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The Economics of Bank Security
Forecasting Inflation: Does the Method Make
a Difference?
The Fed in Print

IN THIS ISSUE . . .

THE ECONOM ICS OF BANK SECURITY

Timothy H. Hannan

3-8

. . .With bank crime figures rising, some par
ties have called on government to impose
tighter security requirements. But it's impos
sible to tell whether bank security is adequate
simply by looking at the raw statistics. So far as
economics is concerned, security levels can
be set too high as well as too low.
FORECASTING INFLATION: DOES THE
METHOD MAKE A DIFFERENCE?

Nariman Behravesh
9-17
...Y e s , answers the author. Mathematical
modeling has a better track record than other
forecasting tools, and it's capable of doing
even better.
THE FED IN PRINT

Doris Zimmermann

FEDERAL RESERVE BANK OF PHILADELPHIA
Business Review September/October 1976

18-27

A subject index of articles appearing in the
Federal Reserve Bulletin and in the reviews
published by System banks during the first
half of 1976.

v_____________________ J

On Our Cover: Lafayette and Washington Inspect Huddled Troops During the Terrible Winter at Valley
Forge. Steel engraving by Henry Bryan Hall (1808-1884) after a painting by Alonzo Chappel (1828-1887).
Photograph courtesy of the New York State Historical Association, Cooperstown, New York.
Born in London, Hall came to the United States and settled in New York in 1850, where he established
himself as an engraver and painter. A specialist in portraiture, Hall painted Napoleon III from life and
worked on the engraving of Sir George Hayter’s “ Coronation of Victoria” as well as etching American
heroes for collectors in New York and Philadelphia.
Chappel was born in New York and developed a considerable reputation as a painter there. His
illustrations of American military scenes enjoyed wide circulation in the last century.
Lafayette, portrayed in this engraving as a serious young man, was only nineteen when he came to
America in the summer of 1777 and was appointed major general by the Congress. Washington was
appalled at the distribution of honorary commissions to visitors from abroad, but Lafayette learned quickly.
He rode with Washington at the Brandywine in September, sustaining a wound in the leg, and accompa
nied him into winter quarters three months later.
Valley Forge was poverty in the midst of plenty. There were no shortages in the surrounding countryside
or in nearby Philadelphia, yet neither the Congress nor the populace would support Washington’s
freezing, starving troops. Lafayette followed his commander’s example in subsisting as many soldiers as he
could out of his private fortune.

BUSINESS REVIEW is edited by John J. Mulhern and produced in the Department of Research.
Comments on articles are welcome and should be addressed to their authors.
Please direct requests for copies and subscriptions to the Department of Public Services, Federal Reserve
Bank of Philadelphia, Philadelphia, Pennsylvania 19106, telephone (215) 574-6115.

SEPTEMBER/OCTOBER 1976

The Economics of
Bank Security
By Timothy H. Hannan*
between 1969 and 1975. The raw figures say
that bank crime has been rising, and the
future appears to offer only more of the same.
Reports of bank crime trends have led to
increased public concern over the adequacy
of bank security measures. Calls for tighter
bank security are not new to bankers. In 1968,
an earlier wave of public concern led to the
passage of the Bank Protection Act, which
established minimum standards and imposed
penalties on banks that didn’t comply.To the
surprise of many, however, the Act has not
brought a reduction in bank crime, and ques
tions are being raised again about the desir
ability of higher standards and tougher
enforcement.
But before reacting to public pressure, it’s
useful to find out what story the figures really
tell. After all, they can be read in several ways,
and they may show on close inspection that
the increase hasn't been as dramatic as it
might seem at first glance. Further, there are
matters of cost and benefit to be considered

A man walked into a Hollywood bank
recently with the intention of holding it up.
Although temporarily successful, he was
apprehended before long as a result of over
looking the little problem of a getaway: he
had only one leg and he walked on crutches.
In Las Vegas, another stickup man found it
impossible to melt into a crowd after his
crime. As a dwarf, and a burly one at that, he
was easy to spot.
Many observers believe that the problem of
bank crime is getting worse, and bizarre
incidents such as these must make bankers
and enforcement officials fear that almost
everyone is getting into the act. According to
the FBI, the number of bank robberies
jumped from under two thousand to over
four thousand and bank larcenies doubled
*The author, who holds a Ph.D. from the University of
Wisconsin, specializes in banking and urban economics.
He joined the Philadelphia Fed’s Department of Research
in 1974.

BUSINESS REVIEW

SEPTEMBER/OCTOBER 1976

here. It may be possible to eliminate some
bank crime at a reasonable cost; but the cost
of reducing it drastically may be too high to
justify the effort. Finally, while government
standards for bank security may have some
role to play, requirements that are unduly
uniform may restrict bank managers' flexibil
ity to an unreasonable extent. Unless security
standards can accommodate the different
circumstances of individual banks, they may
impose an undue burden on bank managers
and the banking public.

CHART 1
TH E TR EN D IN BANK CRIME, TH O U G H UPWARD. IS N 'T S TEEP . . .
Number of Bank Robberies and Total Bank
Crimes, 1969-1975.

BANK CRIME INCREASES: A CLOSER LOOK
AT THE NUMBERS
Some people talk as if the rise in bank crime
were almost vertical. But, as Chart 1 shows,
the picture isn't that simple. Both robberies
and the bank crime total were slightly higher
in 1970 than in 1969 and higher still in 1971.
Robberies were up again slightly in 1972,
though the bank crime total was down that
year. Both were down the next year, with the
total falling almost to 1970 levels. The figures
went up again in 1974, rising above 1971
levels, but not by much. The biggest rise of all
came in 1975, when the bank crime total
jumped up to over five thousand from the
previous year's thirty-five hundred. But this
was one isolated year. Thus, while bank crime
has been trending upward since the begin
ning of the decade, the message isn't as clear
as many people believe.
Why Any Increase? Thieves prey on banks
because, as Willie Sutton said, that's where
the money is. The monetary rewards from a
successful bank robbery can be quite high.
But that doesn't account for the present
increase. Why is there more bank crime now
than there used to be? And why did bank
crime soar in 1975?
Some of the causes of bank crime are causes
of other kinds of crime, and nearly all kinds of
crime have been trending upward. The
increase in robberies of chain stores, for
example, has been almost twice the increase
of similar crimes against financial institutions.
Some criminologists believe that the rising

SOURCE:

American Bankers Association, Insurance and Protection Division.

incidence of heroin addiction and the reces
sionary decline in job opportunities account
for part of the crime-rate increase. The shor
tage of legitimate job opportunities coin
cided closely with increased criminal activity
in 1975.
Like other criminals, bank robbers have to
balance the reward of success against the risk
of capture and punishment. According to a
recent study (see Box), bank robbers are
aware of risk and cope with it by scanning the
horizon for the best possible targets and
victimizing bank offices that offer the biggest
take and the least prospect of being caught.
Recent changes in the structure of the bank
ing system may have altered the relation of
the robber's rewards to his risks, making
robbery and other kinds of bank crime less
4

FEDERAL RESERVE BANK OF PHILADELPHIA

BOX

AN ECO N O M IC APPROACH TO BANK THEFT
Perhaps not all bank robbers act out of calculation alone, but at least one investigation has
discovered a method in their madness. According to Tim Ozenne,who recently conducted a major
study of the economic aspects of bank robbery, thieves have available to them a large number of
targets or theft opportunities, and some of these are likely to be profitable.* Even ill-gotten gains
are not free; theft requires the expenditure of time, energy, and perhaps other scarce resources.
For this reason, according to Ozenne, thieves tend to choose from their array of opportunities only
those targets that offer the highest returns for the risk of being caught and punished. Thus both
bank security and efficient law enforcement are important deterrents to attacks on banks.
This simple observation points to important economic relations in the real world of bank theft.
According to Ozenne, ill-gotten return from theft, adjusted for the prospect of being caught and
punished, tends toward equality across targets. If targets in one area are characterized by net
returns to theft that are higher than those prevailing across the way, thieves will tend to shift their
activity out of the one area and into the other. With stricter law enforcement, the average take tends
to be higher. This observation is consistent with the fact that lowering the net return to robbery
causes robbers to abandon the less remunerative targets, leaving the higher paying targets to be
victimized. And it's reinforced by another finding: states that record the lowest number of bank
robberies per banking office also tend to record the highest average take. These findings together
tend to show that while making bank robbery more difficult will reduce the number of robberies by
discouraging marginal crimes, it won't have as great an effect on crimes against more remunerative
targets.!
*Tim Ozenne, “ The Economics of Bank Robbery,” Journal of Legal Studies 3 (1974), pp. 19-51.
tFor a more detailed discussion of the economics of criminal behavior see Timothy H. Hannan, “ Criminal
Behavior and the Control of Crime: An Economic Perspective,” Business Review, Federal Reserve Bank of
Philadelphia, November 1974, pp. 3-9.

risky. The most important of these changes is
the growth of branch banking.
Banks have branched out at an unprece
dented rate over the last decade, increasing
the total number of bank offices by more than
fifty percent nationwide. No longer are banks
the imposing downtown fortresses they once
were. They've moved a large part of their
volume to suburban offices with a warmer,
friendlier atmosphere for doing business.
While the change of style and location has
brought increased convenience to gardenvariety banking customers, it also has pro
vided more targets for tough customers that
the banks would rather not be serving.
Located outside high-density areas and with
easy access to high-speed roads for quick
getaways, suburban branch banks offer an
attractive prospect to people bent on making
illegal withdrawals.

The growth of branch banking has changed
the shape of the industry, and failing to feed it
into the analysis of bank crime statistics can
give us an incomplete picture of the situation.
Chart 2 graphically represents the growth in
bank crime and branch banking. It shows a
fall-off in the bank crime total from 1969 to
1973 broken by a high in 1971; the total then
trends up in 1974 but remains below the levels
from 1969 through 1972. The bank robbery
figures begin to rise in 1970, fall back in 1972,
and rise moderately in 1974. Both figures are
up sharply in 1975. But this rise may be
explained by a rapid decline in the number of
openings for legitimate work during 1975.
In short, when the bank crime figures are
adjusted for industry growth, the trend in
bank crime appears even less alarming for the
period 1969-74. And the 1975 situation,
though it doesn't look good, may be just a
5

SEPTEMBER/OCTOBER 1976

BUSINESS REVIEW

loss from crime has several alternatives. He
may install alarms and surveillance cameras,
or hire guards, or give his bank a fortified
look. Ingenuity would extend the list. His
choice should depend upon considerations
of cost and effectiveness. But no matter which
way he goes, it's sure to cost money. How
much will be saved by spending a thousand
dollars, or two or three thousand, for addi
tional bank security? Perhaps not enough to
make the investment worthwhile. If left to
himself, the bank manager may decide to risk
more frequent robberies and pay higher
insurance premiums. In any case, he has to
weigh the gain of reducing bank crime against
the cost of prevention.
All businesses have to consider the cost and
benefit of spending more on crime preven
tion. The cost is the expenditure made for
security, and the benefit is the forestalling of
losses. At least one recent study has found
that businesses actually do make greater
efforts to protect themselves where the pros
pect of loss from crime is relatively high and
security measures relatively cheap.1 There's
reason to believe that banks do the same.
Setting the Level. These considerations lead
to the following criterion for bank security:
the level of security maintained by banks
should be increased only as long as the addi
tional savings (however defined) justify the
additional cost. Savings in this case can be
thought of as the reduction in damages
caused by crime. Besides reducing the loss of
funds and damage to bank property,
increased security can reduce the number of
deaths and physical injuries that result from
robberies. And, to the extent that it deters
bank crime, increased security can save asso
ciated police, court, and correctional costs.
The amount of bank security indicated by
this criterion may not do away with successful
bank robberies because the cost of security
measures may be substantial. Would it really
be reasonable to eliminate all bank crime if,

C HART 2
AND AFTER A D JU S TM E N T FOR T H E INCREASE IN BRANCH OFFICES,
T H E UPWARD TR EN D IN BANK CRIME FL A TTE N S O UT.
Number of Bank Robberies and Total Bank
Crimes Per 1000 Bank Offices, 1969-1975.

1969
SOURCES'.

1970

1971

1972

1973

1974

1975

American Bankers Association, Insurance and Protection Divi
sion; Board of Governors of the Federal Reserve System, Annual
Reports 1969-1975.

one-year phenomenon on which no policy
deliberations should be based.
Putting the figures into perspective may
dispel the air of crisis from the bank crime
discussion. And it may help legislators and
regulators avoid being stampeded into pre
mature action. But it doesn't get to the basic
questions—how much security banks should
have and what, if anything, government
should do to make sure they have it.
HOW MUCH SECURITY?
Banks take steps to thwart criminals
because successful crimes impose a cost on
banks. A bank that operates in a high-crime
area may suffer losses both directly, through
removal of funds, and indirectly, through
higher insurance premiums.
The bank manager who wants to reduce his

^ee Ann P. Bartel, “ An Analysis of Firm Demand for
Protection against Crime,” Journal of Legal Studies 4
(1975), pp. 443-478.

FEDERAL RESERVE BANK OF PHILADELPHIA

age. Finally, insurance premiums can be set at
high levels for firms with heavy losses or poor
security protection—an additional incentive
to reduce crime loss. The use of devices such
as these sharply reduces, although it may not
eliminate, the tendency of insurance to foster
laxity in security precautions.2
The possibility that banks may not bear
certain losses from bank crime may be a more
important reason for concern over the ade
quacy of bank security measures. If some of
the costs of bank crime are not considered by
bank managers because those costs are not
borne by their own banks, then it's not likely
that banks, left on their own, would invest
enough in security.
Examples of such costs are not hard to find.
If a bank fails as a result of a major bank crime,
people other than the bank's stockholders
and management may bear some of the loss.
Nor do banks bear the full cost of death and
physical injury to bank personnel and cus
tomers. And then there are the often consid
erable police, court, and correctional costs
required to apprehend, convict, and punish
perpetrators of bank crimes—crimes that
might never have occurred if bank security
measures had been tighter. The avoidance of
such costs of doing business is regarded by
many economists as an important justification
for governmental action.3 But if government
action is necessary because bankers don't
take the full cost of bank crime into account,
what policy options are available to correct
the situation?

for example, it took half the gross national
product to do so? Successive reductions in
bank crime may require disproportionately
increasing outlays for security, and eliminat
ing all bank crime simply may not be worth
the cost required to do it.
Do Banks Pick the Appropriate Level of
Security? Neither the occurrence nor the
increase of bank crime proves that banks are
deficient in security. The extreme cost of
prevention may justify allowing some bank
crime to occur. Even an increase in bank
crime need not indicate that bankers are
choosing inadequate levels of security. Bank
crime may increase dramatically for many
reasons, and while a big increase may indicate
that banks should improve security, it gener
ally does not mean that they should improve it
to the extent that no increase in crime occurs.
It has been suggested that the availability of
insurance keeps bankers from investing in a
high enough level of security. Banks carry
insurance on their losses. The most common
kind is the bankers' blanket bond, which
covers losses from burglary, embezzlement,
forgery, larceny, and theft, as well as provid
ing robbery protection. Banks can buy other
policies to insure losses not covered by the
blanket bond. Many contend that because
banks rely on such insurance, they have little
financial incentive to spend money to hire
guards and install needed protective devices.
In other words, because of insurance, at least
part of the loss from bank crime is avoided by
the banks. As a result, they fail to protect
themselves adequately.
This moral hazard issue, however, is com
mon to many areas of insurance, and insur
ance companies generally deal with it by
employing such devices as deductibles, min
imum prevention requirements, and variable
premiums. The deductible provision excludes
some initial amount of loss from coverage, so
that the victim bears some of the loss and
hence still has an incentive to protect himself.
Minimum prevention standards require the
insured to take certain preventive measures,
such as the installation of a burglar alarm
system, in order to remain eligible for cover

2Perhaps because of such insurance devices, Ann Bartel
has concluded from a recent study of firm security
decisions that insurance generally is not used as a substi
tute for private protection. For more details, see Bartel,
“ An Analysis of Firm Demand for Protection against
Crim e.”
3
One might ask whether the justification for govern
ment intervention in bank security affairs doesn’t apply
to all other commercial establishments. If bankers don't
take adequate security precautions because they don’t
bear all the losses from criminal attack, can’t the same be
said of someone who owns a department store or an allnight restaurant?
The question here is one of cost. The cost that bank
crimes impose on the public may be relatively high in

SEPTEMBER/OCTOBER 1976

BUSINESS REVIEW

appoint security officers, formulate approved
security plans, and install certain minimal
devices and procedures. Establishing guide
lines is a more direct approach to bank pro
tection. It can lead to less than satisfactory
results, however, if security requirements are
set too high or too low or if they fail to
account for the diversity of banking organiza
tions and bank crime problems. A guideline
that requires every bank to install a surveil
lance camera and hire an armed guard, for
example, may be inadequate for banks with
major crime problems but excessive and
needlessly expensive for banks with only
minor difficulties. Inflexibility—always a
problem when centralized regulation repla
ces decisionmaking by managers who have a
first-hand knowledge of the situation—can
result in a considerable economic loss.

A BLUEPRINT FOR POLICY
Policy should aim for just that level of bank
security at which the savings justify the cost,
but all parties' savings and costs should be
figured in, not just the banks'. And it's clear
that the level of security that fits one bank may
be inappropriate to another. It may be desir
able for banks in low-crime areas located next
to police stations to invest very little in bank
security, for the savings from the higher
security levels may not justify the cost. At the
opposite extreme, it may be desirable for a
large bank facing a serious crime problem to
invest in the most comprehensive, up-to-date
security systems.
There are two ways to achieve the desired
level of bank security. The first would require
individual bank decisionmakers to take the
full consequences of their decisions into
account. This might involve charging bankers
for the losses that other members of society
incur as a result of bank crime—a charge that
would make it the bankers' interest to choose
higher levels of security protection. Whatever
its drawbacks, this approach has the distinct
advantage of enabling each bank to make its
own security decision after considering its
own unique situation.
The more usual government approach,
however, is the mandatory guideline. An
example of this approach is the Bank Protec
tion Act of 1968, which requires banks to

HASTE MAKES WASTE
The policymaker has good grounds for
approaching the subject of bank crime with
caution. The raw figures on crime trends can
be deceiving and generally do not serve as a
sound basis for policy. Even when the story
they tell is clear, they don't indicate how
much or what kind of security a bank should
invest in. That has to be determined in each
case by an analysis of cost and benefit, and the
analysis should take account of everyone who
gains or loses from bank security decisions.
Since security measures are not costless,
requiring more security than is justified by
crime reduction works out to a net loss. The
mere occurrence of bank crime, or even an
increase, is not a good argument for ever
tighter security requirements.
Different banks have different crime prob
lems, and guidelines won't work efficiently
unless they reflect this basic fact. Strict
reliance on a few rules could lead to too much
security in some cases and too little in others.
It's safe to expect bankers to protect them
selves whether or not the government issues
guidelines. And it's just possible that the
wrong kind of guideline would do as much
harm as no regulation at all.
S

comparison to losses from crimes against other commer
cial establishments. Bank failures, which could result
from successful bank crimes, long have been recognized
to have extraordinarily wide-ranging effects. Further,
since large sums of money usually are at stake, bank
crimes usually require a larger expenditure of criminal
justice resources. Indeed, it's not uncommon for the FBI
to spend more money investigating a bank robbery or
burglary than was taken during the offense. In the case of
a recent Maryland bank crime, for example, the cost of
investigation alone exceeded a quarter of a million dol
lars.
Though the administrative cost of government inter
vention in bank security decisions also can be quite high,
one can argue that intervention is less costly in the case of
banks because the regulatory apparatus already is in
place. For all these reasons, the argument for govern
ment intervention in bank security decisions need not
justify similar intervention elsewhere.

FEDERAL RESERVE BANK OF PHILADELPHIA

Forecasting
Inflation:
Does the
Method Make
a Difference?
By Nariman Behravesh*
Or rather, we rely on them precisely because
we don't know how the future will look.
Runaway inflation probably wouldn't have
been prevented by better economic forecast
ing, but its impact might have been softened.
Recognizing that their inflation forecasts
were off the mark, economists are taking a
close look at their forecasting methods. They
hope to get a better grip on price changes
from now on.

The double-digit inflation of 1974 and 1975
caught many economists by surprise. After
years of reliable service, their forecasting
tools had started to lead them astray. As a
result, businessmen and policymakers sud
denly found themselves called upon to adjust
to rapidly rising prices on very short notice.
What happened? What went wrong?
Part of the forecasting failure can be attrib
uted to the sheer intractability of events. The
oil embargo, the wage-price freezes, and the
agricultural shortages came out of the blue.
No one could have known about them very
far in advance, and no one could have known
that they would hit almost all at once. But that
doesn't get the forecasting tools off the hook.
They're supposed to help even when we
don't know exactly how the future will look.

WHERE DO FORECASTS COME FROM?
When economists forecast inflation rates,
they apply mathematical modeling tech
niques and their own powers of judgment to
historical information.1 A model is just a
mathematical description of some state of
^or a description of economic forecasting and of how
econometric forecasts differ from judgmental ones see
N. Behravesh, “ Forecasting the Economy with Mathe
matical Models: Is It Worth the Effort?" Business Review,
Federal Reserve Bank of Philadelphia, July/August 1975,
pp. 15-25.

*The author, who joined the Philadelphia Fed's
Department of Research in 1974, received his training at
the University of Pennsylvania. He specializes in econo
metrics and macroeconomics.

SEPTEMBER/OCTOBER 1976

BUSINESS REVIEW

affairs—in this case, the national economy.
The application of mathematical techniques
to the economy goes by the name 'economet
rics'. Purists at the econometric end of the
forecasting spectrum rely, ultimately, on the
inner workings of their computer models.
Purists at the judgmental end won't use any
thing more complicated than a telephone and
a desk calculator. Most economic forecasters
feel at home somewhere between these two
extremes.
Forecasting methods differ in howthey mix
judgment and modeling. They differ also in
how many kinds of information they take into
account. And different methods typically give
different results.
One method—the consensus or survey
method — usually emphasizes judgment
rather than modeling. The technique here is
to collect a range of different estimates from
economists and others and to average them
out. One of the more widely known consen
sus forecasts is the Business Outlook Survey of
the American Statistical Association and the
National Bureau of Economic Research. This
survey polls about fifty economists, most of
whom favor judgmental methods, to predict
the rate of inflation and other measures of
economic activity. About half of these econo
mists may consult an econometric forecast to
check their judgment, but only a few have
their own econometric models. The ASANBER survey arranges the contributing fore
casts numerically and picks as its representa
tive forecast the median or midpoint of the
range.2 Since a large part of its input consists
of noneconometric and primarily judgmental
predictions, the ASA-NBER survey is a repre
sentative judgmental forecast.
A second method focuses exclusively on
historical data about a single variable whose
behavior is being forecasted, leaving all oth
ers out of account. Inflation-rate forecasts
generated this way reflect past changes in

price levels and nothing else. They don't show
the influence that, say, wages and productiv
ity and aggregate demand might have on
future prices.
Single-variable forecasting methods are
popular with institutions that don't have the
resources for large-scale efforts and don't
require the detail of econometric forecasts.
One of the more widely used is the BoxJenkins method. The advantage of Boxjenkins forecasts is that they're easy to under
stand and easy to compute. Like trend
forecasts they presuppose that the future
values of a variable depend on its past values
and the past errors made in predicting them.
A typical forecast of this sort might postulate,
for example, that the level of prices in the
current quarter is related to the level of prices
in the last two quarters. The exact relationship
of current to past prices is estimated from
historical data.3
A third kind—the econometric model
forecast—generally provides for a number of
related equations that reflect the interaction
of several chains of events as revealed by the
data.4 The model is constructed and the data
are selected according to a theory about how
the economy fits together. The behavior of
prices in such a model might be represented
by an assertion that prices are set on the
supply side of the economy by a markup over
3
The Box-Jenkins model used in this article can be
found in J. P. Cooper and C. R. Nelson, “ The Ex Ante
Prediction Performance of the St. Louis and FRB-MITPENN Econometric Models and Some Results on
Composite Predictors,” Journal of Money, Credit, and
Banking 7 (1975), p. 11. The model was estimated using
data through 1966.
4
The pure econometric model forecasts considered
here aren’t really predictions. They are retrospective or
historical forecasts that try to determine what the model
would have predicted if it knew the actual changes in
policy instruments such as government expenditures and
the supply of money. Predictions differ from historical
forecasts in that they require the economist to estimate
future policy changes and thus to impose some judgment
on the outlook. Historical econometric forecasts, or sim
ulations, are pure model forecasts: the internal mecha
nisms of the model alone generate the forecast.

2
The median of the contributing forecasts is chosen,
rather than the mean, in order to minimize the influence
of occasional extreme forecasts.

FEDERAL RESERVE BANK OF PHILADELPHIA

adjust the model forecast judgmentally to
allow for information that isn't represented
explicitly, to compensate for past misses.7This
kind of forecasting requires economists to
help the model along with their best guesses
regarding future changes in the household
sector, the foreign sector, and other parts of
the economy. Users also must feed in their
best estimates of future changes in govern
ment expenditures and in the money stock as
well as other developments that the model
doesn't simulate. These are predictions based
on the judgment of the forecaster, but they
affect the model in ways that are consistent
with its built-in assumptions about how peo
ple behave in an economic environment.
The information used by the four methods
of predicting economic variables is summar
ized in Table 1.

costs.5 It might be assumed, for example, that
prices in the U .S . economy are set so as to
cover production costs and maintain profit
margins. A major component of these pro
duction costs is wages, and wages are deter
mined by the supply and demand for labor.
Most of the econometric models developed
in the late 1960s and early 1970s make an
assumption of this kind about the influence of
wages on prices.6
Most econometric forecasters, however,
don't rely on a pure model forecast; they
5
The model being used here is a modified version of
the MPS (MIT-PENN-Social Science Research Council)
model. The price and wage equations of this model are
described in B. de Menil and J. J. Enzler, "Prices and
Wages in the FRB-MIT-PENN Econometric Model,” in
The Econometrics of Price Determination', ed. Otto Eck
stein (Washington: Board of Governors of the Federal
Reserve System and Social Science Research Council,
1972). The price equation was estimated using data
through 1968.

7
An example of this type of forecasting is the MITPENN-SSRC model modified by the judgment of three
forecasters over different intervals at the Federal Reserve
Bank of Philadelphia.

6
W. D. Nordaus, "Recent Developments in Price
Dynamics,” The Econometrics of Price Determination.

TABLE 1
Type of
Information

SingleVariablet

Past Values of the
Variable Being Predicted
Past Values of Other
Variables

Actual Values of Policy
and External Variables

Judgmentally
Modified
Econometric
Models

Survey

Econometric
Model
Simulationt

Judgmental Information

Future Values of Policy
and External Variables

*ln survey or judgmental forecasts, it may be difficult to determine exactly how past values of variables and
policy variables influence the forecast.
tin single-variable forecasts, the relation of past to future values of the variable being predicted is estimated
using the historical data.
tin econometric models, the impacts of past values of variables and policy variables on the variables being
predicted are estimated using the historical data.

SEPTEMBER/OCTOBER 1976

BUSINESS REVIEW

more severe as the forecasts looked farther
ahead. The worst forecasting years were 1973
and 1974—years when international pressures
tended to upset normal economic expecta
tions.
Again, even a casual look at the graphs
makes it clear that the single-variable fore
casts were far and away the least accurate. The
other kinds of forecasts were bunched; it's
hard to tell which had the better track record
simply by looking. But economists have deve
loped several measures for ranking them
more precisely. Two of these measures are
mean error and mean square error; there are
others as well (see Appendix).
Mean error is average error: if a forecast has
a positive error of 2 in a given quarter and a
negative error of 2 the next quarter, its mean
error for the two-quarter period is zero.
Mean error is not a very useful measure,
however, because it doesn't indicate how far
off the mark a forecast is. If an inflation-rate
forecast, for example, were 10 percentage
points too high one year and 10 too low the
next, it still would average out to a zero mean
error, despite its gross inaccuracy. So econo
mists use mean square error to calculate how
far off the zero line errors are, no matter how
nicely they average out.
How They Stack Up. These measures show
the relative strength of econometric meth
ods. The pure simulation, the judgmentally
modified model forecast, and the survey fore
cast consistently had smaller mean errors and
mean square errors than the single-variable
forecast, with the judgmentally modified sim
ulation doing best for one, two, and three
quarters ahead (see Table 2, page 15).
In short: While all inflation-rate forecasts
have been too low in recent years, and while
these forecasts have been less accurate over
the longer haul, the outlook surveys and both
kinds of econometric forecasts have per
formed far better than the forecasts based on
a single variable.

HOW THE FORECASTS CAME OUT
It's easy to see how the forecasts came out
for the period 1971-75 by plotting graphs of
actual and predicted values. The graphs that
are reproduced in Charts 1-4 on pages 14-15
show how well inflation-rate forecasts gener
ated by the four different methods agreed
with actual changes in the inflation rate. The
vertical axis of each graph is the scale of fore
casted inflation-rate values; the horizontal
axis is the scale of actual values. If a fore
casted value of, say, 2 percent were matched
by an actual value of 2 percent, the dot for that
forecast would be right on the diagonal;
when the dot is not somewhere on the diago
nal, as it usually isn't, actual values failed to
coincide with projected ones. So, for exam
ple, in the first graph of Chart 1, the point
labelled 7411 shows that the actual rate of
inflation in the second quarter of 1974 was
around 9V2 percent against a predicted rate of
about 61 percent.8
/2
The charts are arranged by kind of forecast.
Each of them contains four graphs that show
how forecasts behave when they're used for
periods, one, two, three, and four quarters
beyond the base quarter. The earliest base
period for all forecasts is the third quarter of
1971. The number of quarters shown dimin
ishes from left to right across the charts as the
forecast horizon extends from one to four
quarters ahead.
Comparing the Forecasts. A glance at the
graphs reveals that most of the points fall
below the diagonal. This shows that all four
kinds of forecasts generally underestimated
inflation rates throughout the forecasting
period. And the underestimates became

8
The ASA-NBER and the MPS model-plus-judgment
forecasts were generated using the data available at the
time of the forecast. In the interim, however, the inflation
data have been revised a number of times. Therefore, in
order not to penalize these forecasts for the data revi
sions, the respective forecasting errors have been
adjusted by subtracting the difference between the
inflation data available at the time of the forecast and the
most current data.

WHY DO FORECASTS MISS?
Forecasts miss in differing degrees for dif
12

FEDERAL RESERVE BANK OF PHILADELPHIA

ferent reasons. Single-variable forecasts are
likely to miss because they use little informa
tion and don't provide for judgmental correc
tions. Unlike the other three kinds of fore
casts, single-variable forecasts don't consider
the way prices are set in the economy for
clues to future price changes. Because they're
based entirely on past conditions and trends,
they're unusually prone to missing sudden
changes. The one whose performance is
reflected in Chart 2, for example, assumes that
the inflation trend of any two successive
quarters will tell the forecaster what the infla
tion rates will be in the following quarter.9But
it doesn't always work out that way, even in
the short run.
The problem is compounded in forecasts
that look more than one quarter into the
future. Since single-variable forecasts depend
solely on past changes, forecasts of two or
more periods ahead require, as inputs, fore
casts of the periods immediately preceding
them. So, for example, in using the BoxJenkins method to forecast inflation rates
three quarters ahead, the economist has to
feed in the predicted level of prices for one
and two quarters ahead. As a result, the
forecast errors for one and two quarters
ahead are built into the forecast for three
quarters ahead. Error accumulation is a thorn
in the side of all economic forecasts of more
than one period ahead. But it's especially
troublesome in single-variable forecasts,
since they use past inflation rates alone to
calculate future rates.
Survey forecasts too set their sights on past
inflation trends in estimating future trends.
But the judgmental information that many
contributing economists bring to bear on
their forecasts reduces the weight of past
trends and thus probably weakens the bias
toward underestimating inflation rates.
Unfortunately, the value of judgmental infor
mation appears to fall off as the forecasting

horizon moves farther ahead.
Model simulations also look backward to
get a line on the future, explicitly represent
ing the economy's behavior over a given
period. Since models ordinarily allow for a
range of influences on inflation rates, their
forecasts usually reflect not only past changes
in inflation but also past changes elsewhere in
the economy.
Every retrospective forecast is subject to
error when it's outrun by events. A sudden
change in people's saving and spending hab
its, for example, can impact heavily on prices
and throw the forecast off. If government
unexpectedly slaps on wage and price con
trols, the results can baffle the forecaster. Or if
another country buys heavily in the commod
ity markets here, even the best forecast may
not provide much guidance.
Error builds up in econometric model fore
casts of two or more periods ahead because
past changes are used to predict future
changes. Since econometric models assume
that developments such as inflation are influ
enced not only by their own historical trends
but also by wage hikes and other forces, they
can accumulate error from many sources over
time. Econometric models may miss also
because they're approximations to the struc
ture of the economy at a given time. They
become outdated if behavioral and institu
tional changes that they haven't captured
occur in the economy.
When an economist modifies a model fore
cast in line with his own expectations of the
future, he in effect supplements the informa
tion it incorporates. This is no longer a retro
spective exercise but a predictive one.
Whether it makes for greater accuracy
depends on how good the forecaster's judg
ment is and how apt he is at anticipating
policy changes.
LEARNING FROM PAST MISTAKES
The method makes a difference in forecast
ing inflation. One thing economic forecasters
have learned from their recent experience is
that the past isn't always an accurate guide to

9
The current econometric literature is considering the
application of Box-Jenkins methods to a number of
variables simultaneously.

FEDERAL RESERVE BANK OF PHILADELPHIA

SEPTEMBER/OCTOBER 1976

BUSINESS REVIEW

1 QUARTER AHEAD

4 QUARTERS AHEAD

3 QUARTERS AHEAD

2 QUARTERS AHEAD

DIFFERENT
FORECASTING METHODS
GIVE
DIFFERENT FORECASTS

CHART 1
SURVEY FORECAST:
BUSINESS O UTLOOK SURVEY
(ASA-NBER)

TABLE 2
MEAN ERROR OF FORECASTS
Quarters Ahead
1

CHART 2
SINGLE-VARIABLE FORECAST:
BOX-JENKINS

ASA-NBER
Box-Jenkins
MPS Model
MPS Model (Modified)

741V

7211'721V 73,| • 7 4n 7.4m
L_

O
'

. * .
* • -73IV -741
72111 731 73111 ACTUAL

i_____ i__

10 12 14

-1.82
-3.20
-1.40
-1.13

-2.05
-4.92
-1.87
-1.79

-2.96
-5.63
-2.42
-2.14

-3.60
-6.56
-2.48
-2.88

10 12 14

Mean error is average error. A positive
error of any size in one quarter that's matched
by a negative error of the same size in the next
quarter gives a zero mean error for the twoquarter period.

MEAN SQUARE ERROR OF FORECASTS

Quarters Ahead
ASA-NBER
Box-Jenkins
MPS Model
MPS Model (Modified)

CHART 4
ECONOM ETRIC FORECAST
(MODIFIED): MPS

1 2
8.58 9.73
17.25 32.86
5.86 9.45
4.60 7.61

3
17.24
42.34
13.46
11.57

4
19.79
53.15
14.13
14.79

Mean square error is computed by squaring
each quarter's error and averaging out all the
squares. A high mean square error is a sign
that forecasting errors are relatively large.

BUSINESS REVIEW

SEPTEMBER/OCTOBER 1976

from now on.
The method makes a difference to policy
makers, too. Because government policy is
built into econometric models along with
other institutional features, econometric
forecasts allow policymakers to trace the
influence of their decisions—for example, the
influence of slower or faster monetary growth
on inflation and unemployment. Single
variable and survey forecasts lack this advan
tage.
The unusual inflation experience of recent
years provided economists with a tough test
of their forecasting abilities. What they've
learned is helping to reshape their forecasting
tools—and, they hope, sharpen their view of
the future.

future inflation rates. As a result, they've
begun to keep a closer watch on current
developments, such as commodity price
movements and changes in world market
conditions, for signals of higher prices ahead.
They've learned also that purism, whether
of the judgmental or of the mathematical sort,
imposes unnecessary restraints on the fore
caster's work. Eclecticism, in the form of
judgmentally modified econometric model
ing, appears to offer the greatest promise for
further development. It's relatively easy to
reformulate some econometric models so
that they capture the kind of information that
would have pointed to high inflation rates in
1974 and 1975. An economist who uses one of
the improved models can hope to chalk up a
better track record in inflation forecasting

APPENDIX
OTHER MEASURES OF FORECASTING ACCURACY
Mean error and mean square error are discussed in the text of this article. Mean
absolute error and the Theil statistic are two other measures of forecasting accuracy.
Mean absolute error is the average of the absolute values of the errors. The Theil statistic
was developed by Henri Theil of the University of Chicago and is computed using the
formula
m
Un =2 t-1
where the P are predicted values, the A are actual values, n is the forecasting horizon, and
m is the number of forecasts in computation.
Mean absolute error, like mean square error, measures the dispersion of forecasting
errors. The Theil statistic measures dispersion of the forecasting errors against the actual
changes in the variable being predicted.
Here's how these two measures rank our four kinds of forecast:

MEAN ABSOLUTE ERROR

ASA-NBER
Box-Jenkins
MPS Model
MPS Model (Modified)

Quarters Ahead
1 2
3
4
2.43 2.39 3.19 3.71
3.47 4.93 5.65 6.56
1.89 2.39 2.86 2.97
1.61 2.05 2.70 3.20

FEDERAL RESERVE BANK OF PHILADELPHIA
::

THEIL STATISTIC
1

ASA-NBER
m
Box-Jenkins
MPS Model
MPS Model (Modified)

1.09
1.55
0.90
0.80

Quarters Ahead
2
3
4
1.22 1.43 1.09
2.24 2.25 1.79
1.20 1.27 0.92
1.08 1.17 0.94

sws
These results confirm the ranking of methods by mean error and mean square error.
The Theil statistic seems to indicate, however, that errors associated with predicting the
inflation rate don't necessarily increase over the forecast horizon. In the above example,
the Theil statistics for predictions four quarters ahead are not much larger than those for
predictions one quarter ahead.
S

SEPTEMBER/OCTOBER 1976

BUSINESS REVIEW

FEDERAL RESERVE BANKS AND BOARD OF GOVERNORS
Federal Reserve Bank of Kansas City
Federal Reserve Station
Kansas City, Missouri 64198

Publications Services
Division of Administrative Services
Board of Governors of the
Federal Reserve System
Washington, D.C. 20551

Federal Reserve Bank of Minneapolis
Minneapolis, Minnesota 55480

Federal Reserve Bank of Atlanta
Federal Reserve Station
Atlanta, Georgia 30303

Federal Reserve Bank of New York
Federal Reserve P.O. Station
New York, New York 10045

Federal Reserve Bank of Boston
30 Pearl Street
Boston, Massachusetts 02106

Federal Reserve Bank of Philadelphia
100 North Sixth Street
Philadelphia, Pennsylvania 19106

Federal Reserve Bank of Chicago
Box 834
Chicago, Illinois 60690

Federal Reserve Bank of Richmond
P.O. Box 27622
Richmond, Virginia 23261

Federal Reserve Bank of Cleveland
P.O. Box 6387
Cleveland, Ohio 44101

Federal Reserve Bank of St. Louis
P.O. Box 442
St. Louis, Missouri 63166

Federal Reserve Bank of Dallas
Station K
Dallas, Texas 75222

Federal Reserve Bank of San Francisco
San Francisco, California 94120

FEDERAL RESERVE BANK OF PHILADELPHIA

banks and thrift institutions in the Fifth
District—
Rich May 76 p 14

The Fed in Print
Business Review Topics,
First Half 7976,
Selected by Doris Zimmermann

BANK COSTS
Towards a theory of international
banking—
San Fran Spr 76 p 5

Articles appearing in the Federal Reserve
Bulletin and in the reviews of the Federal
Reserve banks during the first half of 1976 are
included in this compilation. A cumulation of
these entries covering the years 1973 to date is
available upon request. If you wish to be put
on the mailing list for the cumulation, write to
the Publications D epartm ent, Federal
Reserve Bank of Philadelphia.
To receive copies of the Federal Reserve
Bulletin, mail two dollars for each to the
Federal Reserve Board at the Washington
address on page 18. You may send for reviews
of the Federal Reserve banks free of charge,
by writing directly to the issuing banks whose
addresses also appear on page 18.

BANK DEPOSITS
Holding companies and deposit
variability—
Chic March 76 p 12
Member bank deposits and aggregate
reserves revised—
FR Bull April 76 p 294
BANK HOLDING COMPANIES
THE IMPACT OF HOLDING COMPANY
AFFILIATION ON BANK PERFORMANCE
(working paper No. 1) available—
Atlanta Jan 76 p 12
An assessment of bank holding
companies—
FR Bull Jan 76 p 15

ADVISORY COMMITTEE ON MONETARY
STATISTICS
Improving the monetary aggregates (Bach
report)—
FR Bull May 76 p 422

Operation of a travel agency; automobile
leasing—
FR Bull Feb 76 p 148, 149
Bank holding company financial
developments in 1975—
FR Bull April 76 p 302

ALABAMA
A profile of Alabama banking activity—
Atlanta April 76 p 44

Growth of multibank holding companies
1956-73—
FR Bull April 76 p 300

AUTOMOBILE INDUSTRY
Automobile sales in perspective—
St Louis June 76 p 11

BANK LIQUIDITY
Statement to Congress, February 3, 1976
(Leavitt)—
FR Bull Feb 76 p 125

BALANCE OF PAYMENTS
Changing patterns in U.S. international
transactions—
FR Bull April 76 p 283

The safeguard of contingency planning for
banks—
Minn Feb 76 p 5

BANK COMPETITION
Multibank holding companies and local
market concentration—
Atlanta April 76 p 34

Remarks before the New York State
Bankers Association (Volcker)—
NY Feb 76 p 35

Regulations affecting competition between

SEPTEMBER/OCTOBER 1976

BUSINESS REVIEW

BANKERS’ ACCEPTANCES
Trading in bankers' acceptances: A view
from the acceptance desk of the Federal
Reserve Bank of New York—
NY Feb 76 p 51

BANK LOANS
Changes in bank lending practices, 1975—
FR Bull April 76 p 307
BANK LOANS—BUSINESS
Two decades of regional participation in
U.S. banking activity—
Atlanta March 76 p 18

Bankers' acceptances—
Chic May 76 p 3

District business loan inflows—
Atlanta March 76 p 26

BANKING—FOREIGN BRANCHES
Joint ventures policy February 12, 1976—
FR Bull Feb 76 p 185

Statement to Congress, February 16, 1976
(Debs)—
FR Bull March 76 p 227

New quarterly report E.11—
FR Bull May 76 p 460

Issues in the financing of corporate tender
offers—
NY March 76 p 3

BANKING—FOREIGN BRANCHES IN U.S.
Foreign banking in the United States:
Movement toward Federal regulation—
Rich Jan 76 p 3

Business loans and their significance—
Chic May 76 p 12

Proposals for Federal control of foreign
banks—
San Fran Spr 76 p 32

Is the level adequate for future loan
expansion?—
Dallas May 76 p 7

BANKING INTERNATIONAL
Petrodollars, LDCs, and international
banks—
NY Jan 76 p 10

Commercial bank loans and investments
revised—
FR Bull June 76 p 554
BANK PORTFOLIOS
Treasury securities expand rapidly—
Atlanta May 76 p 64

International banking—
San Fran Spr 76 p 3
U.S. west coast as an international financial
center—
San Fran Spr 76 p 9

BANK SIZE
Bank profitability and bank size—
Kansas City Jan 76 p 11

BANKING STRUCTURE
Banking structure in New York State—
NY April 76 p 107

BANK STATEMENTS
Changes in financial reports—
FR Bull Jan 76 p 67

Our changing financial system—
NY May 76 p 119

Supplemental financial report—
FR Bull March 76 p 279

BURNS, ARTHUR F.
Statement to Congress, January 21, 1976
(Federal Reserve System reform)—
FR Bull Feb 76 p 90

BANK SUPERVISION
Statement to Congress, February 4, 1976
(Leavitt)—
FR Bull Feb 76 p 130

Statement to Congress, January 28, 1976
(business forecast)—
FR Bull Feb 76 p 110

BANK TAX
Federal taxation of financial institutions—
Kansas City June 76 p 3

FEDERAL RESERVE BANK OF PHILADELPHIA

Statement to Congress, February 3, 1976
(monetary policy)—
FR Bull Feb 76 p 119

BUSINESS FORECASTS 1976 available—
Rich Jan 76 p 12
1975—Year of economic turn around—
St Louis Jan 76 p 2

Statement to Congress, February 19, 1976
(fiscal policy)—
FR Bull March 76 p 231

Review and outlook 1975-76—
Chic Feb 76 p 3

Statement to Congress, March 18, 1976
(Financial Reform Act of 1976)—
FR Bull April 76 p 323

Economic events in 1975—a chronology—
Chic Feb 76 p 16
The economy in 1975—
FR Bull Feb 76 p 71

Statement to Congress, March 22, 1976
(budget)—
FR Bull April 76 p 333

District conditions 1975-1976—
Minn Feb 76 p 1

Statement to Congress, April 9, 1976
(reserve requirements)—
FR Bull April 76 p 353

Review of 1975—
Dallas March 76 p 6

Statement to Congress, May 3, 1976
(monetary policy)—
FR Bull May 76 p 427

Financial developments in the fourth
quarter 1975—
FR Bull March 76 p 189

The independence of the Federal Reserve
System—
FR Bull June 76 p 493

Regional wrap-up '75: Downturn ends,
recovery begins—
Phila March 76 p 15
District conditions 1976—
Minn April 76 p 1

BUSINESS CYCLES
Recession to recovery: A comparative
view—
Atlanta Jan 76 p 6

Financial developments in the first quarter
of 1976—
FR Bull May 76 p 402

International: World economy turns
upward—
Chic Feb 76 p 15

BUSINESS INDICATORS
Predicting the rate of inflation in 1976—
Rich Jan 76 p 13

The U.S. economy in recovery—
Atlanta June 76 p 70

Evaluating the leading indicators—
NY June 76 p 165

Sustaining the business expansion
(Volcker)—
NY June 76 p 150

CAPACITY
New series for period since 1967—
FR Bull June 76 p 553
The link between money and prices 197176—
St Louis June 76 p 17

BUSINESS FORECASTS & REVIEWS
The Southeast's economic review and
outlook: A slow road to recovery—
Atlanta Jan 76 p 2

CAPITAL
Capital needs projections: A need for
perspective—
Phila May 76 p 3

Forecasts 1976—
Rich Jan 76 p 8

SEPTEMBER/OCTOBER 1976

BUSINESS REVIEW

16, 1976—
FR Bull Jan 76 p 65

Crowding out . . . —
Dallas June 76 p 1

DOLLAR
The $2 bill makes a comeback—
Phila March 76 p 12

CAPITAL MARKET
Development of capital markets in the
U.S.—
Dallas April 76 p 1

The $2 bill returns—
Rich March 76 p 20

CHECK COLLECTIONS
Federal Reserve operations in payment
mechanisms: A summary—
FR Bull June 76 p 481

ECONOMIC STABILIZATION
Stabilization p o licy: Tim e for a
reappraisal?—

Rich March 76 p 3

CITIES
Small cities and their future—
Phila March 76 p 3

EDGE ACT
New Edge offices participate in expanding
international banking market—
Dallas March 76 p 1

COLDWELL, PHILIP E.
Statement to Congress, January 29, 1976
(bank holding companies)—
FR Bull Feb 76 p 113

ELECTRIC POWER INDUSTRY
Industrial electric power use: New monthly
data—
FR Bull Jan 76 p 11

CONSUMER CREDIT
Revision of statistics—
FR Bull Jan 76 p 67

FARM OUTLOOK
Outlook for agriculture optimistic—
Rich Jan 76 p 19

Automobile credit releases consolidated
G. 26—
FR Bull Feb 76 p 186

Agriculture: A year of contrasts—
Chic Feb 76 p 11

CORPORATE PROFITS
Profit in a free economy—
Phila May 76 p 13

Outlook for agriculture—
St Louis Feb 76 p 11
FEDERAL RESERVE BANKS — DIRECTORS
Directory as of February 1976—
FR Bull Feb 76 p 169

CORRESPONDENT BANKS
Account analysis in correspondent
banking—
Kansas City March 76 p 11

Board of directors—
Atlanta March 76 p 24

CREDIT RATIONING
Statement to Congress, June 9, 1976
(Hawke)—
FR Bull June 76 p 507

FEDERAL RESERVE BANKS— EARNINGS
Earnings and expenses 1975—
FR Bull Jan 76 p 65

Regulation C adopted June 9, 1976—
FR Bull June 76 p 550

FEDERAL RESERVE BANKS—OPERATIONS
Annual operations and executive
changes—
Phila Jan 76 p 31

DEMAND DEPOSITS
Is the level adequate.. . ?—
Dallas May 76 p 7

Operations of the Federal Reserve Bank of
St. Louis, 1975—
St Louis Feb 76 p 2

DISCOUNT RATES
Change in discount rate approved January

FEDERAL RESERVE BANK OF PHILADELPHIA

FISCAL POLICY
Tax cuts and economic activity: The role of
“ financing''—
Phila Jan 76 p 13

ANNUAL REPORT available—
NY March 76 p 93
FEDERAL RESERVE BOARD
Membership of the Board of Governors of
the Federal Reserve System, 1913-76—
FR Bull Jan 76 p 31

Government: Income supports—
Chic Feb 76 p 21
FOOD PRICES
Food production and prices—perspective
and outlook—
St Louis Jan 76 p 15

Membership . . . 1913-76—
FR Bull Feb 76 p 88
ANNUAL REPORT available—
FR Bull June 76 p 553

FOOD SUPPLY
Food and population: A long view—
St Louis May 76 p 2

FEDERAL RESERVE—MONETARY POLICY
Monetary policy for the 1976 recovery—
Bost Jan 76 p 3

FOREIGN DEPARTMENT—BANK
International banking: Part II—
Chic March 76 p 3

Is the Federal Reserve hitting its money
supply targets?—
Kansas City Feb 76 p 3

Commercial bank lending to developing
countries—
San Fran Spr 76 p 20

Monetary policy for the coming quarters:
The conflicting views—
Bost March 76 p 2

FOREIGN EXCHANGE RATES
Foreign trade and exchange rate
movements in 1975—
St Louis Jan 76 p 9

Monetary policy in uncharted waters
(MacLaury)—
Minn April 76 p 11

FOREIGN INVESTMENT
The multinational corporation: A
controversial force—
Kansas City Jan 76 p 3

The strategy of monetary control—
FR Bull May 76 p 411
The strategy of monetary control—
NY May 76 p 124

FOREIGN TRADE—DOMESTIC EFFECTS
The impact of dollar devaluation on New
England trade—
Bost March 76 p 36

Preferred habitat vs. efficient market: A test
of alternative hypotheses—
St Louis May 76 p 11
FEDERAL RESERVE SYSTEM—PUBLICATIONS
Special publications of the Federal Reserve
Bank of Richmond—
Rich Jan 76 p 22

FUEL
NEW ENGLAND AND THE ENERGY CRISIS
available—
Bost May 76 p 38

W ORKING PAPERS available—
St Louis March 76 p 23

FUTURES
Hedging interest rate fluctuations—
Chic April 76 p 3
A mortgage futures market: Its
development, uses, benefits, and costs—
St Louis April 76 p 12

FINANCE COMPANIES
Survey of finance companies, 1975—
FR Bull March 76 p 197

SEPTEMBER/OCTOBER 1976

BUSINESS REVIEW

GARDNER, STEPHEN S.
Appointment to Board confirmed January
29, 1976; sworn in February 13—
FR Bull Feb 76 p 185

Resignation effective May 15, 1976—
FR Bull April 76 p 397
HOME MORTGAGE DISCLOSURE ACT 1975
Regulation C implements, June 9, 1976—
FR Bull June 76 p 550

Statement to Congress, May 11,1976 (state
bank tax)—
FR Bull May 76 p 433

HOUSING
Analysis of housing decline suggests
prospects of a good recovery—
Dallas Feb 76 p 1

Statement to Congress, May 24,1976 (bank
supervision)—
FR Bull June 76 p 504

Apartment building in the recovery—
Atlanta June 76 p 77

GOLD STANDARD
Bicentennial perspective—
Dallas Jan 76 p 1

INDUSTRIAL PRODUCTION INDEX
1976 revision—
FR Bull June 76 p 470

GOVERNMENT EXPENDITURES
State and local government spending—
Minn April 76 p 2

INFLATION
The worldwide inflation—
Bost May 76 p 3

Federal government spending on interest,
transfers, and grants—
Kansas City May 76 p 14

Inflation and the economic recovery—
St Louis June 76 p 2

GRAIN
Grain price increase accentuates beef and
pork cycles—
Dallas May 76 p 1

INSURANCE, UNEMPLOYMENT
Unemployment insurance Part I: Programs
and procedures—
Kansas City Feb 76 p 11

Soviet agriculture—
Chic June 76 p 3

Unemployment insurance Part II: Programs
and problems—
Kansas City June 76 p 16

GT. BRITAIN—FOREIGN EXCHANGE
Standby credits—
FR Bull June 76 p 552

INTEREST RATES
Changes in time and savings deposits at
commercial banks appear quarterly in the
Federal Reserve Bulletin

HOLLAND, ROBERT C.
Statement to Congress, December 17,1975
(bank supervision)—
FR Bull Jan 76 p 33

Interest rate stability as a monetary policy
goal—
Bost May 76 p 30

Statement to Congress, January 22, 1976
(financial institutions reform)—
FR Bull Feb 76 p 96

INTEREST RATES—DISCLOSURE
State Taxation of Depositories Act amends
Truth in Lending Act February 27, 1976—
FR Bull March 76 p 247

Statement to Congress, February 5, 1976
(bank supervision)—
FR Bull Feb 76 p 132

JACKSON, PHILLIP C.
Statement to Congress, January 22, 1976
(financial institutions reform)—
FR Bull Feb 76 p 100

Statement to Congress, March 26, 1976
(bank supervision)—
FR Bull April 76 p 339

FEDERAL RESERVE BANK OF PHILADELPHIA

MONETARY STABILIZATION
Priorities for the international monetary
system (Volcker)—
NY Jan 76 p 3

Statement to Congress, March 11,1976
(credit rationing)—
FR Bull March 76 p 237
Statement to Congress, March 17,1976
(Equal Credit Opportunity Act)—
FR Bull April 76 p 320

International monetary reform: The
Jamaican composite—
Bost March 76 p 57

LABOR MARKET
Recent labor market developments—
FR Bull Jan 76 p 1

MONEY SUPPLY
Revision of money stock measures—
FR Bull Feb 76 p 82

LAND UTILIZATION
Land use planning perspectives—
Kansas City March 76 p 3

Currency movements in the United
States—
Kansas City April 76 p 3

Tenth District resource use issues—
Kansas City April 76 p 9

Seasonal adjustment of M 1—currently
published and alternative methods—
FR Bull May 76 p 410

LATIN AMERICA
CARIBBEAN BASIN ECONOMIC SURVEY
available—
Atlanta Jan 76 p 12

Monetary aggregates compared—
Chic June 76 p 11
MORTGAGES
NEW MORTGAGE DESIGNS FOR STABLE
HOUSING IN AN INFLATIONARY
ENVIRONMENT available—
Bost Jan 76 p 30

LILLY, DAVID M.
Appointed to Board April 15, 1976;
confirmed May 28; sworn in June 1—
FR Bull June 76 p 550
LIQUIDITY
Recent changes in the liquidity of major
sections of the U.S. economy—
FR Bull June 76 p 463

Regulation C adopted June 9, 1976—
FR Bull June 76 p 550
MUNICIPAL FINANCE
A review of the municipal bond market—
Rich March 76 p 10

LIVESTOCK INDUSTRY
Recent changes in the cattle inventory—
Atlanta April 76 p 47

OPEN MARKET OPERATIONS
COMMITTEE MINUTES 1970 available for
inspection at National Archives—
FR Bull Jan 76 p 66

MERGERS
Extending merger analysis beyond the
single-market framework—
FR Bull May 76 p 409

The FOMC in 1975: Announcing monetary
targets—
St Louis March 76 p 8

MINNESOTA
MINNESOTA HORIZONS available—
Minn Feb 76 p 9

Records publication speeded—
FR Bull June 76 p 552

MITCHELL, GEORGE W.
Statement to Congress, January 28, 1976
(foreign branches regulation)—
FR Bull Feb 76 p 103

OVER-THE-COUNTER MARKET
OTC margin list changes—
FR Bull March 76 p 280

BUSINESS REVIEW

SEPTEMBER/OCTOBER 1976

PARTEE, J. CHARLES
Appointment to Board confirmed
December 19, 1975; sworn in January 5,
1976—
FR Bull Jan 76 p 65

Amendments May 13, 1976—
FR Bull May 76 p 459
REGULATION D
Amendment December 25, 1975—
FR Bull Jan 76 p 45

Statement to Congress, April 8, 1976 (full
employment)—
FR Bull April 76 p 347

REGULATION H
Amendment December 30, 1975—
FR Bull Jan 76 p 45

Statement to Congress, May 20, 1976 (full
employment)—
FR Bull June 76 p 499

Amendment February 26, 1976—
FR Bull March 76 p 247
REGULATION K
Interpretation on joint ventures of Edge
corporations—
FR Bull March 76 p 249

Statement to Congress, June 10, 1976
(monetary policy)—
FR Bull June 76 p 509
POPULATION
An economic approach to family size: A
new perspective on population growth—
Phila Jan 76 p 3

REGULATION M
Amendment February 6, 1976—
FR Bull March 76 p 248
REGULATION Q
Amendment December 4, 1975 (IRAs)—
FR Bull Jan 76 p 45

PRE-AUTHORIZED PAYMENTS
Delivery of "Federal Recurring Payments”
to financial institutions—
FR Bull Jan 76 p 47

Amendment March 1, 1976—
FR Bull March 76 p 248

PRESIDENT’S ECONOMIC REPORT
The 1976 Economic Report and the Federal
Budget.. . —
St Louis April 76 p 2

Comments deadlines extended—
FR Bull May 76 p 459

PRIVACY ACT OF 1974
Records system effective May 20, 1976—
FR Bull June 76 p 521

REGULATION T
Security credit extensions; revised OTC
stock list—
FR Bull June 76 p 554

RECESSIONS
The recession in perspective—
Atlanta Jan 76 p 9

REGULATION V
Amendment February 4, 1976—
FR Bull March 76 p 249
REGULATION Y
Interpretation of escrow arrangements—
FR Bull March 76 p 251

Recession and recovery in the Southeast: A
new perspective—
Atlanta May 76 p 54

Amendment April 8, 1976—
FR Bull April 76 p 398

REGULATION B
Amendment January 31, 1976—
FR Bull Jan 76 p 46

Amendment May 15, 1976—
FR Bull May 76 p 446

Interpretation on state laws March 23,
1976—
FR Bull April 76 p 364

Interpretation—
FR Bull June 76 p 537

FEDERAL RESERVE BANK OF PHILADELPHIA

REGULATION Z
Amendment October 1975 and
rescinding—
FR Bull Feb 76 p 147

TAX AND LOAN ACCOUNTS
New p o licy.. .prom pts.. . Federal
Reserve—
Dallas March 76 p 8

Amendments and interpretations—
FR Bull Feb 76 p 185

TIME DEPOSITS
Deposit service—new tool for cash
management—
Chic April 76 p 11

Interpretations on semi-annual
statements—
FR Bull March 76 p 251

Changes in time deposits—
Atlanta June 76 p 80

RESERVE REQUIREMENTS
Recent changes in reserve requirements:
An example of contradictory regulation—
St Louis March 76 p 2

TRANSFER OF FUNDS
1975 Annual Report of automated clearing
houses—
Chic Jan 76 p 2

Reserve requirements and monetary
control—
Kansas City May 76 p 3

Access to Federal Reserve clearing—
FR Bull Feb 76 p 147

SAVINGS
Net corporate saving in the 1970s—
Rich May 76 p 3

WALLICH, HENRY C.
Statement to Congress, February 6, 1976
(business forecast)—
FR Bull Feb 76 p 137

SOURCES AND USES OF FUNDS
Finance: Market pressures ease—
Chic Feb 76 p 24

Statement to Democratic Research
Organization, March 26, 1976 (capital
shortage)—
FR Bull April 76 p 342

STATE FINANCE
States as financial intermediaries—
Bost Jan 76 p 17

R
EB
gH E B N
V
A K

FEDERAL RESERVE BANK of PHILADELPHIA
PHILADELPHIA, I*E > A SYLVA X1 V 19106

business review
FEDERAL RESERVE BANK
OF PHILADELPHIA
PHILADELPHIA, PA. 19106

Full text of Business Review (Federal Reserve Bank of Philadelphia) : September/October 1976

FRASER