnced by distinctly different patterns iQ
the time series properties of interest rates. A
crude test of this hypothesis can be performed
by estimating ARIMA models for the federal
funds rate for the 1969-79 sample period and
for the sample since October 1982. The resulting models are:
January 1969-September 1979 16
InFFt - InFFt
1 =
.1460at - l + .2268at _4
(.0409)
(.0405)
at
+ .1321a t -9 + .1040at
(.0415)
January 1969-September 1979
11
InFF t
(.0408)
+ .1008at -13
=
.0371
X2(df=37)
2
X ( .05)(df= 37)=52.2
October 1982-January 1984
44.48
InFF t
InFF! - InFF! - 1
+ .3941 (lnFF t
(.1117)
]
-
InFFt - 2)
=
.0317
X2(df=22)
18.42
2
X (.05)(df=22) = 33.92
February 1984-December 1984
InFFt - InFFt
1 =
at + .4192a t _2
. (.1416)
2
X (df=23) = 21.88
s.e. = .0348
X2(.05)(df=23)
=
at
The only substantial difference between the
effects of the first six lagged innovations in the
two sample periods is that in the earlier sample
lags 1-3 have the same weight as lags 4-6. It
also appears that the three-week average of recent innovations (lags 1-3) has slightly less
weight in the more recent period (.69 vs. 854),
but no measure of the significance of the difference is available. Even though the statistical
significance of these differences cannot be determined, it seems appropriate to conclude that
there is no large difference in the intermediaterun time series behavior of the federal funds
rate under the two control procedures. This evidence is consistent with the hypothesis that the
inertia in the setting of the operating guide un-
at + .7199at -12
(.1033)
s.e.
=
+ .69(.88at 1 + 1.11at -2 + 1.02at _3)
+ .72(1.01at -4 + .99a t -5 + 1.00at -6)
+ ...
October 1982-January 1984
=
at + .854 (a t - l + at 2 + a t -3)
+ 1.081(at _4 + at 5 + at -6) +
and expressed in the same form:
(.0419)
s.e.
=
35.17
At first glance, these estimates suggest that
the time series properties of the federal funds
58
dercurrent procedures, in terms of the speed
with which interest rates (and hence the money
stock) are allowed to adjust, is similar to the
inertia in the 1970s under the federal funds rate
operating guide.
IV. Conclusion
The available evidence suggests that interest
rate volatility increased across the maturity
spectrum with the introduction of the "newoperating procedure." Subsequently, in .1980~82
the volatility of rates declined. It is not possible
to discriminate whether this represents learning
by market participants, contamination of the
1979~80 data by the credit control experience,
or a revision of the implementation of the nonborrowed reserves operating procedure over
time. By 1981-82, the volatility of the federal
funds rate was not significantly greater than in
1969-79. Since the fall of 1982, volatility across
the maturity spectrum has been the same as
that experienced in the 1970s.
Since the volatility and time series of the federal funds rate under lagged reserve requirements and an operating procedure that targeted
borrowings between the fall of 1982 and January 1984 replicates very closely the behavior of
this rate under the fed funds rate operating procedure in effect prior to October 1979, it appears that the two operating procedures have
similar implications for the short-run control of
the growth of monetary aggregates.
Both operate through the money demand
function and both share the common property
that inertia in adjusting the target to new in-
formation will produce persistent drift
monetary aggregate from its target value. However, if the stability of econometric money demand functiOns has deteriorated in the 1980s
compared to the 1970s, as is frequently alleged,
then a borrowings operating procedure that
produces essentially the same funds rate volatility as the funds rate operating procedure, will
not improve the precision ofshort-runmonetary control.
The outlook for longer run monetary control
under the two operating procedures is primarily
determined by the degree of inertia in adjusting
the operating targets. If it is more feasible for
the FOMC to adjust a borrowed reserveS target
correctly in response to new information than
it would be to adjust a federal funds rate target,
then a borrowed reserves operating procedure
could improve longer run monetary control
even though short"run control could be less precise than under the funds rate operating procedure. Since the FOMC continues publicly to
maintain the objective of gradually reducing
the rate of monetary growth to non-inflationary
levels, final judgment on the effectiveness of
the current operating procedure must be deferred until the success or failure of current
monetary policy is established.
Appendix A
Money Market and Monetary Control Implications of Alternative Operating Procedures
Some framework broad enough to evaluate
the effects of the three alternative operating
procedures on monetary aggregates and interest rates yet simple enough to produce useful
conclusions is necessary. The vehicle used here
is an extension of the money market model of
equations 1 through 3 in the text.
The model is presented below.
(1)
InM
= 'Yo
(2)
InM
=
+
'YI
InY + 'Y2 1m +
p + 8] InRR +
(3)
InBOR
=
(4)
InTR
wllnRD
+ (l - WI) InBOR +
(5)
(6)
f.LI
f.L2
InTR
VI
=
=
InRR + In( 1 +
=
InRR +
VI =
1.0;
f.L4
~~)
f.Ls
1m + V2 InRD + V3 InBOR
VI (lnr + (1) + V2 (InRD +
+ V3 (InBOR + (3)
for
59
<Xo + <Xl (lor - lord) +
V2 =
V3 =
0.0
(2)
f.L3
or Vz
=
1.0; VI
=
V3
=
0.0
or V3
=
1.0; VI
=
Vz
=
0.0
nonborrowed reserves (RU) or borrowings
(BQR) to be set as an exogenous variable by
suitable choice of the parameters, Vi'
Not that the control regimes are mutually
7 a nonzero value for one of the v· reexclusIve:
•
1
qUlf<;S> that the other two Vj be set .at zero.
The model has been specified to capture the
relevant properties of empirical money market
models, yet to retain log-linearity so that explicit reduced form expressions can be derived
for In r, In M, In RU and In BOR. The general
reduced form eqnations (without regard to the
control regime) are functions of the potential
exogeE-0us variables: income ("I), the discount
rate (r), nonborrowed reserves (RU) and borrowings (BOR). The stochastic terms in these
reduced form equations are functions of the
st~chastic f.LS and £s in equations 1 through 6.
Fmally, the coefficients in the reduced forms
are complicated functions of the structural parameters of the model and the control regime
variables-vb V2, and V3'
. T~e model is not complete without a specifIcatIOn of the "policy rule" that governs how
the operating procedure is adjusted over time. IS
Two extreme cases are interesting. The first is
complete adjustment each period to any new
information in the attempt to keep the monetary aggregate on its target path. The second
regime is one of inertia in which the control
variable is adjusted infrequently.
Note: Greek letters can be polynomials in the
lag operator B; i.e.
"11
+ "111 B + "112 B Z
"I11B + "IIzB z + --- for any
= "II (B) =
an d , "11* --
"110
polynomial
Equation 1 is the money demand equation
used above. Equation 2 is a reserve require"
ment that allows for stochastic fluctuations in
reserve requirements (p + f.LI) as a result of
shifts in reserves among different types of
banks and the possibility of lagged reserve accounting by changing the parameters of the
polynomial ~. 17
Equation 3 is a borrowings function that relates borrowings by financial institutions to the
spread (in percentage terms) between market
rates and the discount rate. Equation 4 is a Taylor series expansion of the log of total reserves
in terms of the log of nonborrowed reserves
a.nd the log of borrowings with an approximation error (f.L4) to represent the higher order
terms of the expansion. Equation 5 is a statement of the identity between total ~eserves, re"
quired reserves and excessive reserves, with an
assumption that the excess reserve ratio can be
approximated by a stochastic process (f.Ls). Finally, equation 6 allows the interest rate (r),
A. Continual Adjustment of Control Variable:
Interest Rate Operating Guides
In this situation, the reduced form equations
for interest rates and the monetary aggregate
are:
=
(7)
Inrt
(8)
InM t
monetary aggregate at t.
From (8):
(10)
Inft + £t
+ f.LI + 'YZ£I
+ "IllnYt + "I21nft
=
= "10
El- I InM t
=
+ f.Li + "1;£1 +
'YlOE1-l InY t + "IilnY t
+ "Izolnrt + "I;lnrt
"10
so
and !he policy rule governing the adjustment
of Inrt is:
(9)
El- I InM t
(11)
_
Inrt
InM*
1
(lnM* - 'Yo - f.Li
"Izo
- 'YIO El- I InY t
= -
and
where El- I InM t is the monetary authorities'
forecast of InM t based on information available
at t - 1 and InM; is the desired value of the
(12)
(lnMt - InM*)
=
60
f.Llt + 'Y20£lt + 'YlO(lnY t - El IlnY t)
This is the standard result (Thomson and
Pierce, 1972) that under an interest rate control
procedure with constant adjustment, deviations
from monetary targets depend upon stochastic
money demand fluctuations and errors in fore-
casting income. The additional term here is
generated by the error in hitting the interest
rate target, CIt. As long as the income forecast
errors are not serially correlated, deviations of
money growth from targets should not exhibit
serial correlation.
B. Continual Adjustment of Control Variable:
Borrowing Operating Guide
In this situation, the reduced form equations
for borrowings and the monetary aggregate are:
C3t + In BOR t
(13)
InBOR t
=
(14)
InMt
[(1'0 + fLIt) +
=
and the policy rule covering the adjustment of
InBOR t is the same as in equation 9: We assume
that the discount rate is set exactly by the monetary authority and is not changed. 19
The resufting behavior of the monetary aggregate relative to the target value is described
by:
(ao + fL3t)
+ 1m? +
(:~) C3t
(:~)]
+ 1'1 InYt
(15)
(~~) InBORt
(lnM t
InM*) = fLIt
+ I'IO(lnY t - Ei I InY t)
C. Infrequent Adjustment of the Control Variable To New
Information: Interest Rate Operating Guide
The criticism levied against monetary control
procedure in the 1970s and the free reserves
procedures of the 1950s and 1960s was not directed against the regimes described above.
Rather, as is now generally acknowledged, in
those periods, targets were changed only infrequently, or only by small amounts, in spite of
the availability of new information.
Consider a regime where forT is set at a value
based on information available at time t - nand
maintained at that value for r subsequent periods, that is, set lorTso that Ei-n InM T = InM*
for T = t - n + 1, .. , 1.
then
(16)
T
fLIT +
2:
i=t~n
I'IT i (lnY T
T
+
for
T
=
2:
i=t-n
I'ZT-i cIT
t - n + 1, ... ,t
In a regime where InBOR t is set at a value
based on information available at t nand
maintained at that value for n subsequent periods, that is, set InBORT so that Ei-n InM T =
InM* for T = t - n + 1, .. , t
then:
(17)
(lnMT - InM*)
(fLIT - Ei-n fLIT)
(lnMT
InM*)
fLIT
T
+
+ I'I(lnYT Ei-n InYT)
+ I'z[lmT + CIT - Ei n(lnrT+ CIT)]
2:
i=t
61
n
I'IT-i (lnY T - Ei-n InYT)
ApPENDIX
B
Standard Deviations of First Differences of Various Interest Rates (Weekly)
Sample
Fed Funds
Rate
Regime
Borrowed
Reserves
Regime
Nonborrowed Reserves
Regime
Jan 69-Sept 79
Oct 79
Sept 80
Oct 80
Sept 81
Oct 81
Sept 82
.28
.21
.18
.17
.14
.12
.09
.08
.95
.64
.57
.51
.49
.43
.33
.29
.87
.69
.57
.43
.39
.44
.31
.29
.63
.56
.48
.43
.40
.36
.35
.33
Oct 82
Jan 84
Feb 84
Dec 84
--------
Federal Funds Rate
3-Month Bill
6-Month Bill
52-Week Bill
3-Year Note
5-Year Note
lO-Year Note
20-Year Bond
.- _ .....
~,_
....
--
-~"'~-
.~,_
..
,
~
__ ._..
~~,_
..
.43
.18
.21
.20
.22
.21
.20
.19
~_,-~"""".,,.~,,"--'"
""""
.39
.17
.16
.16
.18
.18
.18
.17
-----------------------
FOOTNOTES
1. The results reported in Johnson, et al. Tables 4-9 were
reproduced with the data set employed in this study. The
current data set replicates the previously reported results
with a high degree of accuracy.
6. The random variation in the money demand function is
represented by J..L1 in the model in Appendix A; the random
fluctuation in the demand for borrowed reserves by J..L3'
7. In Appendix A, the fluctuation of the federal funds rate
under a funds rate operating procedure is represented by
2. This point also appears in the bond duration literature
where the percentage change in bond prices for a given
absolute change in yield to maturity is shown to be proportional to the duration of the bond. Since. for a given
maturity and coupon rate, duration decreases with increases in yield to maturity, the percentage (and absolute)
change in bond price for a given change in yield to maturity
is lower the higher the initial yield (see Yawitz, 1977).
£1'
8. In Figures 1A and 1B we assume that the fluctuations
of the federal funds rate in the range r1-r2 are independent
of shocks to the money demand function. In practice, during the 1970s, the Fed's Trading Desk was given the authority to move the federal funds rate systematically toward
an extreme of the range established by the FOMe when
the growth of money stock was observed to deviate from
the established short-run path. This procedure implies a
nonzero covariance between money demand shocks and
deviations of the funds rate from the midpoint of the r1-r2
range. The general expression for the variability of the
money stock under this control procedure is given by equation 12 in Appendix A, which can accommodate nonzero
covariance between £1' the funds rate fluctuation, and J..L1the shock to money demand.
3. The discussion here focuses on week-to-week percentage changes in the various rates (measured as log first
differences). Measures of interest rate volatility were also
constructed using percentage deviations from various
length centered moving geometric averages. These measures were compared with the measure reported in Johnson, et al. for deviations from centered moving arithmetic
averages. The results of these comparisons are consistent
with the comparisons reported here between arithmetic
and percentage changes in rates.
9. In terms of the model in Appendix A, the variability of
the funds rate is determined by the expression:
In particular, the same pattern of significant increases in
interest rate volatility in the 1979-80 period, and declining
volatility in subsequent sample periods, is observed when
the computations are performed relative to centered geometric moving averages.
alO
4. Volatility measures were also tabulated for the 196970 and 1973-75 subsamples considered by Johnson, et
al. Measurements of rate volatility in percentage changes
for these subsamples share the homoskedasticity property
that Johnson, et a/. found in the arithmetic measures of
volatility.
which represented the effect of random disturbances to the
demand for borrowed reserves (J..L3t) and the range of fluctuation in the supply of borrowed reserves (£3t). The interest rate fluctuations are amplified or attentuated by the
interest elasticity of the demand for borrowed reserves, but
are not affected by the parameters of or residual variance
in the demand for money.
5. The figures presented here are graphical representations of the short-run money demand and money supply
model in Appendix A.
10. Recent directives give the Desk authority to change
the degree of restraint on reserve positions systematically
when the growth of the money stock is observed to deviate
62
16. at represents a shock to the federal funds rate. The x2
statistic measures the probability that the a's are not serially correlated. A tabulated x2 value below the critical value
signifies that the probability of serial correlation in the a's
is below conventionally accepted levels of statistical
significance.
17; By suitable choice of the coefficients in the poiynominal 0, the model can even handle different marginal and
average reserve requirements such as proposed by Poole
(1976). A potential criticism of this model is that it does not
adequately account for the expectational behavior of either
households and firms with respect to the demand for
money or banks with respect to their demand for borrowed
reserves from the Federal Reserve System.
from the paths established by the FOMC. This procedure
implies a nonzero covariance between fluctuations in borrowed reserves supplied and shocks to money demand. In
the discussion here, a zero covariance is assumed. The
general expression that allows for nonzero covariances is
given in equation 15 of Appendix A.
11. tit in the model of Appendix A.
f.L3t
t3t.
.
12. -~~-~~ In the model of Appendix A.
«10
13. This can be seen by comparing either equations 12
and 15 or 16 and 17 in Appendix A. The only difference
between 12 and 15 or 16 and 17 is the replacement of tit
in 12 and 15 by
An elegant analysis of short-run money market behavior
has been constructed recently by Goodfried, et al. (1983).
It attempts to incorporate rational expectations with respect
to future interest rate behavior on the part of money demanders and banks, a sophisticated supply function for
borrowed reserves that captures "administrative pressure"
at the discount Window, and a gradual adjustment rule for
the supply of nonborrowed reserves. The dynamic properties of this model closely replicate the dynamic properties
of a simple model such as that in Table 10. Therefore,
conclusions drawn from a model such as that in Table 10
should be applicable over a broad range of potential
models.
«10
in 15 and 16. But those terms just represent the volatility
of interest rates under the two operating procedures.
Hence, if a funds rate operating procedure is compared
with a borrowed reserves operating procedure under the
assumption that the variance of the random component of
money demand and the precision of forecasting income
are unchanged, then the operating procedure with the
larger volatility of interest rates will exhibit less precision in
short-run monetary control.
14. Graphically, the movement from a federal funds operating procedure to a pure nonborrowed reserves operating procedure is a change from a horizontal "money supply function" to a vertical' "money supply function."
Intermediate cases, where the operating procedure allows
for some response in the supply of nonborrowed reserves
to interest rate fluctuations, are represented by positively
sloped "money supply functions."
18. We assume that the monetary authorities have no time
advantage with respect to curreJ:lL developments, so the
setting of the policy variable (r, RU or BOR) for time = t
is based solely on information available through time =
t - 1.
19. In fact, the discount rate at the NY Federal Reserve
Bank changed on only three occasions in the period October 1982 through January 1984, and only twice during
1984, so discount rate changes are not a major consideration in current operating procedures.
15. This serial correlation is introduced through the distributed lag terms in the estimated short-run money demand
equation, and occurs even if the underlying random disturbances in the model (f.L1I, f.L2t, tll and <3t) are not serially
correlated.
REFERENCES
Anderson, RD. and Rasche, R.H. "What Do Money Market
Models Tell Us About How to Implement Monetary Policy?," Journal of Money, Credit and Banking, November 1982.
Malkiel, B.G. The Term Structure of Interest Rates, Princeton, 1966.
Axilrod, S.H. "U.S. Monetary Policy in Recent Years: An
Overview," Federal Reserve Bulletin, January 1985.
Pierce, J.L. and Thomson, T.D. "Some Issues in Controlling the Stock of Money," Controlling Monetary Aggregates 1/: The Implementation, Federal Reserve Bank
of Boston Conference Series No.9., 1972.
Gilbert, R. Alton. "Operating Procedures for Conducting
Monetary Policy," Federal Reserve Bank of St. Louis
Review, February 1985.
Poole, W. "A Proposal for Reforming Bank Reserve Requirements in the United States," Journal of Money,
Credit and Banking, May 1976.
Goodfriend, M., et al. "A Weekly Perfect Foresight Model
of the Nonborrowing Reserve Operating Procedure,"
Federal Reserve Bank of Richmond, Working Paper
84-4, December 1983 (mimeo).
Roley, VV "Money Demand Predictability," N8ER Working
Paper 1580, March 1985 (mimeo).
Tinsley, PA, et al. "Policy Robustness Specification and
Simulation of a Monthly Money Market Model," Journal
of Money Credit and Banking, November 1982.
Johnson, Dana, et a/. "Interest Rate Variability Under the
New Operating Procedures and the Initial Response
in Financial Markets," Federal Reserve Staff Study,
New Monetary Control Procedure, Volume I, Board of
Governors of the Federal Reserve System, 1981.
Wallich, H.C. "Recent Techniques of Monetary Policy,"
Federal Reserve Bank of Kansas City Economic Review, May 1984.
Yawitz, J.B. 'The Relative Importance of Duration and
Yield Volatility of Bond Price Volatility," Journal of
Money, Credit and Banking, February 1977.
Judd, J.P. and Scadding, J.L. "Liability Management, Bank
Loans and Deposit 'Market' Disequilibrium," Federal
Reserve Bank of San Francisco Economic Review,
Summer 1981.
63
@FedFRASER