A stable money demand: looking for the right monetary aggregate.
Teles, Pedro ; Zhou, Ruilin
Introduction and summary
The stability of a money demand relationship has been a major
concern in monetary economics for the last 50 years. It is conventional
to call the relationship between real money, a nominal interest rate,
and a measure of economic activity a money demand relationship. A stable
relationship between these variables helps answer important questions
such as the following: What is the average growth rate of money that is
consistent with price stability, given the average growth of the economy
and a stable nominal interest rate? Knowledge about the response of
money demand to changes in the nominal interest rate may also help
quantify the welfare gains from a low average inflation rate.
In an essay in honor of Allan Meltzer, Lucas (1988) reassesses the
evidence on the stability of the money demand estimated by Meltzer
(1963) and justifies that stability not only on empirical grounds but
also on theoretical ones. He shows that there is a theoretical
equilibrium relationship between real money, a nominal interest rate as
a measure of the opportunity cost of money, and gross domestic product
(GDP) as a measure of transactions that is not exactly a money demand,
but that is indeed stable. He estimates that equilibrium relationship
using the monetary aggregate M1 as the measure of money with data up to
1985 and argues that there is a stable relationship between those
variables with a unitary income elasticity and with a strong negative
response of real balances to the nominal interest rate (see box 1 for
definitions of the different monetary aggregates).
BOX 1
Monetary aggregates
M1: Currency held by the public
+ Travelers checks
+ Demand deposits
+ Other checkable deposits, including
NOWs (negotiable orders of withdrawal
accounts), ATS (automatic transfer
services), and share draft account
balances.
M2: M1
+ Savings deposits, including MMDAs
(money market deposit accounts)
+ Small-denomination time deposits
+ Retail money market mutual funds
M3: M2
+ Institutional MMMFs (money market
mutual funds)
+ Large-denomination time deposits
+ Repurchase agreements
+ Eurodollars
MZM (Money zero maturity): M2
- Small-denomination time deposits
+ Institutional MMMFs
Note: The basic framework for these definitions was
adopted in 1980.
The relationship estimated by Lucas (1988) holds very well until
the mid-1980s but not well at all after that. This could be because the
demand for money is not a stable relationship after all, contrary to
what the simple model would suggest. Another conclusion, which is our
view, is that the measure of money is not a stable measure. In
particular, we argue that technological innovation and changes in
regulatory practices in the past two decades have made other monetary
aggregates as liquid as M1, so that the measure of money should be
adjusted accordingly. We show that once a more appropriate measure of
money is taken into consideration, the stability of money demand is
recovered.
Banking deregulation in the 1980s and 1990s and financial
innovation in the 1990s associated with the development of electronic
payments indeed suggest we need to reconsider the measure of
transactions demand for money. Until the end of the 1970s, the
transactions demand for money was well approximated by M1. Since then,
however, a series of sweeping regulatory reforms and technological
developments in the banking sector have significantly changed the way
banks operate and the way people use banking services and conduct
transactions. First, the Depository Institutions Deregulation and
Monetary Control Act of 1980 abolished most of the interest rate
ceilings that had been imposed on deposit accounts since the Banking Act
of 1933 and authorized nationwide negotiable orders of withdrawal
accounts (NOWs), which are interest-bearing checking accounts classified
in M1. Furthermore, the Garn-St Germain Depository Institutions Act of
1982 authorized money market deposit accounts (MMDAs), interest-bearing
savings accounts that can be used for transactions with some
restrictions. MMDAs are classified in M2 (see box 1). These two major
banking reforms blurred the traditional distinction between the monetary
aggregates M1 and M2 in their transactions and savings roles. Second,
the rapid development of electronic payments technology and, in
particular, the growing use of credit cards and the automated
clearinghouse (ACH) as means of payment, reinforced the effect of the
banking reforms in slowing down the growth of M1. Both credit cards and
ACH transactions can be settled with MMDAs and, therefore, with M2
rather than M1. Third, the widespread adoption of retail sweep programs
(discussed in detail later) by depository institutions since 1994, which
reclassify checking account deposits as saving deposits overnight,
reduced the balances that were classified in M1 by almost half.
These fundamental changes in the regulatory environment and the
transactions technology justify the use of a different measure of money
after 1980. The measure MZM (money zero maturity) includes balances that
can be used for transactions immediately at zero cost and was initially
proposed by Motley (1988) and Poole (1991) as a more appropriate measure
of the transactions demand for money (see box 1). We show that changing
the monetary aggregate measure from M1 to MZM from 1980 onward preserves
the long-run relationship between real money, the opportunity cost of
money, and economic activity up to a constant factor.
In the next section, we show evidence of the difficulty in
explaining the behavior of M1 with the behavior of GDP and the nominal
interest rate. Then, we discuss why MZM, rather than M1, is an
appropriate measure of the transactions demand for money in the past two
decades. Finally, we estimate a money demand equation derived from a
simple transaction technology model, using M1 as the monetary aggregate
before 1980 and MZM after 1980 and obtain evidence in support of the
stability of money demand.
An unstable demand for M1
Figures 1 and 2 reproduce figures 1 and 4 in Lucas (2000),
extending the data through 2003. (1) Figure 1 suggests that, over the
course of the past century, movements in the ratio of M1 to nominal GDP have been inversely related to movements in the short-term nominal
interest rate. Following Meltzer (1963), Lucas (1988) uses data up to
1985 to estimate a money demand equation, using M1 as the measure of
money and a short-term nominal interest rate as the measure for the
opportunity cost of money, and confirms Meltzer's result that the
income elasticity is about 1.0 and the interest elasticity is high. (2)
Lucas (1988) reports an interest rate semi-elasticity between 0.05 and
0.1, which for an interest rate of 4 percent corresponds to an interest
elasticity between 0.2 and 0.4. Using data from 1900 through 1994, Lucas
(2000) reports an interest elasticity of 0.5, consistent with a shopping
time (3) model for money demand. The money demand equation derived in
Lucas (2000) is
1) [M.sub.t]/[P.sub.t] = [alpha][Y.sub.t][i.sub.t.sup.-[gamma]],
where [M.sub.t] is the monetary aggregate measured by M1, Pt is the
price level, [Y.sub.t] denotes the aggregate output level, it is the
short-term nominal interest rate, and the interest elasticity is [gamma]
= 0.5, while [alpha] is a constant term. Real money responds to output
with a unitary elasticity and negatively to the nominal interest rate
with a relatively large elasticity, so that in response to a 1 percent
increase in the nominal interest rate, the real money demand declines by
0.5 percent. Output is a measure of transactions, and people demand more
money when the volume of transactions is higher. The unitary income
elasticity is consistent with real money growing at the same average
rate as output. The negative response of the demand for money to the
nominal interest rate makes sense because the short-term nominal
interest rate is the foregone return from holding non-interest-bearing,
but liquid, money balances.
[FIGURES 1-2 & 4 OMITTED]
Figure 2 plots the actual and estimated real balances using the
money demand equation above with an interest elasticity [gamma] = 0.5.
Clearly, one would expect a larger reaction of real balances to the
lower interest rates in the 1980s and 1990s. A lower elasticity of 0.32,
instead of 0.5, would still not get close to being consistent with the
actual low growth in M1. This is apparent from figure 3, where we plot
the logarithm of the ratio of M1 to nominal GDP against the logarithm of
the nominal interest rate for the period 1900-2003. Figure 3 indicates
that there could be a different money demand relationship for each of
the three periods 1900-79, 1980-94, and 1995-2003. The solid line
corresponds to the estimated elasticity of 0.32 for the entire 1900-2003
period. The interest elasticity for the three subperiods would be 0.26,
0.12, and -0.07, respectively, so that the response to the interest rate
movements over time would be less and less pronounced. The constant term
also changes across the three periods, corresponding to the increased
inability to explain the low growth in M1 with movements in economic
activity and the nominal interest rate.
[FIGURE 3 OMITTED]
Ball (2001) argues that the data after 1987 represent evidence
against a stable money demand. He estimates a linear relationship
between the logarithm of real money, the logarithm of output, and a
nominal interest rate for subperiods of 1903-94. For the period 1903-87
the evidence is consistent with a stable relationship with a unitary
income elasticity and a relatively high interest elasticity, as shown by
Lucas (1988) and Stock and Watson (1993). However, the need to account
for the low reaction of M1 to lower interest rates and higher output
after 1980 lowers both the estimated interest elasticity and income
elasticity. The relatively low income and interest elasticity in the
postwar period (1947-94) are significantly different from the unitary
income elasticity and relatively high interest elasticity in the prewar period (1903-45), leading Ball to argue against a stable long run money
demand. (4)
Measuring money used for transactions
In this section, we argue that M1 was a good measure of money used
for transactions before major developments in banking regulation and
financial innovation starting in the early 1980s. Since then, a measure
such as MZM has become more appropriate.
Figure 4 (p. 54) shows the trend growth of all four monetary
aggregates: M1, M2, M3, and MZM since 1959 (data for MZM are available
since 1974). In particular, since 1980, M1 has grown at a low rate (5.1
percent) and flattened after 1994. In contrast, average MZM growth has
been 9 percent since 1980. The rapid expansion in MZM is evident in the
figure; its value surpassed that of M2 in 2001.
Before 1980, M1, consisting of currency, non-interest-bearing
demand deposits, and a very small amount of interest-bearing checkable
deposits (see figure 5 (p. 54) and discussion in the next section) was
the primary transaction monetary aggregate. The main components of M2,
other than M1, were savings deposits, mostly passbook savings accounts
on which checks could not be written, and small time deposits. Neither
could be directly used for transactions. The other component of M2,
retail money market mutual funds (MMMFs), a nonbank financial instrument
(some have restricted check-writing capacity) developed in the mid-1970s
and remained very small, as shown in figure 5. Therefore, there was a
clear distinction between M1 and the components of M2 other than M1
before 1980. The former could be used for transactions at zero cost and
did not bear interest, while the latter were interest-bearing
instruments that could not be directly used for transactions. Since
then, this distinction has become less clear-cut. Three major
developments in banking regulation and financial innovation are
responsible for the change.
[FIGURE 5 OMITTED]
Financial innovation and regulatory reform since 1980
Banking deregulation
The banking deregulation that ensued in the late 1970s and early
1980s changed the banking industry landscape from a highly regulated one
into a fairly competitive one. An unavoidable consequence of the
deregulation was the blurring of the various components of M1 and M2 as
transaction/saving instruments.
The reform started in the 1970s when many commercial banks and
depository institutions were struggling to survive in the high
inflation, high interest rate environment, with their hands tied by many
regulations, in particular, Federal Reserve Regulation Q. This
regulation prohibited interest payment on demand deposits and imposed
interest-rate ceilings on time and savings deposits. The first move
toward deregulation was the authorization granted by several
northeastern states to state-chartered mutual saving banks, and later
other depository institutions, to offer NOWs, an interest-bearing
transaction account. (5) Other products or services designed to provide
consumers with more efficient cash management tools developed at the
same time. For example, commercial banks and thrifts were able to
provide prearranged automatic transfer services (ATS) from
consumers' savings accounts to their checking accounts, customers
could transfer their savings balances to checking remotely, and
federally chartered credit unions were allowed to issue share drafts.
These innovations were officially sanctioned by the Depository
Institutions Deregulation and Monetary Control Act in 1980. More
specifically, the act eliminated most of the interest rate ceilings on
time deposits and savings accounts and authorized the use of checkable
NOW accounts and other interest-bearing accounts (such as ATS and share
draft accounts at credit unions) by individuals and non-profit
organizations. The privilege was extended to all levels of government
agencies in 1982. The only exception is demand deposits of corporations,
on which the 1933 prohibition of interest payment remains in effect
today. (6) These regulatory changes allowed depository institutions to
compete more effectively for funds; they also removed the impediments for depositors to earn the market rate of return on their transaction
balances. The direct consequence of the act is the prevalent use of
interest-bearing checking accounts.
A second major regulatory banking reform was the Garn-St Germain
Depository Institutions Act of 1982. It authorized the creation of money
market deposit accounts (MMDAs) to compete with MMMFs. Classified as an
M2 account, an MMDA is an interest-bearing account that carries no
reserve requirements. The account offers limited transaction capacity:
no more than six withdrawals by check or pre-authorized transfer per
month, but no limit on deposits or number of withdrawals from an ATM, by
mail, or at a branch. This act led to a substantial increase in the use
of checkable savings accounts for transactions.
The deregulatory measures of the early 1980s, allowing for interest
payments on checking accounts and checking privileges on savings
accounts, blurred the distinction between transaction and saving
deposits, consequently blurring the distinction between M1 and M2.
Electronic payments
Following the banking deregulation in the 1980s, the rapid
development of electronic payments in the 1990s also fostered the use of
components of broader monetary aggregates for transaction purposes.
Credit cards are particularly responsible for this.
Credit cards are often used as a substitute for cash, check, and
debit card transactions. Monthly balances on a credit card can be paid
with an automated clearing house (ACH) transaction or a check written on
a checking account or checkable savings account. (7) The fact that there
is a single payment at a certain date reduces the need to maintain high
daily balances in checking accounts to meet the uncertain sequence of
transaction and payment flows. This reduction is reinforced by the fact
that it is possible to use checkable savings accounts to pay for credit
card balances. The total number of credit and debit card transactions
almost tripled in 1990s, from 10.8 billion in 1990 to 30 billion in 2000
(Humphrey, 2002).
The ACH is another important development in electronic payments.
ACH is a nationwide mechanism that processes electronically originated
batches of credit and debit transfers. ACH credit transfers include
direct deposit payroll payments and payments to contractors and vendors.
ACH debit transfers include consumer payments on insurance premiums,
mortgage loans, and other kinds of bills. This form of electronic bill
payment is a substitute for checks. A share of these transactions is
from checkable savings accounts, classified in M2, instead of from
checking accounts. The Federal Reserve Banks operate the nation's
largest ACH operation, which in 2000 processed more than 80 percent of
commercial interbank ACH transactions. In 1991, the Federal Reserve
processed 1,119 million commercial (not including government) ACH
transactions (valued at $5,549 billion), while in 2003 the number jumped
to 5,588 million transactions ($13,952 billion), an annual increase of
14.3 percent in volume (8 percent in value).
Retail sweep programs
A third important development leading to the confounding roles of
M1 and M2 for transactions and savings was the adoption of retail sweep
programs that reclassify checking account deposits as savings deposits
overnight. Since 1994, commercial banks have started using
deposit-sweeping software to dynamically reclassify the balances in
checking accounts above a certain level as MMDAs and to reclassify them
back when the balances on the checking accounts are too low. By adopting
the practice, depository institutions avoid reserve requirements on the
reclassified portion of the checking account (the reserve requirement on
demand deposits, ATS, NOW, and other checkable deposits can be as high
as 10 percent, depending on the size of the institution). The software
effectively creates a shadow MMDA for every checking account, based on
the customer's payment patterns, subject to the constraint that the
number of "transfers" (reclassifications) from an MMDA to a
checking account does not exceed six each month. The shadow account is
included in M2, but not in M1.
More and more banks are adopting the retail sweep programs. As
indicated by figure 6, (8) the total amount of sweeps of transaction
deposits into MMDAs has been rising steadily since 1994, from zero to an
amount nearly equal to transaction deposits in M1. According to the
Federal Reserve Board's estimates, as of December 2003, the sweeps
of transaction deposits into MMDAs were approximately $575.5 billion,
while total transaction deposits in published M1 were $621.3 billion.
The widespread use of retail sweep programs substantially affected the
growth of M1. The nominal value of M1 has been almost flat since 1994.
[FIGURE 6 OMITTED]
MZM as a better measure of transaction balances since 1980
As a result of the financial innovations and regulatory reforms
since 1980, components of the "transactions" aggregate M1 bear
interest, and components of the "savings" aggregate M2 are
used for transactions. These changes call for a reconsideration of the
measure of transactions demand for money and its opportunity cost. More
specifically, if there is to be a stable, long-run relationship between
real money, its opportunity cost, and transactions, a different measure
of money and its opportunity cost may be necessary to sustain the
relationship.
Motley (1988) and Poole (1991) argue that the present
classification of monetary aggregates (M1, M2, M3) is inherently
arbitrary, in particular in light of the banking industry developments
discussed above. They believe that the important distinction should be
whether the deposit has a specified term to maturity. For example, NOW
accounts in M1 and MMDAs in M2 are nonterm deposits, but small and large
denomination time deposits in M2 and M3 are term assets. Nonterm
deposits can be readily converted into transaction balances, or in other
words, are fully liquid. On the other hand, term deposits that have to
be liquidated before maturity incur the cost of an early withdrawal
penalty. In an environment free of government regulation, and within the
limits of technology constraints, agents' portfolio decisions
depend on their liquidity preferences and the return on the assets. The
term/nonterm distinction of monetary aggregates is aligned with private
agents' incentives.
Motley proposed classifying all nonterm deposits, money that can be
accessed without notice and at par, as a new monetary aggregate. Poole
coined the name MZM (money zero maturity) for the measure. Specifically,
MZM is defined as
MZM = M2 - Small denomination time deposits + Institutional MMMFs.
Institutional MMMFs, currently classified in M3, are
interest-bearing checkable accounts that allow holders to get around the
zero-interest demand deposits restriction.
The demand for money
In appendix 1, we show that it is possible to derive from a simple
stochastic general equilibrium monetary model the equilibrium
relationship
2) [M.sub.t]/[P.sub.t] = [alpha][Y.sub.t][([i.sub.t] -
[i.sup.m.sub.t]).sup.-v],
which is a variant of equation 1 that accounts for the fact that
money may earn interest. This is an exact equilibrium relationship of
observable economic variables. As pointed out in Lucas (2000), this is
reason to think that the empirical analog to that relationship, which
will have to account for measurement error, is a stable relationship.
The equilibrium relationship in equation 2 is not exactly a money demand
function, computed from the decision by households on how much money to
hold, given economic variables out of their control, namely the prices
of goods and assets and endowments. It does, however, look like the
money demand functions that are commonly estimated.
In this section, we estimate the empirical counterpart of the money
demand equation above using ordinary least squares (OLS). First, like
Lucas (1988, 2000), we use M1 as the measure of money and a short-term
nominal interest rate as its opportunity cost. As mentioned before, the
estimated interest elasticity is 0.32, lower than the 0.5 reported by
Lucas (2000) for the period 1900-94. If we estimate the elasticity for
three subperiods, 1900-79, 1980-94, and 1995-2003, the interest
elasticities are lower, 0.26, 0.12, -0.07, respectively. It would also
be apparent that the curves would be shifted down.
Next, we estimate equation 2 using M1 as the measure of money for
the period 1900-79 and MZM for the period 1980-2003. Because components
of M1 bore no interest before 1980 (mostly cash and demand deposits) and
components of MZM are interest-bearing after 1980 (NOWs, MMDAs, MMMFs),
we assume that [i.sup.m.sub.t] = 0 before 1980 and we set
[i.sup.m.sub.t] to MZM's own rate after 1980. MZM's own rate
is a weighted average of the returns on the different components of MZM.
(9) We allow different intercepts for the two periods, because it is not
reasonable to impose the coincidence of the two series, M1 and MZM, in
1980, but we do impose a common interest elasticity. The estimated money
demand equation is as follows,
[MATHEMATICAL EXPRESSION NOT REPRODUCIBLE IN ASCII.]
If we allowed for separate interest elasticity for the two periods
in the regression, the two elasticities would be 0.26 and 0.2,
respectively, for the first and second periods. (10)
Figure 7 plots the logarithm of M1/nominal GDP for the period
1900-79 and that of MZM/nominal GDP for the subsequent period 1980-2003
against the logarithm of the opportunity cost of using these balances,
along with the linear regression lines. The roughly common elasticity
across the two periods suggests that the response of the money aggregate
to changes in its opportunity cost, in percentage terms, has remained
stable over the last century, as long as one uses the appropriate
definition of monetary aggregate and its opportunity cost. The upward
shift of the function (smaller intercept) reflects the fact that MZM and
M1 include different liquid assets, even if all are zero maturity. In
figure 8, we plot the actual and estimated real money demand using M1
for the period 1900-79 and MZM for the period following the deregulation
and financial innovation.
[FIGURES 7-8 OMITTED]
Conclusion
While real M1 has increased very little in the last quarter
century, nominal interest rates have come down considerably. If the
interest elasticity were the one reported by Lucas (2000), we would
expect a substantial increase in M1 that did not occur. This could
indicate that the money demand relationship estimated by Meltzer (1963)
and Lucas (1988), among many others, is not a stable equilibrium relationship. Instead, we argue that M1 is not the appropriate measure
of money, following the regulatory reforms and innovation in electronic
payments since the early 1980s. If we use an alternative, more
appropriate measure of money, that is, MZM or money zero maturity, the
long-run relationship between money and its opportunity cost is
preserved. We estimate the interest elasticity to be 0.24, so that a 1
percent increase in the opportunity cost of holding money induces a 0.24
percent decline in real money balances.
Why do we care about estimating a stable money demand at the cost
of an unstable measure of money? In addition to the theoretical interest
of this issue, there is also a practical aspect to it. It is a worthy
objective of a monetary authority to provide elastic (11) liquidity at
stable prices. A stable estimate of money demand, whatever the
appropriate monetary aggregate might be, is an important tool in
performing this task.
APPENDIX 1: MONETARY MODEL
Here, we consider a simple transaction technology monetary model
and derive an equilibrium relationship between real money, the
opportunity cost of money, and output that holds exactly. That stable
relationship justifies on theoretical grounds the stability of the
empirical money demand equation estimated in this article.
The economy consists of an infinitely lived representative
household/firm and a government. Production uses labor according to the
linear technology
[Y.sub.t] = [A.sub.t][n.sub.t],
where [Y.sub.t] is output and [n.sub.t] is time used for
production. [A.sub.t] is a stochastic technological parameter realized
in the beginning of period t. The history of these shocks up to period t
(or state at t) is denoted by [A.sub.t] . The initial realization
[A.sub.0] is given.
Households have preferences over consumption [c.sub.t] described by
the utility function:
3) [E.sub.0] [[infinity].summation over (t = 0)] [[beta].sup.t]
[[c.sup.1-[sigma].sub.t] - 1] / [1 - [sigma]],
where [beta]?is a discount factor.
Households conduct transactions according to the Cobb-Douglas
transaction technology
4) [c.sub.t] = [xi][([A.sub.t][s.sub.t]).sub.v]
[([M.sub.t]/[P.sub.t]).sup.1-v],
where [M.sub.t] is money balances, [P.sub.t] is the price of the
good in units of money, and [s.sub.t] is the time used for transactions.
The technology parameter is the same for the two technologies,
production of the good, and transactions.
The total amount of time used for transactions and for the
production of the good is normalized to one.
[s.sub.t] + [n.sub.t] = 1.
The government issues money [M.sup.S.sub.t] and makes transfers to
the households [T.sub.t].
In the beginning of period t, households enter an assets market
where they purchase money balances [M.sub.t] that pay net interest
[i.sup.m.sub.t] in the following period, as well as nominal bonds
[B.sub.t] that pay interest [i.sub.t] and [Z.sub.t+1] units of
state-contingent nominal securities, with price [z.sub.t+1], normalized
by the probability of occurrence of state [A.sup.t+1], in units of
currency at t that pay one unit of money at the beginning of period t+1
in a particular state [A.sup.t+1]. Subsequently, they enter a goods
market where they purchase consumption with [M.sub.t], according to the
transaction technology in equation 4. They also receive total income
[P.sub.t][A.sub.t] (1 - [s.sub.t]), as well as nominal transfers, net of
taxes, [T.sub.t]. The period by period budget constraints are
5) [MATHEMATICAL EXPRESSION NOT REPRODUCIBLE IN ASCII.]
A competitive equilibrium is a set of prices and quantities such
that a) households choose [{[c.sub.t], [s.sub.t], [B.sub.t], [M.sub.t],
[Z.sub.t+1]}.sup.[infinity].sub.t=0] to maximize utility in equation 3
subject to the restrictions in equations 4 and 5 together with a
no-Ponzi games condition on the holdings of assets, given [{[P.sub.t],
[i.sub.t], [i.sup.m.sub.t], [z.sub.t+1]}.sup.[infinity].sub.t=0] and
[{[T.sub.t]}.sup.[infinity].sub.t=0]; b) the government satisfies
[M.sup.S.sub.t] = (1 + [i.sup.m.sub.t-1]) [[M.sup.S.sub.t-1] +
[T.sub.t]]; and c) markets clear, so that
6) [B.sub.t] = 0,
7) [Z.sub.t+1] = 0,
8) [M.sub.t] = [M.sup.s.sub.t],
9) [c.sub.t] = [A.sub.t] (1 - [s.sub.t]).
We could derive a money demand equation using the first order
conditions of the households' problem. That equation, however,
would be a function of all the prices, including the prices on the state
contingent nominal debt, as well as unobservable shocks, and, therefore,
could not be directly estimated using simple econometric methods.
Instead, the first order conditions can be used to derive the following
relationship
10) [m.sub.t]/[c.sub.t] = [alpha][([i.sub.t] -
[i.sup.m.sub.t]).sup.-v], t [greater than or equal to] 0,
where [m.sub.t] denotes real money balances, [m.sub.t] =
[M.sub.t]/[P.sub.t],
and [alpha] = [([1 - v]/v).sup.v] [[xi].sup.-1]. As pointed out by
Lucas (1988),
this equation is not exactly a money demand, rather it is an
equilibrium relationship between real money, consumption, and the
opportunity cost of holding money that holds exactly in this stochastic
environment. Given that in this simple model consumption coincides with
output, [c.sub.t] = [Y.sub.t], equation 10 can be rewritten as
11) [M.sub.t]/[P.sub.t] = [alpha][Y.sub.t][([i.sub.t] -
[i.sup.m.sub.t]).sup.-v],
with interest elasticity equal to the Cobb-Douglas transactions
technology parameter v. (1) Note that the derived income elasticity is
one.
The assumptions on the homogeneity of the transaction technology
and technology progress in the two sectors, as well as assumptions on
the utility function, imply that the long-run income elasticity is one.
Alternative assumptions could imply a trend in money demand.
Empirically, this could be captured by a time trend or by an income
elasticity different from one, as in Ball (2001). Instead, we argue that
the evidence is consistent with a stable long-run money demand with a
unitary income elasticity and no time trend, if the monetary aggregate
is appropriately defined to capture the technological and regulatory
innovations since 1980.
(1) Lucas (2000) reports the interest elasticity to be v = 0.5. He
justifies this result by arguing that equation 10 with v = 1/2 is an
approximation to the equilibrium relationship when the transaction
technology is Baumol-Tobin. In fact, if the transaction technology was
Baumol-Tobin, [s.sub.t] = [eta]([c.sub.t]/[m.sub.t]), the money demand
equation 10 would be, [m.sub.t]/[c.sub.t] = [omega]
[([A.sub.t]/[c.sub.t])).sup.5] [([i.sub.t] - [i.sup.m.sub.t]).sup.-.5],
where [omega] = [[eta].sup..5]. The approximation amounts to
ignoring the term [([A.sub.t]/[c.sub.t]).sup..5].
APPENDIX 2: DATA USED IN FIGURES AND REGRESSIONS
The following is a list of data used in the figures and regressions
for this article. Unless explicitly specified, all monetary aggregates
are in billion of dollars and are not seasonally adjusted annual data
(we take the December value of each year as the entire year's
value). (1)
M1 1900-14: U.S. Bureau of the Census (1960, Series X-267).
1915-58: Friedman and Schwartz (1971, pp.708-722, table A1, column 7).
1959-2003: Federal Reserve Board,
www.federalreserve.gov/releases/h6/hist/h6hist1.txt.
M2 Federal Reserve Board,
www.federalreserve.gov/releases/h6/hist/h6hist1.txt.
M3 Federal Reserve Board,
www.federalreserve.gov/releases/h6/hist/h6hist1.txt.
MZM Federal Reserve Bank of St. Louis, FRED database,
http://research.stlouisfed.org/fred2/data/MZMNS.txt.
Other checkable deposits (quarterly frequency) FRB data available
through Haver Analytics (FMOTN in USECON).
MMMFs (quarterly frequency) FRB data available through Haver
Analytics (FMGMN in USECON).
Institutional money market mutual funds (quarterly frequency) FRB
data available through Haver Analytics (FMIOMN in USECON).
Transaction deposits swept into MMDAs (Cumulative) FRB data
available through Haver Analytics (FMSWEEP in USECON).
Demand deposits FRB data available through Haver Analytics (FMDN in
USECON).
Price deflator 1900-28 (1929 = 100): U.S. Bureau of the Census
(1960, Series F-5). 1929-2003 (2000 = 100): BEA data available through
Haver Analytics (DAGDP in USECON or USNA). (2)
Real GDP 1900-28 (millions of 1929 dollars), Kendrick (1961, Table
A-III). 1929-2003 (in chained 2000 dollars), BEA data available through
Haver Analytics (GDPHA in USECON or USNA). (3)
Nominal interest rate 1900-69: Friedman and Schwartz (1982, table
4.8, column 6), defined as short-term commercial paper rate. 1970-2003:
three-month commercial paper, FRB data available through Haver
Analytics, FFP3 in USECON.
Opportunity cost 1900-79: M1's opportunity cost is defined as
the nominal interest rate for this period. 1980-2003: MZM's
opportunity cost = three-month T-bill rate (Secondary Market)--MZM own
rate. Three-month T-bill rate: FRB data available through Haver
Analytics (FTBS3 in USECON). MZM own rate: Federal Reserve Bank of St.
Louis, FRED database, http://research.stlouisfed.org/fred2/data/
MZMOWN.txt.
(1) We follow Lucas (2000).
(2) These two series overlap in 1929 and using the ratio of the two
series' values in 1929, we construct a new price deflator that goes
from 1900 to 2003, with 2000 = 1.0.
(3) From these two series, we construct a new real GDP in 2000
dollars using the new price deflator (2000 = 1.0).
REFERENCES
Ball, Laurence, 2001, "Another look at long-run money
demand," Journal of Monetary Economics, Vol. 47, pp. 31-44.
Carlson, John B., Dennis L. Hoffman, Benjamin D. Keen, and Robert
H. Rasche, 2000, "Results of a study of the stability of
co-integrating relations comprised of broad monetary aggregates,"
Journal of Monetary Economics, Vol. 46, No. 2, pp. 345-383.
Friedman, Milton, and Anna Schwartz, 1982, Monetary Trends in the
United States and the United Kingdom, 1867-1975, Chicago: University of
Chicago Press, for the National Bureau of Economic Research.
--, 1971, A Monetary History of the U.S. 1867-1960, Princeton, NJ:
Princeton University Press.
Humphrey, David B., 2002, "U.S. cash and card payments over 25
years," Florida State University, mimeo.
Kendrick, John W., 1961, Productivity Trends in the United States,
Princeton, NJ: Princeton University Press, for the National Bureau of
Economic Research.
Laporte, Anne Marie, 1979, "Proposed redefinition of money
stock measures," Economic Perspectives, Federal Reserve Bank of
Chicago, March/April, pp. 7-13.
Lucas, Robert E., Jr., 2000, "Inflation and welfare,"
Econometrica, Vol. 68, No. 2, pp. 247-274.
--, 1988, "Money demand in the United States: A quantitative
review," Carnegie-Rochester Conference Series on Public Policy,
Vol. 29, pp. 137-168.
Meltzer, Allen H., 1963, "The demand for money: The evidence
from the time series," Journal of Political Economy, Vol. 71, pp.
219-246.
Motley, Brian, 1988, "Should M2 be redefined?," Review,
Federal Reserve Bank of San Francisco, Winter, pp. 33-51.
Poole, William, 1991, testimony before the U.S. Congress, Committee
on Banking, Finance, and Urban Affairs, subcommittee on Domestic
Monetary Policy.
Stock, James H., and Mark W. Watson, 1993, "A simple estimator
of co-integrating vectors in higher order integrated systems,"
Econometrica, Vol. 61, pp. 783-820.
U.S. Bureau of the Census, 1960, Historical Statistics of the
United States, Colonial Times to 1957, Washington, DC: Government
Printing Office.
NOTES
(1) To be able to make comparisons, we use the same data as Lucas
(2000) for relevant data analysis and figures. In particular, M1, real
GDP, the price deflator, and the nominal interest rate are constructed,
as in Lucas (2000), from different data sources for different periods.
See the appendix for a detailed description of the data used in this
article.
(2) The income and interest elasticities measure the percentage
increase in real money in response, respectively, to a 1 percent
increase in real GDP and a 1 percent decline in the nominal interest
rate. The semi-elasticity measures the percentage increase in real money
induced by a decline in the interest rate of 100 basis points.
(3) In a shopping time model, there is a transactions technology
relating the volume of transactions to time and money used in performing
those transactions.
(4) The relatively low income elasticity is indistinguishable from
a time trend in money demand.
(5) The NOWs were first introduced in Massachusetts and New
Hampshire in 1972, then Connecticut, Maine, Rhode Island, and Vermont in
1976, followed by New York in 1978. See Laporte (1979).
(6) Business customers have several ways to minimize the loss of
interest on demand deposits. One way is the sweep programs developed
during the 1960s and 1970s that allow business demand deposits to be
swept overnight into interest-bearing accounts such as repurchase
agreements and money market mutual funds.
(7) The term checking account is used to mean demand deposits and
other checkable accounts, such as NOW accounts, classified in M1.
Checkable savings accounts are accounts classified in M2 that have
checking privileges.
(8) The Federal Reserve Board makes monthly estimates available on
the nationwide change in NOW accounts attributable to the implementation
of sweeps during the month. These are not the current amounts being
swept, and no data are available regarding the aggregate volume of
deposits currently affected by sweep programs. Depositories do not
report to the Federal Reserve the size of their sweep programs.
(9) The MZM data and the data on the rate of return on MZM are
provided by the Federal Reserve Bank of St. Louis.
(10) Our results are consistent with those of Carlson et al.
(2000), who find a stable cointegrating relationship between real MZM,
an opportunity cost measure, and a measure of economic activity, using
data for the period 1976-98. The income elasticity is not different from
one.
(11) Elastic currency is the wording used in the 1913 Federal
Reserve Act that established the Federal Reserve System.
Pedro Teles is a senior economist at the Federal Reserve Bank of
Chicago. Ruilin Zhou is an associate professor of economics at
Pennsylvania State University. The authors thank Larry Christiano, Craig
Furfine, Anne Marie Gonczy, and Francois Velde for comments and
discussions. They also thank David Hwang for excellent research
assistance.