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2
I.
Competition for Money Market Deposit Accounts........5
Michael C. Keeley and Gary C. Zimmerman
II.
The Information Content of Credit Aggregates............28
Bharat Trehan
III.
Whither the Unemployment Rate?................................. 40
Brian M otley
Editorial Committee:
Hang-Sheng Cheng, Michael Hutchison and Michael Keeley.
3
4
by
Michael C. Keeley
and
Gary C. Zimmerman*
The money market deposit account (MMDA) is the first liquid,
short-term, small denomination deposit account in recent history to
be free from interest-rate ceilings. Introduced in December 1982, it
has become a very important source of deposits, with balances currently over the $450 billion level nationally, which represents about
15 percent of total deposits. In this paper, we analyze why the
account has been so successful, where the funds in the account came
from, how the shift in funds affected banks' deposit costs and how
individual banks competed for and priced MMDAs.
The single most important step in the deregulation of interest rates on retail deposits at
banks and thrifts was the authorization of the
money market deposit account (MMDA) and
the Super-NOW account, which were both free
of interest ceilings. 1 The volume of funds that
moved into MMDAs was staggering: MMDAs
grew to over $300 billion (15 percent of total
deposits) within three months after their introduction on December 14,1982. Super-NOW accounts, however, attracted only some $30 billion during the three-month period after their
introduction on January 5, 1983.
In this paper, we analyze why and how the
MMDA so dramatically altered both depositors' and banks' holdings of deposits and the
nature of competition for deposits. Our objectives are to explain why these accounts were so
popular, where the funds came from, what determined individual banks' pattern of adoption
of these accounts, and how sensitive the quantity of funds in these accounts was to variations
in both their own interest rate as well as the
rate on substitute assets. Our analysis focuses
on the MMDA rather than the Super-NOW because the MMDA's impact on deposit holdings
was so much larger.
Money market deposit accounts are an insured, short-term, ceiling-free account with
limited transaction features that were, in the
language of the authorizing Garn-St Germain
Act of 1982, to be " ... directly equivalent to
and competitive with money market mutual
funds ...". However, prior to their introduction, there was considerable uncertainty about
the sources and stability of MMDA deposits
and how they would be priced. Some thought
that MMDAs would attract large quantities of
money from the money funds, and there even
was speculation about the long-term viability of
the money funds given that MMDAs were insured. Others thought that most MMDA deposits would come from other funds already on
deposit at banks and thrifts. If large amounts
*Senior Economist and Economist, respectively. Research assistance from Joni Whitmore
and Maureen O'Byrne and comments from
Jack Beebe, Fred Furlong, Hang-Sheng Cheng,
Randall Pozdena and Barbara Bennett are
much appreciated.
5
of low-interest "core" deposits like passbook
savings accounts were transferred into
MMDAs, there were fears that banks' and
thrifts' deposit costs would rise substantially.
There was also uncertainty about how quickly
funds would be attracted to MMDAs and
whether they would be responsive to minor rate
changes (as are large, $100,000 and over, Certificates of Deposit, CDs), allowing individual
institutions to increase their market shares by
slightly outbidding their competitors. Moreover, it was unclear whether the MMDA's ratesensitivity would change over time-with balances more rate-sensitive during the initial introductory period than once depositors had
shifted funds into the new accounts.
We address these issues by analyzing the
competition for MMDAs, both among banks as
well as between banks and the money funds.
Our empirical analysis of these issues utilizes
monthly data on the rates and quantities of deposits of MMDAs and other accounts for a sample of 59 banks in the 12th Federal Reserve
District. (See Data Appendix.) Data for individual banks, unlike aggregate data, enable us
to address questions of interbank competition,
which most previous studies of deposit flows
cannot. 2 We do, however, use nationwide aggregate data to estimate the flows of funds into
MMDAs from the money funds and from other
deposit accounts.
Our analysis uses both micro and macro data
to estimate the parameters of the supply function of MMDA deposits to banks. Both shortand long-run, own- and cross-price elasticities
are estimated. In addition, we analyze the process of adjustment in financial markets both to
the introduction of a new account and to
changes in rates once the initial adjustment is
complete.
The organization of the remainder of this paper is as follows. In Section I, we provide a brief
description of the MMDA account and a historical perspective on why it was introduced.
Aggregate data for the nation are used to measure flows of funds into MMDAs, both from
the money market funds and from funds already on deposit with banks and thrifts. Section
II outlines a theory of banks' demand for
MMDA deposits and the nature of deposit adjustment costs. Implications of this theory for
the market acceptance and pricing of MMDAs
are developed as well. In Section III, the competition for MMDAs is analyzed. First, the time
pattern of adoption of MMDAs is modeled as
a function of banks' characteristics and pricing
strategies. Then, estimates of the short- and
long-run, own- and cross-interest elasticities of
the supply of deposits to banks are presented.
Section IV presents our summary and
conclusions.
I. Background
investors transaction and check-writing pnvIleges. These features were not available on
banks' "money market certificates", a sixmonth time account with an indexed ceiling
rate that yielded only slightly less than a sixmonth Treasury bill. Third, most funds' minimum opening balance was well below the
$10,000 minimum required for banks' sixmonth "money market certificates" or the
$20,000 minimum on 7- to 31-day time certificates. Fourth, the money funds were able to
raise "deposits" on a nationwide basis, effectively skirting the prohibition that banks faced
on interstate deposit-taking. Finally, MMFs
Money market deposit accounts were in part
a regulatory/legislative response to the success
of the money market funds (MMFs) which, by
late 1982, had attracted well over $240 billion,
much of it from traditional bank and thrift depositors. Money funds offered significant advantages over the regulated accounts offered by
depository institutions (hereafter referred to as
banks). First, the funds paid returns to investors near the wholesale money market rate.
Yields were determined by the return on the
funds' portfolios of short-term money market
instruments less a small administrative fee. Second, the funds were generally liquid, allowing
6
moved their funds out of the low-paying retail
accounts. Thus, it seemed unlikely there would
be a further shift of funds out of low-interest
retail deposits, such as passbook savings, into
MMDAs.
Rather, the funds for MMDAs, which have
limited value as transaction accounts, would
come from those sources where depositors had
moved them in the first place, to avoid the ceilings. We thus expected particularly large inflows into MMDAs from the money funds. Depositors had shifted balances from regulated
retail accounts into the money funds apparently
because they viewed them as close substitutes.
Moreover, since banks had used large CDs to
replace lost retail deposits, we expected declines in these balances as well. Also, to the
extent that the ceilings had induced depositors
to move funds into other near ceiling-free accounts, such as the six-month money market
certificate, some of those funds probably also
would be moved into MMDAs.
By analyzing the decline in various types of
deposits that were contemporaneous with the
MMDA's initial rapid deposit growth, it is possible to infer which types of deposits were probably the most important sources of MMDA
funds. For banks and thrifts, aggregate deposit
data (at the national level) for small and large
time deposits, savings deposits and transaction
deposits are analyzed along with data on money
funds' assets. In Chart 1, these various deposit
stocks are plotted along with MMDA and
Super-NOW deposits to indicate which types of
deposits fell as MMDAs grew. Also, monthly
changes in various types of deposits were regressed on monthly changes in MMDAs (and
other control variables) to provide quantitative
estimates of the sources of MMDA deposits. 3
Chart 1 shows that a substantial decline in
the money market funds' assets coincided with
the growth in MMDAs, suggesting that the
money funds were substitutes for MMDAs and
thus an important source of MMDA deposits.
Similarly, our regression model shows a statistically significant decline of $.24 in money fund
assets for each dollar that flowed into MMDAs.
Although the data suggest that the money
could be linked with other mutual funds and
security transactions.
Because of the money funds' dramatic
growth, there was considerable political pressure to allow banks to offer comparable instruments so that they could compete on an equal
footing. As it turned out, the MMDA and, to
a much lesser extent, the Super-NOW accounts
were just such instruments. Without them (or
accounts similar to them), it appeared that depository institutions might continue to lose retail deposits to the money funds.
MMDA Terms
Although the MMDA was patterned after
the MMFs, there are some differences, primarily regarding reserve requirements and regulatory limitations on transactions and minimum
balances. The MMDAs are free of interest rate
ceilings as long as a minimum balance of $1 ,000
is maintained ($2,500 prior to January 1, 1985),
and are insured to $100,000. The MMDA is
available to aU depositors, including individuals, governments, nonprofit institutions and
businesses-although non-personal deposits,
unlike personal deposits, are subject to a 3 percent reserve requirement. In addition, unlike
the money funds, MMDAs have transaction
features that are restricted by regulation. Depositors are allowed up to six automatic, telephone or check transfers per month (with a
maximum of three check transactions), although withdrawals made in person are unlimited. (See Appendix Table 1 for a detailed description of the characteristics of MMDAs,
Super-NOWs and the money funds.)
Sources of MMDA Deposits
Where would the funds for the MMDA come
from? In general, funds would be expected to
come from other financial instruments that
were close substitutes (from both banks' and
depositors' perspectives) for regulated retail deposits. Since, at the time of the MMDA's introduction, open-market interest rates had been
above the ceilings for a number of years, depositors who did not value the implicit interest
in terms of added services would already have
7
Chart 1
Money Market Funds vs.
Components of Total Deposits
(Combined Bank and Thrift Total)
8
funds were an important source of MMDA deposits, the money attracted from the MMFs did
not lead to a comparable increase in the total
deposits of the banking sector. As Chart 1
shows, there was only a slight increase in total
deposits after December 14, 1982 despite the
influx of funds into MMDAs from the money
funds. Thus, the MMDA inflows must have
been mostly offset by outflows from other types
of deposits. In particular, we would expect
some of the funds in banks' large CDs to leave
the banking sector as money funds' assets ran
off. In part, this is because of the direct effect
of a reduction in the money funds' holdings of
banks' CDs as the money funds contracted.
Moreover, as banks experienced rapid inflows
into MMDAs, they would reduce their purchases of relatively more expensive CDs, and
some of the previous holders of large CDs
would move their funds out of banking deposits. We find that there was indeed a statistically
significant decline in large time deposits (CDs)
of $.42 for each dollar increase in MMDAs.
This drop was considerably larger than the decline in the money funds' assets.
This rather massive substitution of retail
MMDAs for wholesale CDs has important implications for bank costs. Since MMDAs, like
other retail deposits, are generally less costly
than large CDs, this shift alone lowered banks'
deposit interest costs. The inflow from money
funds also has implications for their long-run
viability. Although we estimate that MMDAs
attracted nearly $90 billion from the money
funds, this appears to have been a one-time
shift since the money funds have continued to
grow despite competition from the MMDA. Indeed, MMF assets have rebounded to near their
pre-MMDA peak.
There was also a dramatic, statistically significant decline of $.52 in small-denomination
(less than $100,000) time deposits for each dollar increase in MMDAs. After an actual decline
of nearly $150 billion over a six-month period,
small time deposits resumed their trend growth
rate as the growth in MMDAs tapered off. This
pattern suggests that there was a one-time shift
of funds. The largest decline in the small time
category took place in the popular six-month
money market certificate, which already paid a
near (wholesale) market rate of interest, but
tied funds up for six months.
The impact of the switch from small time accounts to MMDAs on the cost of funds was
probably Il()tt()() large for many institutions.
Nearly all of the funds in the small-time category were already paying near open-market
rates or were tied to those rates by the end of
1982. Still, even though this switch did not directly alter the cost of these funds substantially,
it changed the overall composition of deposits
and shortened the (stated) maturity distribution
for retail deposits.
Both savings (passbook accounts, at the time
paying 5% percent at banks and 51/2 percent at
thrifts) and transactions balances-including
demand deposits, Negotiable Orders of Withdrawal (NOW) and Automatic Transfer Service
(ATS) accounts, and savings deposits authorized for telephone and preauthorized transfers,
but excluding Super-NOWs-also appeared to
fall slightly during the months following the authorization of the MMDA. However, the
regression analysis does not provide evidence
of a statistically significant shift. It is likely that
the declines did not represent actual shifts because of build-ups (evident in Chart 1) in both
savings and transactions balances in the weeks
preceding the authorization of the MMDA.
Knowing that banks would be authorized to offer these short-term market rate accounts as of
December 14, many depositors with maturing
instruments likely held funds temporarily in
transaction or savings accounts until the new
accounts were available.
The lack of a significant shift from savings
accounts into MMDAs suggests that (passbook)
savings accounts must be offering a large service benefit that offsets the binding effect of the
interest ceiling. (The effect of binding interest
ceilings is discussed in the Box.) This confirms
our hypothesis that the gradual erosion of these
accounts had left mainly depositors that prefer
implicit interest in the form of non-taxable services rather than taxable interest. Our findings
are consistent with evidence provided by Furlong (1984) that savings accounts-through
9
10
Figure 1
Tradeoff Between Services and Interest Needed
to Attract a Given Quantity of Deposits
Interest Payments
Added Cost of a Given Quantity
of Deposits Due to Interest Ceiling
R
1--------"-.
Combination of Interest and
Services Needed to Attract
Qo Deposits
Services, Measured in the Dollar
Cost of Providing Them
11
high turnover-provide a substantial transaction service component different from that offered with MMDAs. Thus, the nearly $290 billion in savings deposits currently on the books
are not likely to be shifted suddenly out of savings in response to higher returns on MMDAs.
Surveys of the sources of MMDAs made during the rapid growth period provide results similar to those discussed above, although most indicate a higher proportion of new funds. 4 As
previously discussed, our evidence suggests that
although a significant fraction of MMDA deposits were attracted from the money funds,
these inflows were offset by outflows from
other deposits. Although MMDAs apparently
had only a minor impact on total deposit
growth, they significantly altered institutions'
mix of deposits-increasing retail deposits at
the expense of wholesale deposits-and they
were successful in allowing banks to compete
with the money market funds for retail
deposits.
II. Market Adjustment
MMDAs' very rapid acceptance by the marketplace confirms that there were substantial
cost savings for banks in offering such accounts
and that depositors preferred the combination
of explicit interest, maturity and services offered by MMDAs to those available on at least
some pre-existing accounts. However, because
both banks and depositors would probably experience adjustment costs associated with opening such accounts and shifting funds into them,
the adjustment of actual to desired stocks of
funds in these accounts would not be instantaneous. These adjustment costs have a number
of important implications discussed below.
In theory, the growth of funds in MMDAs
would be determined jointly by households'
and banks' portfolio decisions. Banks, within
the limits imposed by competition, would set
the rates (and other terms) on these accounts,
and consumers could reallocate their portfolios
in response to those rates subject only to the
costs of such reallocations. Banks, of course,
might try to take into account households' responsiveness to interest rates when setting
rates, but households' reallocations might also
depend on their expectations about how banks
would price these accounts in the future. Furthermore, information and other unique transaction costs associated with moving funds into
MMDAs might significantly affect the flow of
MMDA funds.
Adju.stment Costs
As Flannery (1982) and others have shown,
the existence of bank-specific transaction and
information costs mean that retail deposits have
a specific capital component making them a
"quasi-fixed" factor of production. 8 That is, retail deposits are somewhat like specific human
capital in that the transaction and informational
costs involved in opening an account are largely
specific to the bank in question. For example,
a consumer must invest time to learn about a
bank's rate, location and procedures, and must
fill out various forms to open an account. Most
ofthis investment, however, becomes worthless
if the consumer switches to another bank or
investment alternative.
As Becker (1962, 1964) has shown in the human capital context, the cost of specific investments will be shared. If banks paid the full costs
Banks' Demand for MMDAs
Interest ceilings had led banks that were in
competitive markets to substitute nonpriced
services for interest payments and wholesale
deposits for retail deposits. By allowing banks
to attract funds directly through price competition, MMDAs were a lower cost means of attracting funds than had existed previously.s
(See Box.) This regulatory innovation lowered
the average and marginal costs6 of attracting
deposits and simultaneously increased the effective rate paid to depositors, and thereby provided a strong incentive for banks to attract
funds into these accounts as well as a strong
incentive for depositors to shift funds into these
accounts. 7
12
porarily increases, in order to minimize adjustment costs. Over along-run period, however,
deposit costs are equated (on average) to marginal revenue products. Flannery also notes
that ifnon:retail deposits, such. as CDs, have
no or very small specific capital costs, then
banks will use these instruments to meet temporary fluctuations in demand. Thus, it will be
occasionally worthwhile for banks to pay higher
rates on retail deposits than on wholesale funds
such as large denomination CDs to avoid the
adjustment costs associated with changing the
level of retail deposits.
Adjustment costs are likely to be important
for all types of retail deposits regardless of
whether they are newly authorized accounts.
However, unlike existing accounts in which one
can simply deposit a check, virtually all MMDA
deposits in the first few months were new deposits with the associated bank-specific set-up
costs. Because of this, banks could partly compensate depositors for the costs of opening a
new account by paying high interest rates initially. However, for a short-term account like
the MMDA, this strategy is not cost-effective
once a substantial number of new accounts are
opened since high rates would have to be paid
to both new and existing accounts. Thus, one
strategy for banks would be to pay high rates
initially to partly compensate depositors for the
initial bank-specific set-up costs, but to compensate depositors in some other way for the
costs of opening a new account once the rate
of new account formation slowed.
This specific-capital theory of retail deposit
flows implies that the cost and quantities of
such deposits will respond sluggishly or incompletely to changes in wholesale market interest
rates. As Flannery and James (1984) point out,
this means that the effective maturity of a
bank's retail liabilities need not equal their
stated maturity (or time to repricing). Thus,
retail deposits will not be supplied perfectly
elastically, and the short-run interest elasticity
of the supply of deposits to banks will be consi<ierably less than the long-run elasticity.
(and received the returns) of the specific investment associated with opening accounts (by
compensating depositors for the time and
money costs of opening accounts), customers
could. switch accounts with no cost to themselves and therefore would not take into account these bank-specific investment costs.
Banks, in turn, would earn no return on their
investment in set-up expenses. Conversely, if
depositors bore the entire (time and money)
cost of setting up an account, banks could lower
the rates paid without taking into account the
lost investment the depositor would incur in
switching accounts. The theory of specific capital investment predicts, therefore, that the
costs of specific capital investments will be
shared by both parties so that they both at least
partially take into account the effects of their
behavior on these specific investments. Thus,
when an investment has a strong specific capital
component, as does opening an MMDA account, the trading parties share the costs of the
specific investment. This sharing, in turn, provides both parties with an incentive to continue
their relationship to protect their investment.
These shared costs of setting up new accounts
mean that both banks and depositors face adjustment costs when shifting deposits into
MMDAs. For example, if a bank wishes to attract more deposits (at least partially through
deposits into new accounts), it must bear part
of the initial set-up costs as well as pay explicit
interest. Depositors also bear part of the initial
set-up costs. Adjustment costs for depositors
lead to differences in the short- and long-run
interest elasticities of the supply of deposits to
banks, and imply it takes time for actual stocks
to adjust to changes in desired deposit stocks.
Similarly, adjustment costs for banks imply differences in bank's short-run and long-run interest elasticities of the demand for deposits.
As Flannery (1982) points out, these adjustment costs can lead banks to pay rates of interest on deposits in excess of their marginal revenue products in the short-run when demand
temporarily declines, and to pay less than the
marginal revenue products when demand tem-
13
was only two months after the enabling GarnSt Germain Act was passed). Thus, the costs
associated with offering them must have been
greatly exceeded by the expected returns. However, the costs associated with opening. an
MMDA account must have been significant
since it took at least three months for deposits
to reach an "equilibrium" level.
Banks apparently expected substantial longrun cost savings by attracting funds into
MMDAs because many institutions waged aggressive promotional campaigns. Many developed concerted marketing efforts to attract
funds via television, radio and print media and
direct mail. Institutions also employed bonuses
The Market Acceptance of MMDAs
When a new cost-saving technology such as
the MMDA is introduced, the adoption of that
technology is not instantaneous because there
are •costs ill leamillg. about the technology as
well as costs involved in actually adopting the
new technology. The rate at which a new technology is adopted depends on the cost-savings
it affords compared to the information and
other adjustment costs of adopting it. Although
it appeared to take MMDA deposits 3 to 4
months to reach an equilibrium (see Chart 1),
approximately 80 percent of banks nationwide
offered MMDA accounts starting on December
14, when they were first authorized (and which
Chart 2
MMF Rate
VS.
Bank MMDA Rate
Percent
11.0
10.5
10.0
MMF Rate~
(National)
9.5
9.0
8.5
~
MMDA Rate
(Twelfth District)
8.0
1983
1984
Monthly-End of Month
14
rates followed by declines~predicted by the
specific capital
because high interest
rates cannot continue to be used to partly compensate depositors for the cost of opening new
accounts once a substantial number of new accounts have been opened. After May 1983, the
rate on the money funds exceeded that on
MMDAs and was considerably more variable.
This pattern .also is consistent with the specific
capital model which predicts that rates on retail
accounts will behave more sluggishly than
wholesale rates. Also, since MMDAs offer both
federal deposit insurance (not available on
MMFs) and more convenience features (for example, .access through automated teller machines) than money funds, we would expect
MMDA rates generally to be lower than money
fund rates except during periods when interest
rates temporarily decline.
for depositors opening new accounts (an incentive to move funds between institutions) and,
perhaps most importantly, many offered premium interest rates considerably above money
market. fund •. yields .••.This •pricing .• behavior is
consistent with the specific capital model which
predicts that the specific capital investment required to open a new account will be shared by
banks through high initial direct interest payments, through cash bonuses for opening accounts, or both.
In Chart 2, we plot the average rate paid on
MMDAs (in our sample of western banks) and
money funds from the end of 1982 to the end
of 1984. This chart shows that the rates paid on
MMDAs were considerably higher than the
money fund rate in December 1982 and January 1983, but that the rates were close by March
of 1983. This is the exact pattern-high initial
III. Competition for MMDAs
greatest added costs in attracting deposits due
to the inefficiencies of non-price competition.
They would have, in effect, been paying high
rates of interest (explicit plus implicit) on deposits while depositors were receiving low rates
because depositors valued the "free" services
and convenience at less than their cost. Similarly, banks that had substituted wholesale deposits for retail deposits might have different
incentives to shift to MMDA funding than
banks that had substituted nonprice competition for price competition. Also, banks may be
in different loan markets and thus have different demands for deposits. Finally, banks may
be in different markets for other factor inputs,
such as labor and real capital, and thus face
different prices for other factors of production.
These different input prices also would lead to
different demands for MMDAs.
To determine whether banks did differ in
their strategies to attract MMDAs and what effects these strategies had on the time-pattern of
adoption of MMDAs, we employed an empiricalstrategy first suggested by Griliches (1957)
for analyzing the adoption of new technologies.
If, in fact, the costs and benefits of attracting
In this section, we analyze the competition
among banks for MMDAs. Two broad issues
are considered: the determinants of banks' initial patterns of adopting MMDAs and the interest-sensitivity of MMDA deposits. To analyze differences in banks' patterns of adoption
of MMDAs, we employ a logistic model of the
percent of each bank's total deposits in
MMDAs as a function of time. Differences in
the banks' parameters of the logistic are then
modeled as functions of various bank characteristics and pricing strategies. To analyze the
interest-sensitivity of MMDAs, a standard
stock adjustment model of MMDA deposits is
employed. Short-run and long-run, own- and
cross-interest elasticities of the supply of
MMDA deposits to banks are estimated.
The Pattern of Adoption of MMDAs
As theory suggests, different banks would
adopt different strategies to attract MMDA deposits depending on the expected benefits and
costs. Those banks (and depositors) in the most
competitive deposit markets would have the
greatest incentives to switch to MMDAs because these banks would have experienced the
15
MMDAs differ among banks, then we should
expect differences among banks in the timepattern of adoption of MMDAs. For banks in
the aggregate, there was anS-shaped pattern
of adoption (See Chart 1) .. Although we ",ould
expect individual banks to have the same general S-shaped pattern of adoption of MMDAs,
the parameters of this function are expected to
differ among banks because of differing costs
and benefits to them of attracting MMDA
deposits.
To determine empirically whether the parameters of this general function do differ among
banks, we fit separate logistic functions to each
bank's percentage of total deposits in MMDAs
over time. The logistic is an S-shaped function
that captures the evolution over time in the
share of total deposits in MMDAs in each bank.
If the parameters of the logistic-which determine its origin, rate of growth and equilibrium
percentage-differ substantially across banks,
they then can be analyzed as functions of the
banks' strategies for attracting deposits to determine how various strategies affected banks'
time-pattern of adoption of MMDAs.
The logistic9 is defined as:
pet)
=1+
K
e-(a+·6tj
b
the rate of growth of the percent of
deposits in MMDAs
a parameter that positions the logistic on the time scale.
a
The logistiC functiol1, equatio111, is estimated
for each of the 59 banks in our sample using
the first 12 months of data on deposits. The
method of estimation is non-linear least squares
(with Gauss-Newton iterative optimization)
that enables us to estimate the parameters K,
a and b simultaneously. Fits are generally excellent with over 99 percent of the variance explained by the model, and asymptotic t-values
of all parameters significant at the 1 percent
level or better.
Parameter estimates for a, band K (available
on request) show considerable variation across
banks in the time-pattern of adoption of
MMDAs. In Table 1, summary statistics for
these parameters of the logistic are presented.
Comparing the minimum to the maximum, the
parameter a varies by over 2 months; the rate
of growth parameter b also varies by a factor
of 3; and the equilibrium percentage of
MMDAs, the parameter K, varies from as low
as 7 percent to as high as 35 percent. This wide
variation indicates that banks did in fact experience different time-patterns in the adoption
ofMMDAs.
These results also can be used to compute the
time required for MMDAs to reach 90 percent
of their equilibrium value by applying the following formula.
(1)
where:
the percentage of deposits at time t
pet)
in MMDAs
the equilibrium percentage of
K
MMDAs of total deposits (when
t = (Xl)
TABLE
1
Summary Statistics for the Variation in the Logistic Parameters Across Banks
Parameter
_
.. _~
Minimum
Maximum
Standard
Deviation
(origin)
(in months)
a
Mean
-2.63
-4.13
-1.34
.74
3.08
.62
--_...- . _ - - _.. _. - - - - - - .81
(slope)
1.80
(percent per month)
--_._---~~
b
,_._-._---
K
(equilibrium
proportion)
.07
.21
16
.35
.064
T*90%
where: P/K
=
lib {log [P/(K-P)] - a}
the growth rate of MMDAs. Banks with more
branclles experienced less rapid growth of
MMDAsperhaps because their greater convenience made them less constrained by interest
ceilings and thus less willing to promote
MMDAs.Asexpected, high initial rates. on
MMDAs did lead to more rapid growth of these
accounts, but the average rate paid did not affect growth.
In column 2 of Table 2, the equilibrium percentageof MMDAs is analyzed in terms of the
same independent variables. Both Idaho and
Utah had significantly smaller percentages of
deposits in MMDAs than California. We find
that the equilibrium percent of MMDA deposits depends on the mean rate paid over the entire period but not on the initial rates paid in
December and January. We also find that banks
with a strong wholesale presence initially, measured by the percent of large CDs in total deposits, attracted fewer MMDAs. This might
have been expected since banks that focused on
wholesale markets probably would be less likely
to seek retail deposits.
Finally, in column 3 of Table 2 we analyze
the parameter of the logistic that shifts the function horizontally. An increase in this parameter
shifts the logistic to the left (and a decrease to
the right) indicating an earlier start to whatever
pattern of adoption was followed. Banks with
more branches did adopt MMDAs earlier. Not
too surprisingly, neither the initial nor longer
term MMDA rate have a significant effect on
when banks adopted the new account.
In sum, this analysis indicates that the adjustment of the market to MMDAs, while
rapid, was not instantaneous. This result is consistent with the presence of adjustment costs
and differences between short- and long-run interest rate elasticities. Banks that offered
higher initial rates attracted MMDAs more rapidly, but the ultimate percentage of their deposits consisting of MMDAs depended on the
average rate paid over a longer period of time.
Although this cross-sectional analysis of
MMDA deposits does suggest that banks
adopted different strategies for attracting deposits and experienced different patterns of acceptance of MMDAs, it does not provide esti-
(2)
= .90
This formula indicates that, for the "average
bartk"irt()\.l.l'.sample,.MMDA depositsl'eacned
90 percent of their equilibrium level in only 2.7
months, a very rapid rate of adjustment.
To test whether these observed differences in
banks'time-pattern of adoption of MMDAs can
be explained by differences in banks' strategies,
three regressions are performed with parameters of the logistic as the dependent variables.
A common set of economic variables, including
banks' pricing strategies and other variables intended to capture some of the differences in
banks' behavior in attracting MMDA deposits,
are the independent variables.
In all three regressions, we allow for parameter differences among the states (in the
Twelfth District) by including state dummy
variables because banks in different states are
likely to be in different deposit and loan markets. We also control for total deposit growth
during the year prior to the introduction of
MMDAs because it seems likely that banks previously experiencing rapid deposit growth also
would experience more rapid MMDA growth.
Control variables for the absolute size of the
bank, in terms of total deposits in November
1982, the number of branches, and a dummy if
the bank has 5 or fewer branches, are also included· to capture differences in the nonprice
component of payment. The key economic independent variables are the average of the rates
offered in the last weeks of December 1982 and
January 1983-the average of the initial promotional rates-and the average rate paid during the last weeks of the next 10 months. We
expect that banks offering high initial rates
would have more rapid initial deposit growth
but that the equilibrium percentage of deposits
would . depend more strongly on the average
rate paid over time.
In column 1 of Table 2, we find that banks
with more rapid previous total deposit growth
also had more rapid MMDA growth, and that
the size of the bank in terms of total deposits
in November 1982 is also positively related to
17
TABLE
2
Effects of Economic Variables on the Parameters of the Logistic
(Standard Errors in Parentheses)
Speed of
Adjustment
Equilibrium
Percentage
a
59
K
59
b
59
Number of observations
Origin
.05
.63
.46
.62
.46
1.80
.21
-2.63
3.57
(5.08)
- .83*
(.44)
.21
(.35)
.043
(.03)
.09
(.42)
Hawaii
-.35
(.40)
.026
(.035)
.37
(.49)
Idaho
.031
(.44)
- .078**
(.04)
.15
(.53)
~.032
(.38)
.012
( .033)
.34
(.46)
.30
(.36)
.12***
(.03)
1.01 **
(.43)
Standard error of estimate
Mean value of dependent variable
Intercept
State dummy variables:
(California is the omitted category)
Arizona
Oregon
Utah
- .43
(.30)
Washington
-
lO.03E -g"
(4.5E-S)
..
~-,~~,,~,---_.--------~
- - - - - ~ - , __---""~~""'-~'~---~----''''._--''''""-
-
.53
(.35)
- .012
(.061)
-~-------"--'
Total November '82 Deposits
(6.lO)
- .014
(.025)
1.51 **
(.70)
Nevada
~7.69
2.31***
(.84)
--""_._-~-
._-------
-l.35E -7"
(.54E- 7 )
7.7E -10
(39.4E- 10)
-,,------~""---_
...
Large Certificate of Deposits/Total Deposits
.33
(.52)
.16***
(.045)
.lO
(.62)
November '82 Deposits/November '81 Deposits
1.45*
(.77)
.025
(.067)
-.93
(.93)
- 5.()E -3"
Number of Branches
(1.9E- 3)
=
-.35
(.22)
1 if 5 or fewer branches
.2E-5
(16.3E-S)
- .008
(.02)
6.7E-Y"
(2.3E -3)
.13
(.27)
. _ - - ----,,----
A bank's mean MMDA interest rate over Feb. '83-Nov. '83
A bank's mean MMDA interest rate over Dec. '82 and Jan. '83
._--_._,--***Significant at the 1% level
* *Significant at the 5% level
'Significant at the lO% level
18
-7.9E-3
(5.8E- 3)
.004*
(.002)
.0012**
(.0005)
.74E- 4
(1.6E -4)
.011
(.007)
-3.2E"3
(2.2E -3)
we assume that the public's supply function of
deposits is stable compared to individual banks'
demand for deposits, so that the observed variation in interest rates is exogenous. For variation in rates over time, this would seem to be
agoodaSSllmptioIl, bllt as the preceding analysis suggests, there is also substantial exogenous cross-sectional variation in banks' strategies for attracting MMDAs.
Our empirical version of equation 6, which
represents the supply of MMDA deposits to
banks, is as follows:
mates of the short- or long-run cross elasticities
with respect to rates on competitive assets (such
as the rate on money funds), nor does it provide
estimates of the short- or long-run own interest
elasticities of MMDA deposits after the initial
adjiistmerifoccurred. To address theseqties~
tions, we estimate a stock-adjustment model of
the supply of MMDAs to banks by pooling data
on our cross-section of banks over time.
A Stock-Adjustment Model of MMDA
Deposits
Portfolio theory suggests that the desired
stock of a particular asset (MMDA deposits
held by households and businesses), Af, will be
positively related to its own rate of return and
negatively related to the rates of return on substitute assets. Thus,
Af
Af
W
ri
f(rlh,· .. , rj, ... , rn> W),
where:
desired holdings of asset i
wealth
expected rate of return on other
assets, i.
Ln(Q il ) = a + 131 Ln(Qil_l)
+ 132 Ln(Ri, MMDAI ) + 133 Ln(RMMFt )
+ 134 CONTROLi + eit
where:
The quantity (stock) of
MMDA deposits at bank i in
month 1.
the lagged quantity of
MMDA deposits.
the rate bank i pays on
MMDA deposits in month 1.
the average rate on money
market funds during month
(3)
Because adjustment of actual asset stocks to
changes in desired asset stocks is costly, only a
fraction of the difference between desired and
actual asset stocks will be eliminated each period. lO Thus, the actual asset stock of MMDAs
will behave as follows:
LlAil = Ail - A il-l =A (Afl - Ail-I)
1.
CONTROL = a vector of control variables
including: the natural log of
total deposits in November
1982, the growth of deposits
from November 1981 to November 1982, the percentage
of CDs in total deposits .in
November 1982, the natural
log of the number of
branches, a dummy for 5 or
fewer branches, and dummies for each state in the
Twelfth Federal Reserve
District with California
being the excluded category
a random error term
parameters to be estimated.
(4)
where A is the fraction of adjustment per unit
of time of the gap between the desired and actual value of the stock. Rewriting equation (4)
gives:
Ail = AAfl + A il-l (1 - A)
(5)
And substituting equation (3) gives:
Ail = (1 - A) A il-l
(7)
+ Af (r l , ... , r n , W). (6)
In this model, 8f/8ri is the long-run effect of a
change in ri on the (desired) asset stock (which
equals the actual asset stock in the long-run),
whereas A8f/8ri is the short-run, one-period
effect.
In estimating this stock-adjustment model,
This model has four important features.
First, as equation 7 indicates, the coefficient of
InQil-l is an estimate of I-A. Also, the coefficients of the interest rate variables are short-
19
run elasticities (one-period elasticities), but the
long-run elasticities may be found by dividing
the coefficients by "-.
Second, in this model, data from individual
banks are pooled over time. This means that
theertbt term is likely to contain a bank-specific permanent component reflecting permanent unmeasured characteristics of the bank.
As Balestra and Nerlove (1966) discuss, such a
permanent component can cause bias in models
like this one with lagged dependent variables
because the lagged dependent variable captures
the permanent component. To address this
problem, we include a variety of control variables including the size of the bank, both in
terms of deposits and branches in the month
prior to the introduction of MMDAs, the
growth of the bank during the year preceding
the introduction of MMDAs, the percent of
CDs in total deposits in the month prior to the
MMDA introduction (to proxy for the bank's
retail presence), and a set of state dummies to
capture remaining differences in the state market and regulatory environment not captured
by the other variables. We hope that by including these control variables most of any permanent component of the error term will be eliminated. In addition, the effects of the control
variables are of interest in their own right.
Third, we apply this general model to three
different periods: the entire period, the initial
adjustment period following the introduction of
MMDAs, and the post-adjustment period.
These distinctions were made because the logistic analysis suggests that the flow of deposits
into MMDAs was much different during the
first three months after their introduction than
once they had reached an "equilibrium" level.
Thus, it is likely that both the own-and crossinterest elasticity of supply of deposits, as well
as the speed of adjustment, would differ during
the adjustment and post-adjustment periods.
Finally, the functional form of the model is
log-log. This functional form has several advantages when bank-level data are used. With this
form the coefficients of the interest rate variables can be directly interpreted as elasticities.
More importantly, since the banks in our sample vary widely in size (by several orders of
magnitude), the constant-elasticity functional
form is superior on a priori grounds to the linear form. This is because it is highly unlikely
that· a 1 percentage point increase in the
MMDA rate would have the same absolute effecfiouMMDAdeposits in a $20 billion dollar
bank as in a $20 million bank. By using the
constant elasticity, log-log functional form, in
which all analysis is in percentage terms, this
problem is avoided.
In Table 3, coefficient estimates of the model
described by equation 7 are presented. In the
first column, results are presented for the entire
period. The fit is very good and most coefficients are significant at the 1 percent level or
better. Generally, there are significant differences between several states and California in
the intercept of this model. These differences
suggest that MMDAs during the initial adjustment period were more popular in California
than in Idaho, Nevada, Oregon, and Utah
(holding constant all other variables in the
model). This may be because the California
banking market is more competitive.
The results for the entire period (Column 1)
also suggest that the initial size of the bank (before MMDAs were offered) was an important
determinant of MMDAs, with an elasticity of
November 1982 total deposits of .30. That is,
banks with 1 percent greater total deposits attracted .30 percent more MMDAs, all other
things equal. However, as the results in column
3 suggest, this effect of initial deposit size was
much smaller (about one-tenth as large) during
the post-adjustment period.
In December, banks with larger branch networks were more successful in attracting
MMDAs. However, there was not a significant
relationship between the number of branches
and MMDAs in either the post-adjustment or
adjustment periods.
Banks experiencing rapid growth in deposits
prior to the introduction of MMDAs also appear to have attracted more MMDAs (although
the result is not consistent across all time
frames). This result is not surprising since
banks situated in rapidly growing markets
might also experience more rapid MMDA
growth.
20
TABLE 3
Analysis of the Quantity of MMDA Deposits at Banks Over Time
(Standard Errors in Parentheses)
Jclnuary '83
December '84
Number of observations
Janua.ry '83
February '83
Ma.rch '83
December '84
1416
118
Decernber· '82
1288
59
Standard error of
.12
.15
.043
.48
R2
.996
.995
.9995
.96
----
Mean of dependent variable
Anti-log of mean ($1000s)
Intercept
State dummies (California excluded)
Arizona
11.83
11.56
11.86
$137,749
$104,820
$141,492
$35,596
.08
(.
-22.19**
(9.76)
- 4.81***
(.41)
396.06***
(58.38)
.03***
(.01)
10.48
.0038
(.06)
.006
(.005)
.58*
(.29)
Hawaii
-.02
(.02)
- .15**
(.06)
.001
(.006)
-.085
(.30)
Idaho
- .17**'
(.01 )
- .22*"
(.07)
-.006
(.006)
-.041
(.41 )
Nevada
- .10*'*
(.03)
- .37***
(.12)
-.002
(.01)
-.72
- .05**'
(.01)
- .17***
(.06)
.002
(.005)
.24***
(.01)
- .21 ***
(.07)
-.01
(.006)
- .07***
(.01)
.14***
(.05)
.0005
(.004)
.11
(.26)
Ln (Nov. '82 Deposits)
.30***
(.01)
.38***
(.04)
.03***
(.005)
.56***
(.17)
Nov. '82 Deposits/Nov. '81 Deposits
.15***
(.03)
.033
(.16)
.02*
(.01)
l.O87
(.71)
Large CDs/Total Deposits, Nov. '82
- .28***
(.03)
.46***
(.13)
.05***
(.01)
.71
(.59)
-.052
(.043)
.0001
(.004)
.52***
(.18)
.002
(.01)
.08
(.06)
.006
(.005)
Ln (Lagged MMDA quantity at Bank i)
.67***
(.01)
.65***
(.04)
.97***
(.005)
Ln (Rate on MMDAs at bank i
at time t)
1.56***
(.08)
Oregon
Utah
Washington
(.56)
.62*
(.34)
.97***
(.30)
~-~,~"-----~~~-"
Ln (Number of Branches)
.04***
(.01)
----_.~-~-
1 if 5 or fewer branches
-.023
(.26)
"-"_._----,."---"-_.~._-----,,~---
Ln (Rate on MMFs at time t)
.08
(.28)
- .60***
(.09)
- .86**'
(.04)
.19***
(.04)
3.18**
(1.32)
- .21 ***
(.02)
-------_._--"'-_.-
21
The coefficient of the lagged dependent variable does suggest that adjustment is not instantaneous and hence not costless. However, during the initial adjustment period (Column 2),
the. estimates suggest that an adjustment of
about 35 percent of the difference between actual and desired stocks occurred per month.
This result indicates that over 70 percent of the
adjustment to the new equilibrium occurred
within 3 months. This rate of adjustment is not
too different, although it is somewhat slower,
than that obtained from the logistic analysis.
However, during the post-adjustment period
(Column 3), adjustment is much more sluggish,
with an implied rate of only 3 percent per
month. This result also is consistent with the
notion that the costs of setting up new accounts
are much different than the costs of adjusting
deposit balances in existing accounts. In fact,
the bank-specific capital model predicts that
once new accounts are established, both banks
and consumers will behave in such a way as to
make relatively few adjustments in the quantity
of funds in the accounts. This would lead to
high serial correlation and a slow adjustment.
The own interest elasticity for the entire period (Column 1) suggests that the accounts were
sensitive, at least in the long-run, to the rate
paid on them. For example, the short-run elasticity was 1.56 and the long-run elasticity 4.73.
However, it should be noted that these are
firm-level elasticities that are expected to be
large in competitive markets.
During the post-adjustment period (Column
3), MMDAs were much less interest-sensitive,
with a statistically significant short-run own
elasticity of about .19. Also, during this period,
the estimated speed of adjustment was dramatically less-only 3 percent per month. This result is not unexpected given the existence of
bank-specific capital costs. However, even during this period, the long-run elasticity was approximately 6.33.
To see whether the high initial rates were successful in attracting MMDAs, the model without the lagged dependent variable (which is minus infinity) and the money fund rate (which is
constant in anyone month) is estimated for De::""
22
cember (Column 4). The results suggest a very
high initial interest elasticity of over 3. That is,
banks with 1 percent higher MMDA rates attracted over 3 percent more MMDA deposits
by the end of December.
The results in Table 3 also suggest that money
funds provide important competition to
MMDAs. We find a statistically significant
shorHun cross elasticity of MMDAs with respect to rates paid on money funds of about .21
(Column 3), confirming that these two accounts
are substitutes. This result is consistent with the
sizable initial runoff of money funds into
MMDAs.
The money fund rate in this model, however,
plays a dual role. Although it is a measure of
the return on an alternative substitute asset, it
is also a proxy for market rates in general.
Thus, we probably have overestimated the
cross elasticity of money funds with MMDAs
because a higher money fund rate may simply
indicate high MMDA rates being paid at other
banks. Attempts to measure the effects of both
the money fund rate and the average rate of
MMDAs proved unsuccessful, probably because of the high correlation and limited independent variation in these two rates.
One of the major uncertainties surrounding
the introduction of the MMDA was its interestrate sensitivity. If MMDAs were very sensitive
to interest rates, banks could attract inflows
with marginally higher interest rates and
MMDAs would be a relatively unstable and
costly source of funds whose rate would behave
very much like rates on money funds, or other
wholesale market return instruments.
If, on the other hand, MMDAs were relatively insensitive to interest rates, then deposits
would be less likely to shift from institution to
institution without large or permanent rate differences. Thus, institutions potentially would
benefit by having a stable source of retail funds
whose effective maturity exceeded its stated
maturity and whose cost varied much less than
wholesale deposits.
Although our results suggest that MMDAs
are quite interest-sensitive in the long-run, they
also support the notion that MMDAs are not
component than wholesale deposits such as
large CDs.
very interest-sensitive in the short-run. Thus,
MMDAs appear to behave more like retail deposits with a significant bank-specific capital
IV... Summary and Conclusions
In this paper, the competition for MMDA deposits-both interbank as well as with the
money funds-is analyzed. The analysis focuses
on four areas: (1) the sources of the MMDA
deposits, (2) the pattern of adoption by banks
and the public of these new accounts, (3)· the
pricing of these accounts and (4) the interestsensitivity of these accounts in both the shortand long-run and with respect to their own rate
as well as the rates on money fund assets. Several findings emerged.
The MMDA deposits came primarily from
the money funds, small time deposits, and large
CDs. Although MMDAs attracted approximately $90 billion from the money funds, the
money funds have continued to prosper in the
face of competition from the MMDAs. The
MMDA did not, on average, appear to lead
banks to increase the overall quantity of their
liabilities substantially, but it did enable them
to increase substantially their quantity of retail
deposits thus reducing their dependence on
wholesale deposits (large CDs). To the extent
that banks' primary comparative advantage is
in providing intermediation services at the retail level, the MMDA has enabled banks to
strengthen greatly their competitive position in
the retail deposit market. By reducing their reliance on purchased funds, it may actually have
improved their ability to borrow in the wholesale markets as well.
This suggests that banks' primary responses
to Regulation Q were to substitute wholesale
for retail deposits, and nonprice competition
for direct price competition in attracting funds
to these. accounts. Both responses apparently
increased banks' deposit costs.
The facts that the money funds lost only a
fraction of their deposits to the MMDAs and
that their cross elasticity was statistically significant but not too large suggest that the money
funds and MMDAs are substitutes, but not as
close substitutes as some had anticipated. This
is not surprising since money funds had taken
numerous actions aimed at reducing potential
outflows. With the authorization of the
MMDA, many money funds lowered their minimums to well below the statutory MMDA minimum, and increased the services their products
provided, for example, by linking accounts to
brokerage services and providing easy access to
other funds (often called families of funds), and
by specializing in short-term investments in taxexempt securities, riskless securities or high
risk/high return securities. We also find in our
analysis of aggregate data that because the
MMDAs are not substitutes for transaction accounts, there is little reason to expect them to
have affected the M1 measure of the money
stock.
The adoption of MMDAs was very rapid.
Most banks offered such accounts on the day
they were authorized and the quantity of funds
in these accounts reached over 90 percent of its
equilibrium value within 3 months. The rate of
adoption by depositors depended on the initial
promotional rates offered by banks whereas
each bank's equilibrium percentage of deposits
in MMDAs depended on the average rate paid
over a longer period of time.
Most banks paid very high initial rates on
MMDAs, but once the rate at which new accounts formed declined, rates dropped below
the level offered by the money funds. This type
of pricing behavior is consistent with large
bank-specific set-up costs associated with opening new accounts. Theory predicts that such
specific capital costs will be shared by banks
and their customers and high initial rates are
one way of doing this. In addition, the rates
paid on MMDAs have been less volatile and
generally below wholesale rates after the initial
adjustment period-a type of pricing behavior
also consistent with the specific capital model.
23
much slower because of the existence of significant bank-specific capital costs. These costs
meant that, once accounts were opened, deposits would shift only slowly in response to
il1terbank interest differentials. This implies
that the effective maturity (or duration) of
MMDAs is considerably longer than their
stated maturity, or time to repricing.
In sum, MMDAs have been an important innovation in the retail banking market. They
have offered retail customers a more valuable
package of explicit compensation and implicit
services than had existed previously. On the
banking side, banks have been able to substitute retail for wholesale deposits and price competition for nonprice competition, thus securing
a more stable and lower cost source of deposits.
The speed with which MMDAs were adopted
suggests that depositors viewed them as being
superior to existing retail accounts, especially
small time accounts (from which a significant
fraction of the funds came). The fact that banks
promoted these accounts so widely and paid
such high initial rates suggests that banks had
faced substantial costs in their nonprice competition for retail accounts and in their substitution of wholesale for retail accounts to mitigate the economic forces of disintermediation
due to Regulation Q.
The MMDAs were fairly interest-sensitive
(even in the short-run) during the initial promotional period and this quality made the initial adjustment of actual to desired asset stock
levels rapid. However, once MMDAs reached
an equilibrium level, further adjustment was
Data Appendix
Data analyzed in this study were collected by
the Federal Reserve Bank of San Francisco's
Statistical and Data Services Department for
the Monthly Survey of Selected Deposits and
Other Accounts (FR 2042) and the Report of
Transaction Accounts, Other Deposits, and
Vault Cash (FR 2900) reports. The FR 2042
data are collected from a stratified sample (by
size) of sixty-four banks in the eight western
states. Total time deposits of these banks account for about eighty-two percent of the total
time deposits of all insured banks in the Twelfth
District. Both outstanding dollar amounts as of
the last Wednesday of the month, and the most
common interest rate paid during the week
ending on the last Wednesday of the month, are
reported for a number of deposit categories,
including MMDAs, Super-NOWS and several
other time certificate categories. Additional deposit data for these banks were taken from the
daily FR 2900 report. In particular, total domestic deposits, and total large denomination
time deposits were used as control variables in
the study.
Aggregated bank and thrift data for the nation were provided by the Division of Research
and Statistics, Board of Governors of the Federal Reserve System. Data were not seasonally
adjusted, and most are available from the
Board of Governors' H.6 press release entitled
Money Stock Measures. For our analysis, the
large time deposits series used was the gross
series, which includes money market fund and
thrift holdings of large certificate of deposits.
Additional information on money market
fund rates, and bank and thrift interest rates
were taken from Donoghue's Moneyletter and
the Bank Rate Monitor respectively.
Bank structure and branch measures are derived from the annual Summary of Deposits
Survey taken by the Federal Deposit Insurance
Corporation, and published yearly under the
title, Data Book, Operating Banks and
Branches.
24
ApPENDIX
TABLE 1
Features
Account Type
Money Market
Deposit Account
(MMDA)
MINIMUM BALANCE:
Before Jan. 1, 1985
Jan. 1, 1985 to Jan. 1, 1986
Money Market
Mutual Fund
(MMF)
Yes
Yes
Yes
Yes
ELIGIBILITY:
Individuals
Business
Non-Profit
GovefIlment
Super-NOW
Account
Yes
No
Yes
Yes
Yes
Yes
Yes
Yes
$2,500
$1,000
$2,500
$1,000
$1 and up
$1 and up
Set by
Institution
Set by
Institution
Determined
by return on
fund's portfolio
Insured by
FDIC or FSLIC
Insured by
FDIC or FSLIC
Not
Insured*
12%
12%
None
None
.~---
INTEREST RATE:
INSURANCE:
~~~~~~-
RESERVE REQUIREMENTS:
Personal Accounts
Non-Personal Accounts
._.. _ - - - - - - - _..._.._ . _ - _ . _ - - - - - -
None
3%
TRANSACTION FEATURES (Number per month:)
Total Transactions (Including Checks)
Maximum Check Transactions
In Person Transactions
Varies, but
most are:
Six
Three
Unlimited
Unlimited
Unlimited
Unlimited
Unlimited
Unlimited
nla
MINIMUM DEPOSITS:
No statutory
minimum
No statutory
minimum
Varies,
$1 and up
MINIMUM CHECK:
No statutory
minimum
No statutory
minimum
Varies,
$1 and up
*At present only a few money market funds have private insurance coverage.
25
FOOTNOTES
1. The Depository Institutions Deregulation Committee
(DIDC) created the Super-NOW account. This account,
which became available on January 5,1983, was a ceilingfree checking account without limitations on transactions
intendedt6be cOI11J:>etitive withthernoney funds.
5. See Keeley (1984) and Keeley and Zimmerman (1984)
for a discussion of the effects of ceilings on deposit costs.
Also see Benston (1964), Startz (1983) and Rogowski
(1984).
6. It should be noted that these marginal and average (interest plus non-interest) costs relate to a given maturity
deposit at a given point in time. That is, for a deposit of a
given maturity at a particular point in time, the elimination
of interest ceilings reduces its marginal and average costs.
This concept differs from that of differences in marginal
and average costs for long-term deposits at differentpoints
in time due to the possibility of attracting new Ipng. term
deposits at different rates than are being paid on existing
long-term deposits that had been acquired earlier.
2. See Rosen and Katz (1983), Fortune (1975), King
(1984), and Garcia and McMahon (1984) for examples of
studies of aggregate deposits.
3. The regreSsion model controls for changes in SuperNOWs, total liquid assets in the economy, a time trend, and
seasonal factors. The estimation period was from January
1979 to June 1983. The results from this regression are as
follows:
A $1.00 Change in MMDAs Has the Following Impact
(Standard Errors in Parentheses)
Effect
(in dol/ars)
Dependent Variable
Change in Small Denomination Time
- .52***
Deposits
(.15)
Change in Large Denomination Time
Deposits
7. This analysis along with the smaller market for unlimited
transaction accounts may explain why Super-NOWs were
much less popular than MMDAs. Since Super-NOWs were
close substitutes for existing checking and NOW acpounts
in terms of the services they provided and in terms of reserve requirements, one would expect Super-NOWs to
grow rapidly only if the interest ceilings on checking and
NOW accounts were binding. However, even with interest
ceilings, most banks imposed fees, at least for small depositors, on such accounts. Thus, for such small depositors, the ceilings were not binding. Only for largedepositors, for which the ceilings likely were binding, would there
be any gain for the banks and depositors in shifting to
Super-NOW accounts.
8. The concept of a quasi-fixed factor of production is due
to Oi (1962).
- .42***
(.09)
Change in Savings Deposits
-.07
(.15)
Change in Transaction Deposits
+.06
(.07)
Change in Total Deposits Except MMDA
and Super-NOW Deposits
9. The logistic function is asymptotic to 0 and K and symmetric around the inflection point. Its first derivative with
respect to time is given by:
- .96***
(.07)
dP
b K [K - P(t*}]
dtt=t,
Change in Total Deposits
Change in Money Market Mutual Fund
Assets
---~------
P(t*}
+.04
(.07)
That is, the rate of growth of the logistic is inversely proportional to the growth already achieved and directly proportional to the distance from the ceiling.
-.24*
(.13)
In other words, ~--,-og [P/(~-P}]
dt
***Significant at the 1% level
**Significant at the 5% level
*Significant at the 10% level
b.
10. Griliches (1967) has shown that if the costs of adjustment are a quadratic function of the amount of adjustment,
and if the costs of being out of equilibrium are also a quadratic function of the amount one is out of equilibrium, only
a fraction of the difference between the desired and actual
stock will be eliminated each period.
4. See Furlong (1983).
26
REFERENCES
Baltensperger, Ernst, "Alternative Approach to the Theory
of the Banking Firm," Journal of Monetary Economics,
Vol. 6, 1980, pp. 1-37.
Griliches, Zvi, "Distributed Lags: A Survey," Econometrica,
Vol. 35, pp. 16-49, 1967.
Griliches, Zvi, "Hybrid Corn: An Exploration in the Economics of Technological Change," Econometrica, Vol. 25,
No.4, October 1957, pp. 501-522.
Becker, Gary S., Human Capital: A Theoretical and Empirical Analysis with Special Reference to Education,
New Vork: National Bureau of Economic Research,
1964.
Keeley, Michael C. and Gary C. Zimmerman, "Deregulation
and Bank Profitability," Weekly Letter, Federal Reserve
Bank of San Francisco, July 13, 1984.
Becker, Gary S., "Investments in Human Capital: A Theoretical Analysis," Journal of Political Economy, Vol.
70, Oct. 1962, pp. 4-49.
Keeley, Michael C., "Interest-Rate Deregulation," Weekly
Letter, Federal Reserve Bank of San Francisco, January 13, 1984.
Benston, George E., "Interest Payments on Demand Deposits and Banks Investment Behavior," Journal of Political Economy, October 1964, pp. 431-449.
King, Thomas A. "Thrift Institution Deposits: The Influence
of MMCs and MMFs," Journal of Money, Credit and
Banking, Vol. 16, No.3, August 1984, pp. 328-334.
Brainard, William C. and James Tobin, "Econometric
Models: Their Problems and Usefulness: Pitfalls in Financial Model Building," American Economic Review,
Vol. 58, May 1968, pp. 99-122.
Klein, Michael A., "A Theory of the Banking Firm," Journal
of Money, Credit and Banking, Vol. 3, May 1971, pp.
205-218.
Flannery, Mark J., "Retail Bank Deposits as Quasi-Fixed
Factors of Production," American Economic Review,
Vol. 72, No.3, June 1982.
Nerlove, Marc and Pietro Balestra, "Pooling Cross-Section
and Time Series Data in the Estimation of a Dynamic
Model: The Demand for Natural Gas," Econometrica,
Vol. 34, No.3, July 1966, pp. 585-612.
Flannery, Mark J. and Christopher M. James, "Market Evidence on the Effective Maturity of Bank Assets and
Liabilities," Journal of Money, Credit and Banking, Vol.
16, No.4, November 1984, Part 1, pp. 435-445.
Oi, Walter V., "Labor as a Quasi-Fixed Factor," Journal of
Political Economy, Vol. 70, December 1962, 538-555.
Rogowski, Robert J., "Pricing the Money Market Deposit
and Super-NOW Accounts in 1983," Journal of Bank
Research, Summer 1984, pp. 72-81.
Furlong, Frederick T., "New Deposit Instruments," Federal
Reserve Bulletin, Vol. 69, No.5, May 1983, pp. 319326.
Furlong, Frederick T., "New Limits for the New Vear,"
Weekly Letter, Federal Reserve Bank of San Francisco, December 28, 1984.
Rosen, Kenneth T. and Larry Katz, "Money Market Mutual
Funds: An Experiment in Ad Hoc Deregulation: A
Note," The Journal of Finance, Vol. XXXVIII, No.5,
June 1983.
Fortune, Peter, "The Effectiveness of Recent Policies to
Maintain Thrift-Deposit Flows," Journal of Money,
Credit and Banking, August 1975, No. 7(3), pp. 297315.
Startz, Richard, "Competition and Interest Rate Ceilings in
Commercial Banking," Quarterly Journal of Economics, May 1983, pp. 255-265.
Zimmerman, Gary C., "As the Dust Settles," Weekly Letter,
Federal Reserve Bank of San Francisco, October 1,
1983.
Garcia, Gillian and Annie McMahon, "Regulatory Innovation: The New Bank Accounts," Economic Perspectives, The Federal Reserve Bank of Chicago, Marchi
April 1984, pp. 12-23.
27
Bharat Trehan*
Knowledge of changes in private credit aggregates is useful in
interpreting the money/GNP relationship because it helps to distinguish shifts in asset demands by households from changes in the
demand for transactions balances by firms. This is necessary because both these changes have the same impact on money and interest rates but have different implications for future GNP.
changes in output as firms increase their demand for transactions balances in order to finance plans to increase future output.
Within this framework, we first examine the
relationship between money and credit.
Changes in both credit and money precede
changes in output, and we show that changes
in credit provide information in addition to that
provided by both monetary aggregates and interest rates. Our findings indicate, in fact, that
without knowledge about what has happened
to private credit, it is difficult to determine
what a change in money growth means for the
future course of economic activity. In contrast,
the connection between government borrowing
and future economic activity is not as clear-cut,
and the empirical results indicate that government borrowing does not provide reliable information about future economic activity.
The key point of this paper is that information on credit can help distinguish between disturbances to money demand-money demand
"instability", in other words-and disturbances
to credit demand, which also affect the stock of
money because the demand for credit is in fact
a demand for payments media. Positive disturbances to either will lead to increases in the
quantity of money and to a rise in interest rates.
However, the future course of economic activity depends upon precisely where the disturbance originates. Information on credit aggregates is useful because it provides a means for
pinpointing the source of the disturbance. Em-
There exists a large body of work documenting movements in narrowly defined money
(Ml) as leading movements in economic activity. The monetarist tradition regards this as evidence of causation, running from money to
GNP. However, even casual empiricism suggests that this relationship has not been very
stable recently. The first example is the sharp
decline in the velocity of Ml over the second
half of 1982 and the beginning of 1983 (see
Judd, 1983, for a discussion). The second example is the sharp slowdown in the growth rate
of money during the second half of 1983 (when
money slowed from a 12.4 percent annual rate
in the first half to a 7.2 percent rate in the sece
ond), which was followed by an unusually high
rate of GNP growth in the first half of 1984.
(For a more formal analysis of recent shifts in
the money-GNP relation see Simpson, 1984.)
These episodes underline the need for obtaining information beyond that contained in
the monetary aggregate when predicting future
output. Towards that end, this paper examines
what information can be obtained from movements in credit aggregates. A simple model is
sketched out in which the money-output relationship over the business cycle is motivated in
a way that is the opposite of the usual monetarist story. Changes in money growth precede
* Associate Economist, Federal Reserve Bank
of San Francisco. David Taylor rendered valuable research assistance.
28
pirical analysis supports this hypothesis. Section IV presents equations for real and nominal
GNP as well as equations for M1 velocity, and
shows that changes in several types of private
credit are significant in explaining changes in
those variables.
I. Households' Demand fOr Money
Since households operate under a wealth
constraint, any change in money holdings not
accompanied by a change in wealth must be
matched by an opposite change in the holdings
of other assets. In the simplified model considered below, the only other asset available to
households consists of loans to firms. Thus, an
increase in the demand for money must be offset by a decrease in the supply of loans. More
generally, the point is that changes in households' asset demand for money will affect credit
market conditions. Below, we show how this
leads to a role for credit aggregates in predicting future activity.
Before doing that, however, it is useful to
examine what factors can cause changes in
households' demand for money and to discuss
how relevant these factors are likely to be. Intuitively, it appears that expectations about future conditions are important determinants of
the households' demand for money. For instance, Friedman and Schwartz state that expectations of instability due to the outbreak of
war cause money demand to go Up.1
Perhaps a more obvious example of a period
during which the household demand for money
will increase significantly is a recession. When
a recession occurs, or is perceived as likely to
occur, individuals tend to become more cautious and to retain money balances since they
think that there is a greater chance of being
unemployed. Furthermore, the more severe or
prolonged the recession, the greater the shift in
households' expectations of future income. As
a consequence, the increase in money demand
will be higher as well.
Some evidence consistent with this hypothesis is provided by the behavior of velocity during recessions. (Recall that velocity is defined
as the ratio of real GNP to real money balances,
so that an increase in money demand due to
expectational factors leads to a decline in velocity.) The first example is the behavior of velocity during the period from late 1982 through
early 1983. The fact that the 1982 recession was
the worst since the Great Depression and that
it followed very closely on the heels of the
recession in 1980 must have made a substantial
psychological impact on households, leading to
an increase in money demand. 2 Exactly the
same thing happened during the Great Depression: Ml velocity declined practically continually from the first quarter of 1929 to the first
quarter of 1933, with the sharpest declines occurring in three of the last four quarters of this
period. While both the examples above are
rather extreme, they provide some support for
the hypothesis that expectational factors are important determinants of money demand.
Previous researchers have, of course, considered the role of movements in various credit
aggregates in forecasting economic activity.
Perhaps the most well-known is the work done
by Benjamin Friedman (see Friedman, 1985,
and the references there). In contrast to the
approach below, his work focuses on the determinants of asset demands to show why credit
aggregates matter. It relies heavily upon the observed stability of the debt-income ratio in the
post-war period (see Friedman, 1981). Friedman also showed that movements in domestic
nonfinancial debt contained information at
least as useful as any of the monetary aggregates about movements in GNP. However, subsequent empirical research has shown that at
least some of his results hinge upon econometric technicalities (see Porter and Offenbacher,
1983, and Froewiss and Judd 1979). Moreover,
the ratio of nonfinancial debt to income has
been rising since 1980.
29
II. A Simplified Model
Businesses have two sources from which to
borrow: banks and households. It is assumed,
for simplicity, that households do not borrow
from banks, although they add to or reduce
their holdings of bank balances by withdrawing
or depositing currency. (It is also assumed that
the supply of currency is perfectly elastic, that
is, the monetary authority supplies the amount
of currency demanded.) Thus, firms are the
only borrowers. Which source firms draw on
for their funds, however, is critical in determining how money and credit behave and, in particular, in determining which will be a better
indicator of future economic activity. In the
event firms borrow from banks, new transactions deposits are created that add to the stock
of money outstanding. In contrast, business
borrowing from households simply transfers
transactions deposits from households to firms.
In the former case, both money and credit are
affected; in the latter, only credit.
The importance of information about credit
aggregates can be shown in a simple framework
in which there are only three types of decisionmakers: firms, households and banks.
In this framework, we assume that firms desire to increase output levels as a result of positive shocks to productivity (King and Plosser,
1984). Positive shocks to productivity could occur, for instance, when new technology makes
it profitable for firms to increase production.
Because production planning and implementation takes time, firms wishing to produce
more tomorrow must begin accumulating the
needed productive resources today. Not all the
funds needed by a firm are likely to be available
internally, so it must borrow. It is worth pointing out that this accumulation of money balances for future use is what Keynes called the
finance motive for holding money, describing it
as the "coping stone" of the liquidity theory of
money demand.
Figure 1
Credit Market Equilibrium
r~
Q~
Q~
Bank Loan Market
Household Loan Market
30
Qh
reserves necessary to support the new deposits
come from several sources: from an inflow of
currency from the public as banks raise the rate
they are willing to pay on deposits; from banks
reducing their holdings of excess reserves; and
frOll partial accollllodation of the increase in
bank credit by the monetary authority.3 Notice
that the bank loan supply curve is based on
maximizing behavior by the banks and, in the
absence of rigidities or imperfections, this implies equilibrium in the bank reserves market.
Figure Ib shows the market for household
lending to firms. Business demand for loans
from households, HLD , is negatively related to
the rate charged on these loans, rh' and (implicitly) positively related to the rate firms must
pay for bank loans, rb. The supply of household
loans, HLs , responds positively to rho It is negatively related to the rate banks pay on deposits, rd' with households offering a smaller supply of loans to businesses when banks pay a
higher return on deposits.
We are now in a position to examine why
changes in the quantity of credit provide useful
We turn, now, to a diagrammatic exposition
of the analytic framework in this paper. Three
markets are of interest in the model: the market
for bank loans; the market for household loans,
that is, lending by households to firms; and the
market for bank deposits. In Figure 1, o111ythe
markets for bank loans and household loans are
shown. The deposit market is redundant in the
sense that developments in the deposit market
can be incorporated in what happens in either
the household loan or the bank loan market.
In the market for bank loans, Figure la,
firms' demand for bank loans is represented by
BLD . The quantity of bank loans demanded increases with a lower bank loan rate, rb. Also,
BLD is implicitly a function of the rate households charge for loans to businesses, with a
higher household loan rate, rh, increasing firms'
demand for banks' loans.
The supply of bank loans varies directly with
the rate of interest on loans and inversely with
the rate that banks must pay for their deposits,
rd. An increase in rb induces banks to lend
more, creating new deposits for funding. The
Figure 2
An Increase in the Demand for Credit
BL~
o~
06
Bank Loan Market
Q~
Q~
Household Loan Market
31
Now, consider an alternative scenario. Assume that household demand for money increases, so that the supply of credit by households declines. In Figure 3 below, two things
happen. First, the HLs curve shifts from Hq
information about the future course of the
economy. To see this, two different situations
are contrasted below.
Consider, first, what happens when firms decide to supply greater output in the next time
period. If the increased demand for credit is
manifested first in the market for bank loans,
the demand curve BLD shifts from BL? to BL~.
The resulting increase in rb forces some firms
into the nonbank market, that is, HLD shifts
out. Consequently, rh increases. Arbitrage between the two loan markets will continue until
interest rates are brought back into equality.4
In equilibrium, the quantity of both bank and
nonbank loans has increased and so has the rate
of interest. Since loans are positively related to
deposits, both deposits and money supply are
higher as well. In the context of the present
model, both the interest rate and the money
supply provide evidence of increased demand
for credit and predict increased output in the
next period.
toHq.
Second, since households do not lend this
money to firms, but hold it as deposits, banks
can use the money to make new loans. Thus,
the bank loan supply curve shifts from Bq to
BL~. Note that the increase in loan supply by
banks will be smaller (in absolute terms) than
the decrease in loan supply by households for
two reasons. First, households will not increase
deposit holdings by the exact amount of the increase in money demand (or decrease in loan
supply) because part of their money holdings
will be held as currency. Second, banks will not
be able to lend out the entire amount of the
increase in deposits because of the existence of
reserve requirements.
Figure 3
An Increase in the Household's Demand for Money
BL~
r~
r~
06
06
Ofi
O~
Household Loan Market
Bank Loan Market
32
Now, as a result of these shifts, rh exceeds rb'
Therefore, firms will begin to move from the
household loan market to the bank loan market. As a result HLD moves in and BLD moves
out. Thus, the two rates move towards each
other and equilibrium is restored when the two
are equal. At the new equilibrium, interest
rates will be higher than before. This follows
because as a result of a decrease in the willingness to lend; total credit supply has declined
with no shift in the demand for credit. The new
equilibrium interest· rates are Tt; and r~. Since
bank loans have increased, the quantity of
money will be higher as well.
Thus, as far as the impact on money and interest is concerned, this scenario is no different
from the first one. But the implications for future GNP are entirely different. In the first
case, higher interest rates and money were indicators of a future rise in GNP. In the second,
there is no such implication. Indeed, to the ex"
tent that higher interest rates discourage economic activity, future GNP will be lower in this
case.
The only way to discriminate between the
two cases is to look at the credit aggregates.
Non-bank credit (household lending) increases
in the first, but declines in the second. This
difference in performance provides a way of
discriminating accurately between the two
cases. Movements in total private credit-bank
plus non-bank lending-similarly allow one to
discriminate between the two. 5
It is tempting to conclude that changes in
government borrowing will play the same sort
of role as private borrowing did in the model
above. However, for this to be true, changes in
government borrowing must be causally related
to changes in future economic activity. An important reason that this may not be true has to
do with the procyclical nature of the budget deficit. During recessions, for example, tax revenues decrease while outlays increase because of
higher cyclically sensitive government expenditures such as unemployment benefits. Thus,
government borrowing goes up during periods
when income is low. However, this borrowing
is intended to cushion household income from
cyclical vagaries and does not directly influence
future output. This source of borrowing will,
therefore, offset any positive correlation between future output and federal borrowing due
to the other federal expenditures. Thus, it is
likely that changes in federal borrowing will not
provide useful information about changes in future output.
III. Empirical Tests
tivity and also be important in explaining
money growth. This section presents empirical
tests for both these propositions.
First, several alternative "forecasting" equations for real output have been estimated with
the intent of testing whether changes in private
credit predict changes in output. These equations are similar to those presented in earlier
work, for instance, Friedman (1983). The basic
equation includes real federal high employment
expenditures and real money balances as explanatory variables. To this, the real rate of interest and alternative credit measures have
been successively added and tests made to determine the significance of the additional
variables.
Second, essentially the same equation has
The discussion above is based primarily on
two hypotheses. First, firms borrow money to
increase production over the course of the business cycle. Thus, changes in credit lead changes
in economic activity. Further, since firms satisfy
part of their needs by borrowing from banks,
and since loans by banks and demand deposits
are positively correlated, changes in money
lead changes in economic activity as well. Second, the household demand for money function
is subject to shifts due to changes in expectations. These shifts in the money demand function will be reflected in the demands for other
financial assets, such as the financial liabilities
of firms.
Thus, movements in private credit should
provide significant information about future ac-
33
been estimated for nominal GNP. The attraction in estimating such an equation is that the
results are directly comparable to previous research. For instance, the well-known "St.
Louis" equations (from the Federal Reserve
Bank of St. Louis) also regress GNP on money
and High Employment Federal Expenditures.
(Note, however, that the St. Louis equations
view money as being exogenous, that is, all
changes in money are viewed as being policyinduced.)
Finally, an equation for velocity is estimated
to test the money demand implications. The velocity equation is derived from a money demand specification in which the demand for
money is expressed as a function of income and
interest rates and in which nominal money balances adjust to desired balances with a lag. Different credit variables are then included in this
basic equation to determine whether they help
predict movements in velocity.
Quarterly data was used over the period
1959:Ql to 1984:Q2. The beginning date is dictated by the availability of the Ml series. The
interest rate used is the three-month Treasury
bill rate. All credit variables are expressed as
flows. Of the different measures of credit employed below, the widest aggregate is Domestic
Nonfinancial Debt (which is the variable used
by Benjamin Friedman). This is decomposed
into Federal Debt and Private Debt (the latter
is not strictly accurate since it includes state and
local government borrowing).
Finally, two other measures are also considered-totalloans by commercial banks and total loans by financial institutions other than
banks. This is in line with the discussion above,
which distinguished between bank and nonbank sources of credit. Obviously, these variables are not ideal for the purpose at hand. For
instance, because banks may, in the short run,
vary managed liabilities such as Certificates of
Deposit when the volume of loans changes, the
loans-to-money link may not be as tight. Similarly, loans by financial institutions serve only
as a proxy for loans by households.
Consider now, the real GNP equations in Table 1. The dependent variable is the rate of
growth of real GNP. For all independent vari-
ables, except the rate of interest, the GNP deflatorhas been used to transform nominal values to real values. The real rate of interest has
been obtained by subtracting the expected rate
of inflation (in terms of the GNP deflator
again) from the nominal rate of interest. The
expected rate of inflation is itself obtained by
estimating a univariate time series equation for
inflation. (An alternate method for obtaining
the real rate, where actual inflation was used
instead of expected inflation, produced results
that were essentially the same as those reported
below.) All independent variables are included
in growth rate terms, except for the interest
rate, which is included as a difference.
Current and two lagged values have been included for all explanatory variables (except the
lagged dependent variable and the time trend).
For four of these variables (money, private
credit, the Treasury bill rate and loans by financial institutions), this length was selected by
imposing the condition that the F statistic (for
the null hypothesis that current and lagged values of the variable being tested are all zero)
have a marginal significance level of at most
0.05 and that the standard error of the equation
not increase when additional lags were added.
The same lag length was chosen for the other
credit aggregates to ensure comparability. It
should be pointed out that for these latter variables,the results will not change if the lag
length is altered. Finally, only one lag for the
dependent variable was included since the second lag is insignificant across all specifications.
Table 1 presents summary statistics for these
equations. For each independent variable (including lags), I report the marginal significance
levels for the F test. The marginal significance
level (M.S.L.) can be can be interpreted as the
probability that the variable under considerationhas no impact on GNP. Conventionally, the
variable is regarded as significant if this probability is less than 0.05. Thus, in the first equation the M.S.L. for the F test on money is
0.0001, which implies that the probability that
changes in money have no impact on GNP is
extremely small. Equation 1 also includes real
federal high employment expenditures, which
do not seem to affect output significantly. No34
tice that Durbin'sh statistic shows significant
evidence of serial correlation. The second
equation adds the real rate of interest to Equation 1. The explanatory power of the equation
increases, .whiletheserialicorrelation declines.
In Equations 3 through 7, different credit
variables are added to the set of explanatory
variables in Equation 2. Equation 3 includes
the rate of growth of private credit. Notice that
the credit variable is highlysignificant.andthat
the h statistic (testing for the presence of serial
correlation) is close to zero. Also notice that
the M.S.L. on lagged real GNP jumps to 0.8.
In Equation 4, the rate of growth of federal
borrowing is included. This variable is clearly
insignificant and iF is actually lower than in
Equation 2. In the next equation, total domestic nonfinancial debt is also insignificant, although it is more "significant" than federal
debt. From the last two equations, it can be
seen that loans by financial institutions have
somewhat greater explanatory power for real
GNP than do loans by commercial banks.
Somesilllpletest~ to examine the stability .of
the coefficients on the credit variables were also
carried out. The sample was split at two differentplaces to see whether there was any evidenceofastructuralbreak. The first split was
at1971:Q2, where Sims (1980) found evidence
of a. structural break in a system that inclUded
output, money growth, and prices. Second,the
data was also split at 1979:Q3 to examine
whether the change in operating procedures by
the Federal Reserve at that time had any impact. Tests were then carried out to examine
whether the coefficients of the credit variables
(at a specific lag as well as for all lags taken
together) had changed.
TABLE
1
Real GNP Equations-Summary Statistics
Sample 1959(04)-1984(02)
Equations
Credit Variable Included
Explanatory Variables
3
4
5
6
7
PVT
2
FED
TOT
TLFI
TLCB
Marginal
Levels of Explanatory Variables
M1
.0001
.0001
.001
HEXP
.13
.12
.03
.007
.04
RGNPLl
.055
.04
.8
TIME
.27
.18
.03
.0001
.13
.01
.76
.03
.24
TBR
CDT
.0002
.0001
.0001
.0001
.10
.02
.051
.007
.12
.02
.04
.18
.003
.056
.058
.17
.13
.09
.09
.464
2
R
.370
.433
.532
.415
.440
.498
MSE(X1Q2)
.661
.596
.487
.608
.582
.522
.558
.07
.84
.98
Durbin's h
Notes:
1.69
1.22
0.34
2.09
(1) All variables are in real terms and in rates of growth, except that the rate of interest term is included as a
difference. HEXP is federal high employment expenditure. CDT represents the credit variable. To see
which credit variable is included in a particular equation, look at the top of the relevant column. Thus, in
equation 3, PVT (that is, private credit) is included. FED is federal borrowing and TOT is total domestic
nonfinancial borrowing. FITL is total loans by financial institutions and CBTL is total loans by commercial
banks. The current value and two lags have been included for each of these variables. RGNPLl is the
lagged dependent variable.
(2) The Marginal Significance Level (M.S.L.) for a particular variable can be interpreted as the probability that
the variable has no impact on the dependent variable (real output in this case). Conventionally, a variable is
considered important in a particular equation if it has a M.S.L. of .05 or less.
35
For the split at 1971:02, it was possible to
reject the hypothesis of no shift at the 5 percent
level only for the contemporaneous value of domestic nonfinancial debt (TOT) and for the first
lag of loans by commercial banks; ForthespIit
at 1979:03, the federal debt variable shows evidence of a shift at all lags individually and together, a result that is not very surprising given
the large Treasury borrowings of recent years.
Summary statistics for the nominal GNP
equations are presented in Table 2. The variables are defined in the same way as in Table
1, with the exception that all variables are now
expressed in nominal terms. (Neither lagged
values of GNP nor a time trend were significant
here.)
Once again, the rate of interest is significant
in predicting changes in nominal GNP. Adding
private credit improves the fit of the equation
even futher. Notice that adding federal borrowing reduces iP again and that the total debt
variable has a M.S.L. of .25. Both the loan variables, total loans by financial institutions
(TLFI) and total loans by commercial banks
(TLCB), are significant at 1 percent.
The significant credit variables were also
tested to see if the coefficients had shifted over
time. For the break at 1971:02, it was not possible to reject stability for any of the coefficients. For the break at 1979:03, the private
debt and commercial bank loan variables show
no evidence of a shift, while TLFI does.
Consider, now, Table 3 which presents the
results for the velocity equation. As discussed
above, the estimated equation is derivedfrolll.
a money demand equation, with the additional
constraint that the coefficient on real income in
the estimated money demand equation equal
1. 6 The first equation includes only the rate of
interest and a lagged money term. Successive
equations then add different credit variables.
Table 3 also shows that while private credit is
significant in predicting velocity, neither federal
nor total credit are. Total loans by financial institutions are significant here (as in the GNP
equations) but loans by commercial banks are
not.
Credit variables in the velocity equation were
also tested to see if they showed any signs of a
shift. However, for neither the break at
1971:02 nor the break at 1979:03 can the hypothesis of no shift be rejected.
TABLE
2
Nominal GNP Equations-Summary Statistics
Sample 1959(04)-1984(02)
Equations
Credit Variable Included
Explanatory Variables
3
4
5
6
7
NPVT
2
NFED
NTOT
NTLFI
NTLCB
Marginal Significance Levels of Explanatory Variables
.----~
Ml
.0001
.0001
.0002
.0001
.0001
.0001
NHEXP
.10
.04
.0052
.064
.056
.005
.013
.0001
.0008
.0001
.0002
.002
.0001
.0005
.80
.25
.010
.013
NTBR
NCDT
2
.0001
R
.318
.451
.539
.439
.458
.502
.499
MSE(XWZ)
.753
.607
.509
.620
.599
.550
.554
D.W.
1.54
1.63
1.86
1.59
1.74
1.72
Notes: See notes to Table 1 for explanations. The variables are the same as in Table 1 except that they are all
measured in nominal terms.
36
1.81
TABLE 3
M1 Velocity
Sample 1959(04)-1984(02)
E:qLJatiOrlS
2
4
PVT
Credit Variable Included
3
FED
TOT
TLFI
TLCB
Explanatory Variables
.578
NTBR
NTBR1L
NTBR2L
.267
.481
.064
CDT
CDTlL
CDT2L
-.126
M1LP
.609
.595
.596
.563
.206
.438
.076
.267
.480
.068
.255
.475
.053
.216
.430
.006
.249
.478
.079
.015
.016
-.003
Constant
- .0002
-.0001
.00
.005
.004
.005
.0045
.0015
.0067
.0017
.0016
- .0002
-.253
-.105
.165
-.216
-.122
Marginal Significance Levels
.0001
.0001
.0001
.0001
.0001
.0001
.01
NTBR
CDT
.65
.72
.02
.10
.02
.31
.14
.04
.23
M1LP
.22
if
.363
.413
.353
.351
.405
.385
MSE(X102)
.775
.714
.786
.789
.724
.749
D.W.
Notes:
1.80
1.95
1.76
1.86
1.92
1.94
The dependent variable is the growth of velocity. See Tables 1 and 2 for an explanation of variables. M1LP is
the lagged money term. NTBR1L is NTBR lagged one quarter, NTBR2L is NTBR lagged 2 quarters.
IV. Conclusions
This paper has presented some theoretical arguments and empirical evidence to show that
changes in private credit will provide useful information about changes in f\Iture output and
Ml velocity. Previous analyses of. the money/
GNP relationship have often tended to focus
on the asset demand for money and,consequently, emphasized. the. substitutability between money and credit. In contrast, explicit
attention was paid earlier in this paper to the
need for money to carry out transactions. In
this framework, it is easy to see how money and
credit can vary in the same direction-because
the demand for credit. can be viewed as a demand for payments media.
For the policymaker, this means that information about changes in money and. interest
rates alone is not sufficient for predicting what
will happen to output. To determine the implications of.a change ·in money, it is·important
also to know how the credit aggregates are behaving. The evidence presented above is also
specific about what credit aggregates are usefuL
It indicates thatchallgesin federal government
borrowing are not significantly related to GNP,
while several measures ofprivatecrediLare.
The most recent example of thephe l1omenon
captured in these tests is what happelled in late
1982 when declining.output was accompanied
by rising money but falling private borrowing.
37
direct means to determine whether the money
demand function has shifted (regardless of the
sQurce of the change), and that this knowledge
is necessary to interpret the money-output relationship properly.
Although the analysis above has focused on
recessions as periods when changes in (private)
credit aggregates are likely to provide significant information, the underlying logic can be
applied more widely. The argument of this paper has been that changes in credit provide a
FOOTNOTES
1. Friedman and Schwartz (1982, p. 39), when specifying
the arguments of the money demand function, state "another variable that is likely to be important empirically is
the degree of economic stability expected to prevail in the
future. Wealthholders are likely to attach considerably more
value to liquidity when they expect economic conditions to
be unstable than when they expect them to be highly stable
... For example, the outbreak of war clearly produces expectations of instability, which is one reason war is often
accompanied by a notable increase in real balances.. ."
hOld loan supply, These effects arise through the deposit
market. For example, if the rate on bank loans goes up,
banks are likely to begin offering higher rates on demand
dElj)osits. As a result, hOUSeholds will decrease loan supply
and. increase deposit holdings.
5.• It is interesting to examine whether the model sketched
above is robust to some generalizations. Consider, first, the
assumption that demand deposits are the only liabilities of
banks. In a more general setting, one would also have to
consider other liabilities such as certificates of deposit
(CDs). Does the existence of CDs destroy the positive link
between loans and demand deposits? Intuitively, the answer appears to be no. If it is true that banks face rising
marginal costs to increasing either demand deposits or
CDs, banks will increase both types of liabilities together.
In equilibrium, the bank must face the same marginal cost
for poth liabilities, otherwise it is always possible to decrease costs by substituting the cheaper liability for the
more expensive. Thus, it is unlikely that the amount of bank
loans willirttrease significantly without an increase in demand deposits.
2. Others have also suggested the possibility of a shift in
the money demand function during the 1982 recession. For
example, Axilrod (1984), when discussing the decline in
velocity in 1982, states "During part of the period, economic uncertainties may have heightened precautionary
demands for cash." Later, he says that he expects velocity
to increase in the near future, which "would be consistent
with the view that some of the previous decline was a reflection of precautionary demand for cash balances, balances that can be expected to be unwound as confidence
in the economy is restored." Similarly, Simpson (1984, p.
259) says "In late 1981 and early 1982, the demand for
NOW accounts, passbook savings, and other very liquid
assets in household portfolios strengthened while transactions demands weakened and rates dropped only moderately, perhaps reflecting a desire to be better able to
cushion an earnings disruption, which at that time seemed
more likely."
Consider next, the implications of allowing households to
hold a third asset in addition to loans and money, say equity. In this case, increased demand for liquidity will not be
matched exactly by a decrease in the supply of loans to
firms. Instead, households will reduce equity holdings as
well. Once again, the household is unlikely to obtain the
necessary balances by selling equity holdings only. Since
the shift in liquidity preference does not alter the relative
price of loans to equity, holdings of both will be reduced.
Thus, the qualitative result is unchanged-firms must still
turn to the banking sector for loans.
3. The shape of the bank loan supply curve depends upon
the monetary authority's behavior. To see this, consider the
two extremes of behavior by the monetary authority. Assume first that the monetary authority accommodates all
increases in credit demand, which would happen, for instance, if it were trying to peg the interest rate. In such a
situation, the supply curve of bank loans would be horizontal, because the monetary authority stands ready to
supply all the reserves for deposit (and loan) expansion.
6. The demand for nominal money can be written (in log
form) as
where
The other extreme is where the monetary authority does
not accommodate any cyclical increase in credit demand.
Such a situation may occur, for instance, if the authority is
following a fixed money growth rule. In this case, banks
can increase loans only by inducing the public to hold more
deposits. The supply curve for loans would then be much
steeper and, given a limit to the amount of deposits that
individuals wish to hold, would ultimately become vertical.
Mi denotes desired nominal money balances,
Yt denotes real income,
Rt denotes the nominal rate of interest, and
Pt denotes the price level
Then, under the assumption that actual money balances
do not adjust at once to desired, we have
Mt - Mt_, = A(Mi
Mt_,)·
Substituting this in the equation above gives
Mt = A(aYt - f3R t) + (1 A) Mt_, + APt·
Next, subtract Pt from both sides to obtain an expression
for real balances.
Mt - P t
A(aYt - f3R t) + (1 A) (M t-, - Pt).
Imposing the condition that the coefficient on real income
is 1 and transposing gives an expression for velocity that
is the estimated Equation 1 of Table 3.
The assumption in the text is that the authority's behavior
lies somewhere in between these two extremes. It can also
be shown that changes in the credit aggregate convey significant information even if the monetary authority follows
one of the above policies.
4. The analysis suppresses the shift in bank loan supply
due to a change in rh and a similar impact of rb on house-
38
REFERENCES
Axilrod, S.H. "Issues in Monetary Targeting," in Proceedings of the Conference on Monetary Targeting and
Velocity, Federal Reserve Bank of San Francisco,
1984.
JUdd, J.P.. "The Recent DeCline in Velocity: Instability in
Money Demand or Inflation," Economic Review, Federal Reserve Bank of San Francisco, Spring 1983.
King, .R. and C, '. Plosser. "Money, Credit and Prices in. a
Real Business Cycle," American Economic Review,
Vol. 74, June 1984.
FriEldrrlan, B. "Portfolio Choice and
Debt to
Relationship," NBER Working Paper No. 1545, January 1985.
Porter, R.D. and Offenbacher, EK "Empirical Comparisons of Credit and Monetary Aggregates Using Vector
Autoregressive Methods," Economic Review, Federal
Reserve Bank of Richmond, November/December
1983.
- - . "The Roles of Money and Credit in Macroeconomic
Analysis," in "Macroeconomics, . Prices and Quantities", James Tobin, ed. Washington, D.C.; Brookings
Institution.
Simpson, T.D. "Changes in the Financial System: Implications for Monetary Policy," Brookings Papers on
Economic Activity, 1984:1.
- - . "The Relative Stability of Money and Credit 'Velocities' in the United States: Evidence and Some Speculations," NBER Working Paper No. 645, March 1981.
Friedman, M. and A.J. Schwartz. "Monetary Trends in the
United States and the United Kingdom," Chicago: National Bureau of Economic Research, 1982.
Sims, C.A. "Macroeconomics and Reality," Econometrica,
Vol. 48, Jan. 1980.
Froewiss, K.C. and J.P. Judd. "Optimal Control and Money
Targets: Should the Fed Look at 'Everything'?," Economic Review, Federal Reserve Bank of San Francisco, Fall 1979.
39
Brian Motley*
This article develops a model of short-run changes in the unemployment rate and uses it to make forecasts of the rate in 1985. The
model is based on Okun's Law which relates changes in unemployment to the growth rate of aggregate demand. It differs from
earlier models, including Okun's own work, because it estimates
explicitly the growth rate of demand that is required to offset increases in labor force participation and labor productivity rather
than assuming that growth rate to be constant. The unemployment
rate changes in response to the differential between the actual
growth of GNP and this "required" growth rate.
Between December 1982 and June 1984, the
unemployment rate in the U.S. declined from
10.7 percent to 7.2 percent of the civilian labor
force. Over this same period, real GNP grew
at a rapid 6.8 percent annual rate. Since last
June, however, real GNP growth has slowed
and no further progress has been made in lowering the unemployment rate. Moreover, most
economic forecasters do not expect real growth
to pick up in 1985, with most estimates for the
year in the 3-4 percent range.
An important issue facing economic policymakers is whether real growth in this range
would be sufficient to bring about significant
further reductions in the unemployment rate.
Many economists argue that it probably would
not be, but that any attempt to pursue more
rapid real growth would risk jeopardizing the
hard-won gains in bringing down inflation in
recent years. Others agree that faster real
growth is required to reduce unemployment to
any significant extent, but argue that the risk
of faster inflation is worth running, in view of
an unemployment rate that remains high by historical standards. In the twenty-five years before 1975, unemployment exceeded six percent
of the civilian labor force in only two years,
1958 and 1961, but in the last ten years it has
been below six percent only once.
One piece of information that is required to
make a judgment on this issue is an estimate of
the response of the unemployment rate to
changes in the growth rate of real GNP. To this
end, this paper develops a model that provides
short-term predictions of the unemployment
rate given expectations of the growth rate of
real GNP. This model extends the work reported in a recent Economic Review article!
that developed long-term projections of the
unemployment rate. Like that earlier long-run
model, the analysis in this paper is based on the
observed relation between changes in the
unemployment rate and the rate of growth of
real GNP, also known as Okun's Law.
To bring down the unemployment rate, the
real demand for the economy's output of goods
and services must increase. Indeed, a certain
minimum rate of economic growth is required
simply to prevent the unemployment rate from
rising. For example, increases in the total population and in the proportion of the population
that wants to work mean that to prevent an
increase in unemployment, the demand for output must grow enough to create jobs for these
new entrants to the labor force. Similarly, the
productivity of labor (that is, output per employed worker) generally rises through time, so
*Senior Economist, Federal Reserve Bank of
San Francisco. Research assistance was provided by Kenneth Khang.
40
The Model
that unless the demand for goods and services
increases at least as rapidly as output per
worker, the demand for labor will decline and
unemployment will mount.
In this article, the rate of growth in the demand for real GNP that is needed to offset
changes in the labor force and productivity exactly-and thus to hold the unemployment rate
constant-will be termed the required GNP
growth rate. 2 To predict the impact on unemployment of a particular rate of growth of real
GNP, an estimate of this required growth rate
is needed. This article develops a set of equations that explain changes in labor productivity
and in the size of the labor force, and uses these
equations to derive estimates of the required
GNP growth rate.
Over the business cycle, the actual growth
rate of real GNP diverges from the required
growth rate and, as a result, unemployment
rises and falls. In the recovery phase of the
cycle, for example, output increases more rapidly than the required rate and the unemployment rate consequently declines. During the
recession phase, the reverse occurs. Okun's
Law (See Box 1) summarizes the relationship
between changes in the unemployment rate and
cyclical variations in the rate of GNP growth
relative to the required rate. It provides a "rule
of thumb" for estimating how much the unemployment rate will change in response to a given
change in real GNP. For example, Okun's own
estimate of this rule of thumb was that a three
percentage point increase in the growth rate of
real GNP above the required rate would be associated with a one percentage point decline in
the unemployment rate.
However, most previous estimates of this relationship, including Okun's own estimates,
have assumed that the required rate of GNP
growth remained constant over the sample period. If this assumption were not correct, the
estimates of the relation between GNP growth
and changes in the unemployment rate might
be biased. The Okun's Law equation developed
in this paper avoids this assumption by using
the estimates of the required rate derived from
the analysis of the determinants of labor force
participation and labor productivity.
The accounting relation between real GNP
and total employment may be represented in
the following identity:
Y/Pop
where
Y
E
L
Pop
~
(Y/E) x (ElL)
X
(LiPop)
(1)
Real GNP
Civilian employment
Civilian labor force
Adult population3
This identity shows that real output per capita, Y/Pop, may be decomposed into the product of (i) output per employed worker, Y/E,4
(ii) employment as a proportion of the labor
force, ElL, and (iii) the labor force as a proportion of the population, LlPop. Using lower case
letters to represent the ratios in Equation 1, this
identity also may be written in terms of growth
rates:
dIn y ~ dIn q + dIn e + dIn p
(2)
where
y = real GNP per capita, Y/Pop
q = labor productivity, or real GNP
per employed worker, Y/E
e = the employment ratio, or the proportion of the labor force that is
employed, ElL
p = the participation rate, or the proportion of the population that is
in the labor force, LlPop, and
dIn represents the change in the logarithm, and thus the growth rate, of each
variable.
Since our principal interest is in the growth
of employment, and hence of unemployment,
it is useful to rearrange this equation and write
it as:
dIn e
~
dIn y - (din q + dIn p)
(3)
If the growth rates of labor productivity
(dIn q) and labor force participation (dIn p)
were to depend only on technological, demographic and other non-economic factors that remained constant over time, the forecasting of
the employment ratio would be relatively
straightforward. Suppose, for example, that la-
41
42
bor productivity were known to rise at a constant two percent a year and the available labor
force at one percent. In this case, the required
GNP growth rate would be three percent since
if real aggregate demand were to increase at
that rate, the growth in the demand for labor
would exactly match the growth in the supply,
and the proportions of the work force that were
employed and unemployed would remain constant. In terms of Equation 3, if real GNP were
to grow at three percent a year, din e would be
zero because din y would be exactly equal to
the sum of dIn q and dIn p.
If real GNP were to increase by more than
three percent, the proportion of the labor force
employed would rise. In particular, Equation 3
shows that, in the special case in which the
growth rates of participation (dIn p) and of productivity (din q) are constant, an increase in the
annual GNP growth rate of, for example, one
percentage point (from three percent to four
percent), would cause the employment ratio to
grow at an annual rate of one percent and hence
would cause the unemployment rate to decline
by one percentage point per year. 5
Thus, if the growth rates of productivity and
the labor force were constant, the required
GNP growth rate also would be constant and
each one percentage point increase in the actual
GNP growth rate above the required rate would
produce a one percentage point decline in the
unemployment rate.
In fact, the growth rates of productivity and
the labor force are not constant. The demographic, technological and other non-economic
factors that affect labor force participation and
productivity growth vary over time, and these
variations lead to changes in the required GNP
growth rate. In addition, participation and productivity also respond to changes in the growth
rate of real GNP over the business cycle. More
rapid GNP growth during a business cycle expansion, for example, tends to be associated
with faster growth both in output per worker
(partly because hours of work increase) and in
labor force participation. This means that a
given increase in real GNP growth leads to a
smaller increase in the employment ratio than
Figure 1
Determining the
Required Growth Rate
Growth Rate
Q
dlnq+dlnp
p
din q +dlnj)
s
o
R
C
Growth Rate of Per Capita GNP
if the growth rates of productivity and participation were unchanged. In terms of Equation
3, since the rise in din y associated with a cyclical upswing typically is accompanied by increases in both dIn q and din p, the increase in
din e is correspondingly smaller.
Figures 1 and 2 illustrate these arguments
graphically. In these figures, the horizontal axis
represents the growth rate of per capita GNP.
The 45-degree ray OTQ identifies points at
which the growth rates measured on the vertical
and horizontal axes are equal. Figure 1 illustrates the determination of the required GNP
growth rate and shows how changes in the
growth rate of GNP over the business cycle lead
to increases and decreases in the employment
rate, while Figure 2 illustrates the effect of
demographic, technological and other non-cyclical factors on the required GNP growth rate.
In Figure 1, the curve STP, labeled dIn q +
din p, represents the combined growth rate of
productivity and participation. This curve
slopes upward to illustrate the tendency for the
growth of both productivity and participation
to increase and decrease as the growth rate of
real GNP rises and falls over the business cycle.
43
For simplicity, STP is represented as a straight
line. The accounting identity in Equation 3 implies that the vertical distance of the curve STP
above or below the ray OTO represents the rate
of change of the employment ratio. Hence, the
intersection of the curve STP with the ray OTO
at the point T identifies the growth rate of per
capita real GNP at which the employment ratio
remains unchanged. At this intersection, the
combined growth rate of productivity and participation is exactly equal to the growth rate of
per capita GNP. This growth rate of productivity and participation is labeled din q + din p.
The GNP growth rate which holds the employment ratio constant is the "required
growth-rate." In Figure 1 this growth rate is
OR. If real aggregate demand per capita grows
at the required rate, the combined growth rate
of productivity and participation, RT, is exactly
equal to the growth rate of per capita GNP,
OR. Hence, the demand for labor rises at the
same rate as the supply, and the employment
ratio remains unchanged.
In a cyclical upswing, when the actual growth
rate of real GNP rises above the required
growth rate, OR, the combined growth rate of
productivity and participation also increases but
by a lesser amount. Hence, the employment ratio increases. For example, if GNP per capita
grows at rate OC, productivity and participation together grow at rate CPo Although this
growth rate is above the required GNP growth
rate, OR, it is less than the actual GNP growth
rate, CO. Hence, the employment ratio increases at rate PO. Conversely, when real GNP
growth is less than OR, the growth rate of productivity and participation is greater than that
of GNP so that the employment ratio declines.
When the growth rates of participation or
productivity increase or decrease for reasons
that are not related to the business cycle, the
required GNP growth rate will change. An increase in the trend rate of growth of labor force
participation, for example, adds to the supply
of labor, which means that real aggregate demand must increase more rapidly if there is to
be no increase in unemployment. Similarly,
faster trend growth in labor productivity reduces the demand for labor; if unemployment
is to remain unchanged, this must be offset by
faster output growth. Thus, in both of these
instances, the required GNP growth rate rises.
In Figure 2, such changes are represented by
an upward shift of the curve STP to ST'P'. As
a result, the intersection point with OTO is
shifted from T to T' and the required growth
rate increases from OR to OR'. The empirical
section below attempts to quantify such shifts
and to derive estimates of how the required
growth rate has changed over time.
The preceding argument also may be stated
in algebraic terms. The hypothesis that a cyclical increase (decrease) in the growth rate of per
capita GNP leads to a lesser increase (decrease)
in the combined growth rate of productivity and
participation may be written as
Figure 2
An Increase in the
Required Growth Rate
Growth Rate
Q
p'
_"T-'
.p
s
din q + din p
o
+ 13 din y
where 0 < 13 < 1
= 0'.
(4)
This equation represents the curve STP in
Figure 1. The intercept term, a, represents the
effect of technological, demographic or other
R
R'
Growth Rate of Per Capita GNP
44
noncyclical factors that affect the growth rates
of productivity and participation. The slope
coefficient, 13, represents the response of productivity and participation to variations in the
growth rate of per capita GNP over the business cycle. Substituting this equation into
Equation 3 and re-arranging terms yields
din e = - ex + (1 - 13) din y
required growth rate, dIn yR, and to use it to
estimate Equation 7. This is the procedure employed in the following empirical section.
Empirical Results
To estimate Equation 7, a statistical series for
the required GNP growth rate must be constructed. The previous section showed that this
growth rate varies in response to changes inthe
demographic, technological and other non-cyclical factors that influence productivity and labor force participation. This argument suggests
that a statistical series for the required growth
rate, dIn yR, may be constructed in a series of
steps. First, separate equations are estimated to
explain labor productivity and labor force participation in terms of both cyclical and non-cyclical variables. Second, these equations are
simulated over the sample period holding the
cyclical variables constant. The growth rates of
these simulated values are interpreted as estimates of din q and dIn p-the growth rates of
productivity and participation that would arise
if there were no cyclical variations in the economy and hence a situation in which the unemployment rate remained constant. On this interpretation, the sum of these simulated growth
rates represents din yR, the required GNP
growth rate.
Separate equations were estimated for the female and male participation rates and for labor
productivity. Earlier research 7 suggested that
both participation and productivity may be adequately modeled using a cyclical variable, a
few demographic variables and a series of trend
variables. In the present context, it was natural
to follow this previous research and choose the
employment ratio as the cyclical variable since
the required growth rate is defined as the rate
that holds that ratio constant. 8 Full details of
the estimated equations are shown in the table
in Box 2. The estimation period was from the
first quarter of 1953 to the last quarter of 1982.
Each estimated equation was simulateddynamically over the sample period, holding the
employment ratio constant at its 1953(01)
level9 . This procedure computes how productivity and participation would have changed
(5)
As illustrated in Figure 1, when per capita GNP
is growing at the required rate, din yR, the employment ratio is constant and the growth rate
of per capita GNP is equal to the combined
growth rate of productivity and participation.
Thus,
din yR = din
q+
din
p=
ex + 13 din yR
(6)
where din q and dIn p represent the growth
rates of productivity and participation when per
capita GNP is growing at the required rate.
Equation 6 represents the growth rate of per
capita GNP at the intersection point T in Figure
1. As was illustrated in Figure 2, a change in
the value of the intercept term, ex, which represents the effect of non-cyclical variables on
the growth of productivity and participation, alters the required growth rate.
When Equation 6 is solved for ex and the resulting expression is substituted into Equation
5 it yields:
din e
=
(1-13)(din y - din yR)
(7)
This equation, which is a form of Okun's Law,
shows that the growth rate of the employment
ratio depends on the differential between the
actual and required growth rates of real GNP.
However, most estimates of this equation, including Okun's own, have assumed that the required growth rate was constant and hence that
changes in the employment ratio depend only
on the actual GNP growth rate.
More recent research 6 suggests that this assumption that the required growth rate does not
change over time may not be an accurate one
and hence that estimates of Equation 7 made
under that assumption may be biased. This suggests that an alternative and preferable procedure is to construct a statistical series for the
45
46
47
over the sample period if the employment ratio
had remained constant. The simulated values
of the male and female participation rates were
combined into an overall participation rate. Fillelly, the growth rates of simulated total participationand labor productivity were summed
to yield a series of the required growth rate of
per capita real GNP that would hold the employment ratio constant at its 1953(Q1) level.
Charts 1--3 show the actual and simulated
values of productivity and of male and female
participation.• Although most of the variation
in aU three variables represents the business
cycle, it is clear that even when the effects of
the cycle are removed, a significant amount of
variation remains. Chart 4 shows the actual and
required growth rates of per capita real GNP.
Toward the end of the sample period, therequired per capita GNP growth rate was approximately two percent, but it was significantly lower through most of the 1970s. This
constructed series of the required GNP gro\Vt~
rate was used to estimate an empirical version
of Equation 7.
Most previous estimates of Okun's Law have
found that the employment ratio responds to
changes in the GNP growth rate with a lag. The
theoretical model represented in Equation. 7
implies that this lagged response should refer
to the differential between the actual and required growth rates, suggesting that the empirical form of Equation 7 should include current
and lagged values of both the actual and the
required growth rates of per capita GNP. In
Chart 1
Growth Rate of Productivity
Actual vs. Trend
Annual
Percentage Rate
12
10
·Actual
8
6
4
2
o
-2
-4
-6
-8
_
53 55 57 59 61
63
65 67 69 71
48
73 75
......
77 79
81
83
practice, because the required growth rate is a
smooth series, its current value isa good proxy
for its lagged values. 10 Hence, the estimated
equation was:
dIn e1
=. a + bodln Yt +. b
+ b 2 dIn Yt.2
-
1 dIn Yl.l
c dIn ylf
The results of estimating this equation, and
testing these hypotheses, are set out in Table 1.
In that Table, Equation A shows the estimated
coefficients of Equation 8 with no restrictions.
Allcoefficients carry the signs predicted by the
sl.lllloftheestllllatedcoefficients on the current and lagged values of the
GNP growth rate is not exactly equal to the
coefficient on the required rate, the hypothesis
that they are equal cannot be rejected at conventional significance levels. In addition, Equation A confirms the prediction that the intercept term should be zero; the estimated
intercept is small and not statistically significant. When the intercept is eliminated in Equation B, the sum of the coefficients on dIn Yt
is much closer to that on dIn Ylf. Finally, constraining these values to be equal, as in
(8)
where dIn ylf represents the constructed series of the required GNP growth rate. The
proposition embodied in Equation 7 that
growth in the employment ratio is proportional
to the differential between the actual and required GNP growth rates implies that the intercept term in Equation 8 should be zero and
that the sum of the coefficients on the current
and lagged growth rates of per capita GNP
should be equal to the coefficient on the required growth rate, that is, bo + b l + b 2 = c.
Chart 2
Growth Rate of Male Participation
Actual VS. Trend
Annual
Percentage Rate
4
-oeActual
- 4 ...................................................II-.......""""""'.....II............-t"""""""'................""""-lIIIIIIIIIIIiolllllllllllllll
53 55 57
59 61
63 65
67 69
49
71
73
75 77 79 81
83
of the employment ratio by one percent (that
is, to lower the unemployment rate by one percentage point per year), actual per capita GNP
must increase at a rate two percentage points
above the required rate. This compares \Vith
Okun's estimate of three percentage points.
Several other studies made since Okun's initial
work, which used data from the 1950s,also
have suggested that the unemployment rate has
become more responsive to changes in the GNP
growth rate. 12
Chart 5 shows the quarter-to-quarter changes
in the unemployment rate and compares them
to those derived from the fitted values of Equation C in Table 113 . Given the substantial volatility of the unemployment rate, the fit of the
equation appears to be quite good.
Equation C, has no noticeable effect on the estimatedcoefficients.
For comparison, Equation D reports the
result of restoring the intercept but excluding
the •..variable dIn .Y'l-. This equation correspondsto a specification in which the required
growth rate of real GNP is constant and equal
to-a/(bo + b 1 + b2). As pointed out above,
earlier research suggested that this specification
is not supported by post-war U.S. data ll . This
finding is confirmed by its standard error,
which is slightly larger than those for the earlier
equations.
Equation C is the empirical counterpart of
Equation 7 and incorporates the coefficient restrictions suggested by the theory. It implies
that, in order to increase the annual growth rate
Chart 3
Growth Rate of Female Participation
Actual VS. Trend
Annual
Percentage Rate
14
12
10
8
6
4
"'Actual
2
o
-2
-4
-6
-8
-10
..u-...
53
55 57
Iooo..olL-
59 61
63 65
67
50
69 71
73
75
77 79 81
.....
83
TABLE 1
Estimates of Okun's Law
Equations
D
B
A
Constant
-0.0010
(1.49)
dIn y,
0.253
(11.94)
0.253
(11.90)
0.254
(12.01)
0.250
(11.69)
dIn Yt-l
0.179
(7.98)
0.181
(8.01)
0.181
(8.04)
0.176
(7.76)
dIn Y'-2
0.066
(3.13)
0.067
(3.16)
0.067
(3.19)
0.062
(2.91)
0.498
(18.71)
-0.306
(1.92)
0.501
(18.78)
0.503
(18.91)
-0.503
(18.91)
0.487
(18.44)
Sum
dlny~
-0.0023
(10.25)
-0.533
(10.38)
SEE
0.00225
0.00226
0.00225
0.00227
DW
1.65
1.61
1.62
1.60
TABLE 2
Unemployment Forecasts 1983-84
Change in Unemployment Rate (Percentage Points)
Predicted
Actual
Error
198301
02
03
04
+0.16
-0.30
-0.43
-0.37
0.23
-0.24
-0.80
-0.86
+0.39
-0.06
-0.37
-0.49
198401
02
03
04
-0.48
-0.49
-0.13
+0.01
-0.60
-0.37
0.09
-0.22
-0.12
+0.12
-0.04
-0.23
1982 04/1983 04
-0.95
-2.13
-1.18
1983 04/1984 04
1.09
-1.27
-0.18
51
Predictions and Policy Implications
To test its predictive power, the model was
used to forecast the unemployment rate over
the period from 1984(Ql) to 1984(Q4). The
forecast ",as made in two stages.IQ thg first
stage, the equations estimated in Box 2 were
simulated over the forecast period holding the
employment ratio constant at its 1953(Ql)
level, and the resulting projections of labor productivity and participation were combined to
yield quarterly estimates of the required per
capita GNP growth rate. Over the eight-quarter
forecast period, this required growth rate was
estimated to increase modestly and to average
slightly above two percent. In the second stage
of the forecasting procedure, these projections
of the required rate were entered into Equation
C in Table 1 and that equation was simulated
to produce forecasts of the employment ratio.
A nnua I
Percentage Rate
Finally, these estimates were transformed into
forecasts of the unemployment rate. These
forecasts are shown in Table 2.
Over the eight-quarter period, actual per
capita QNPgr()\Vth averaged .5.2 percent. Simulation of the. model predicted a decline in the
unemployment rate of 2 percentage points. In
fact, the unemployment rate declined by more
than this: by 3.4 percentage points. The underprediction of the improvement in the employment ratio implies corresponding overpredicitons of the other components of real output
growth. Examination of unrestricted simulations of the productivity and participation rate
equations (that is, allowing the employment
rate to vary rather than holding it constant) indicates that both female participation and labor
productivity increased less rapidly over this period than historical relations would have pre-
Chart 4
Growth Rate of Per Capita Real GNP
10
8
6
Actual~
4
2
o
-2
-4
-6
-8
-10
-12 '-53
55
......1
57
59
61
63
65
67
52
....1-
..10....
69
71
73
75
77
79
81
......
83
dicted. Thus,although the strong economic expansiondid produce more rapid growth in
productivity, participation and employment,
the gain in productivity and participation was
slllallerthan usualandhence,given.the GNP
growth that actually occurred, the gain in employment and the corresponding decline in the
unemployment rate were larger. This outcome
is somewhat ironic in view of earlier expectations that changes in tax· policy would lead to
faster productivity and labor supply growth.
However, Table 2 indicates that most of the
prediction error occurred in 1983 when the
unemployment rate fell much more rapidly than
the model would have predicted. The error in
1984 was significantly smaller: from 1983(04)
to 1984(04) the model predicted a decline in
the unemployment rate of 1.1 percentage points
compared to the actual decline of 1.3 percent-
age points. In view of this result, the model has
been used to make projections of the unemployment rate over the four quarters of 1985.
To do so, the model was re-estimated
through the fourth quarter ot 1984.Theestic
mated coefficients of the Okun's Law equation
were essentially unchanged although the computed values of the required per capita GNP
growth rate over 1983__84 wef(:~ slightly. lower
than those forecasted on the basis of pre-1983
data. In making the forecasts for 1985, the required per capita GNP growth rate was assumed to remain constant at its 1984(04) level,
namely two percent per annum. Real GNP was
assumed to grow by four percent over the four
quarters of 1985. Given the Census Bureau estimate that the adult population will rise 1.1
percent, this real growth assumption implies
that per capita GNP will increase by 2.9 per-
Chart 5
Change in the Unemployment Rate
Actual vs. Fitted Values
Percentage
Points
2.0
1.5
1.0
0.5
0.0
-0.5
-1.0
54 56 58 60 62 64 66
68 70 72 74 76
53
78 80 8283
ment rate this year. An alternative. conclusion
would. be that a somewhat more rapid rate of
real growth would not bring the economy significantly closer to a level of the unemployment
rat~atwllicl1 the infl~tiOll rat~\yolllclb~iJik~ly
to rise. This appears to be the Administratioll's
position as it has suggested as a target the four
percent growth rate assumed above. Theestimatesdeveloped in this paper sllgge~tthatyVyn
a four percent growth rate would produce only
a relatively modest decline in theuIl~mpIQY
ment rate and hence would not add significantly
to the risks of inflation.
cent. On the. basis of these assumptions, simulation of the model indicated that the unemployment rate would decline modestly from its
levelof 7.2 percent in 1984(Q4) to 6.8 percent
in the fourth quarter of this year.
Most economic . forecasters outside the
Administration expect real GNP growth in 1985
to be less than the four percent rate assumed
in Illaking this forecast. Most forecasts cluster
around 3V2 percent growth. Thus, one possible
conclusion from these estimates would be that
it is. unlikely that much further progress will be
made toward lowering the nation's unemploy-
FOOTNOTES
1. Brian Motley, "How Soon will the U.S. Reach Full Employment? An Assessment Based on Okun's Law" Economic Review, Federal Reserve Bank of San Francisco,
Number 3, Summer 1984.
Charles S. Morris, "The Productivity 'Slowdown': A Sectoral Analysis," Economic Review, Federal Reserve Bank
of Kansas City, April 1984.
8. In each of the studies cited in the preceding footnote,
the influence of the business cycle on labor force participation and productivity is represented by changes in employment or unemployment.
2. For the purposes of this paper, the phrase "required
growth rate" is more descriptive than "potential growth
rate." The latter describes the rate at which the supply of
output could grow while the former is that at which demand
needs to grow to hold the unemployment rate constant.
9. The equations also include the change in the employment rate. In the simulations this term was set to zero after
1953(01).
3. Throughout this paper the phrase "adult population" refers to the civilian non-institutional population.
10. When both the current and lagged values of the required growth rate are included in the estimated equation,
none of their coefficients is individually significant, but their
sum is very close to the coefficient on the current value
when it alone is included.
4. Output per worker may, in turn, be decomposed into
output per hour and hours per worker. For simplicity, this
decomposition is not made in this paper.
5. Representing the unemployment rate by u and the employment ratio bye, it can be shown that din e is approximately equal to -duo This means that if the employment
ratio increases at an annual rate of one percent, the unemployment rate declines by one percentage point per year.
11. See Motley, op. cit., and Woodham, op. cit.
12. Woodham's results, for example, imply that over the
1974-1983 period it would have required a 2.3 percentage
point increase in the GNP growth rate to lower the unemployment rate by one point. See Woodham, op. cit.,
Table 4.
6. Motley, op. cit. and Douglas G. Woodham, "The Changing Relationship between Unemployment and Real GNP in
the United States," Research Paper No. 8407, Federal Reserve Bank of New York, September 1984.
13. The dependent variable in the estimated equation is
the quarterly change in the logarithm of the employment
ratio. For purposes of Chart 5, the fitted values have been
transformed into quarterly percentage point changes in the
unemployment rate.
7. Rose McElhattan, "Is the Economy Overheating?" unpublished paper, Federal Reserve Bank of San Francisco,
March 1984; George L. Perry, "Potential Output and Productivity," Brookings Papers on Economic Activify,1, 1977;
54
@FedFRASER