Full text of Business Review (Federal Reserve Bank of Philadelphia) : January/February 1983

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Federal Reserve Bank of Philadelphia
IS S N 0 0 0 7 -7 0 1 1




JANUARY-FEBRUARY I983

Using
Econometric
Models
to Make
Economic
Policy

’81 ’83 ’83 ’84 ’85

search
era!

DEREGULATION:
Jew Mture for Thrifts
lib r ar y
Bank

of St. Louis

JANUARY/FEBRUARY1983

USING ECONOMETRIC MODELS
TO MAKE ECONOMIC POLICY:
A CONTINUING CONTROVERSY

Richard W. Lang
. . . Economists are sharply divided over the
question of whether econometric models
can be used to analyze policy—even if the
correct type of model is employed.

DEREGULATION:
A NEW FUTURE FOR THRIFTS

Jan G. Loeys
Federal Reserve Bank of Philadelphia
100 North S ixth Street
Philadelphia, Pennsylvania 19106

The BU SIN ESS REVIEW is published by
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John Mulhern. Future issues will be edited by
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The Federal Reserve Bank of Philadelphia
is part of the Federal Reserve System—a




...T h e road to financial deregulation can be a
rocky one, but there may be no other choice if
thrift institutions are to survive the 80s.

System which includes twelve regional banks
located around the nation as well as the
Board of Governors in Washington. The
Federal Reserve System was established by
Congress in 1913 primarily to manage the
nation’s monetary affairs. Supporting func­
tions include clearing checks, providing coin
and currency to the banking system, acting
as banker for the Federal government, super­
vising commercial banks, and enforcing
consumer credit protection laws. In keeping
with the Federal Reserve Act, the System is
an agency of the Congress, independent
administratively of the Executive Branch,
and insulated from partisan political pres­
sures. The Federal Reserve is self supporting
and regularly makes payments to the United
States Treasury from its operating surpluses.

FEDERAL RESERVE BANK OF PHILADELPHIA

Using Econometric Models
To Make Economic Policy:
A Continuing Controversy
by Richard W. Lang*
target, the Fed would like to know how the
economy will respond to various monetary
policies. The Fed would like to have accurate
forecasts of economic activity conditional
on alternative rates of money growth in the
economy.
How can the Fed obtain forecasts that will
help it make policy decisions? It must use
some sort of forecasting model. But the
choice of a forecasting model (and associated
statistical techniques) depends upon how the
forecast will be used. In particular, not all
forecasting models are designed to evaluate
alternative economic policies.
Economists and policymakers, including
those within the Federal Reserve System,

Economic forecasting frequently has been
called an art, not a science. Yet this art often
is crucial to the formulation of public policy.
Policymakers—such as the officials of the
Federal Reserve System—rely on forecasts
of economic activity when they develop poli­
cies. For example, in January of each year,
the Federal Reserve decides on tentative tar­
get ranges of monetary growth for the com­
ing year. In order to choose the appropriate

‘ Richard W. Lang is Vice President and Associate
Director of Research at the Philadelphia Fed. He re­
ceived his Ph.D. from The Ohio State University, and
specializes in monetary policy and financial markets.




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BUSINESS REVIEW

JANUARY/FEBRUARY 1983

frequently use econometric models to fore­
cast the effects of choosing one policy or
another.1 But over the past few years,
serious questions have been raised about the
use—and usefulness—of econometric mod­
els in evaluating and choosing among alter­
native economic policies. The resulting debate
among economists has addressed the current
state of economic theory as well as the state
of econometric practice. Resolving these
issues will require substantial efforts on the
part of theoretical economists as well as
econometricians and statisticians. In the
meantime, the controversy about the use of
econometric models for policy evaluation
has generated some heated debates.
POLICY ANALYSIS HAS SPECIAL
REQUIREMENTS
The choice of a forecasting model depends
upon how the forecast is to be used. For
example, suppose your firm’s sales have
been highly correlated historically with
national output (Gross National Product, or
GNP). To plan production schedules for
1983, you want an accurate prediction of
1983 GNP. What model should you choose?
Whatever works! You can use any of a num­
ber of approaches: a large econometric mod­
el, a small model, a statistical procedure
based only on GNP’s past history, or a purely
judgmental approach. In fact, you could
“pool” several models’ predictions of GNP,
taking either a simple average or a weighted
average based on past predictive accuracy.
The point is that to obtain a GNP prediction
to be used to plan production schedules,

whatever works—whatever has minimized
the prediction error—can be used.
You do not have to be an economist or use a
forecasting model based on economic theory
to predict economic variables.2 Economic
predictions attempt to estimate future values
of economic variables, such as GNP, unem­
ployment, and inflation. These forecasts may
be based on a model grounded in economic
theory, but they need not be, and often they
are tied only loosely to theory. If we know A
and B are highly correlated, and we know A
earlier than B, we have a good chance of
inferring the future value of B. If one finds
that the unemployment rate always rises
one-tenth of one percent when Aunt Matilda
has a cold, Aunt Matilda’s health can be used
to forecast. To predict, one doesn’t neces­
sarily need to know what is cause and what is
effect; a high degree of correlation is all that
is required.
Economic theory, in contrast, attempts to
spell out cause-and-effect relationships in
economic behavior, starting from the pre­
mise that individuals desire to maximize their
own welfare and businesses attempt to maxi­
mize their profits. For example, economic
theory tries to explain how the demand for a
commodity changes as its price changes; or
what forces affect the level of interest rates
over time; or what factors change unem­
ployment.
If you use predictions of economic activity
in making your business decisions, you want
predictions that turn out to be close to the
actual values. If the predictions miss the
mark, your profits could be affected adver-

■^The term ‘econometric’ simply refers to measure­
ment and empirical estimation of economic relation­
ships using statistical techniques. An econometric
model is a set of equations representing, or describing,
economic relationships that can be statistically esti­
mated. For a further discussion of econometrics, see
Michael D. Intriligator, E con om etric M odels, T echn i­
ques, and A pplication s (Englewood Cliffs; PrenticeHall, Inc., 1978), especially Chapters 1 and 2.

2The term ‘economic variable’ refers to measures of
economic activity—such as GNP, consumption, the
unemployment rate—as well as to prices and interest
rates associated with economic activity. That these
measures are referred to as variables simply reflects that
they take on different values depending on the cir­
cumstances. For example, the unemployment rate was 9
percent in March 1982 but was 8.5 percent in January
1982.




4

FEDERAL RESERVE BANK OF PHILADELPHIA

sely. To provide an accurate prediction you
might use a model grounded in economic
theory. But this approach might be more
expensive than some other approach that
does at least as well. Or you might find that
there are some variables for which economic
theory provides little guidance in generating
a forecasting model. In any case, as long as
you care only about the accuracy of your pre­
dictions, not about how they are obtained,
economic theory need not play a major role in
your forecasting procedure.
In contrast, if you are trying to estimate the
effects on the economy of alternative econ­
omic policies, you need more information
than if you are only interested in predicted
values with small errors. You need to know
the links between policy actions and the
behavior of the economy. Policymakers are
clearly in this position, and economic theory
can provide guidance to them in building
models of these links. Although the theoreti­
cal relationships between policy instruments
and all other economic variables need not be
spelled out completely, policy evaluation
does require more information about the
structure of the economy than would be
necessary if one were making predictions
alone.
Because different types of forecasting
models require the collection of different
amounts of information, the choice of a
model depends on how the forecast is to be
used. Business forecasters may well prefer to
use one type of model, while an economic
policymaker would find that same model of
little use in evaluating alternative policies.
Different forecasting purposes generally are
accommodated by one of three types of
econometric models: autoregressive models,
reduced-form models, and large-scale struc­
tural models.3

WHAT DIFFERENT MODELS CAN DO
Econometric models consist of a set of
equations that are supposed to represent the
relationships between economic variables.
Econometric models of the national economy
come in various sizes, from just a single
equation to hundreds of equations. The three
different types of econometric models are
distinguished not only by size, but also by the
information they require and the kinds of
analysis for which they can be used.
Autoregressive Models. Estimating an
autoregressive model involves a statistical
procedure which relates the current value of
an economic variable to the past values of the
same variable—its own past history. A single
equation which relates current values of
GNP to past values of GNP, for example,
would be a simple autoregressive model of
overall economic activity. To generate a pre­
diction of next year’s GNP, the current and
past values of GNP are plugged into the
autoregressive model’s equation.
A lthough such predictions do not rely on
any information other than the variable’s
own past history, these models at times have
been more accurate than other types of mod­
els. But lack of reliance on any other infor­
mation is exactly why autoregressive models
are not helpful to policymakers in evaluating
alternative economic policies. The Fed, for
example, may ask the question, “How fast
will GNP grow next year if money grows at X
percent instead of Y percent?” Since money
growth does not enter into the autoregressive
GNP model’s forecasting procedure, the
model cannot answer this question. A model
that can answer the Fed’s question must
include a variable representing money growth
in addition to just GNP’s past history. One
way to capture this additional information is
to use a reduced-form model.
Reduced-Form Models. Reduced-form
models seek to explain the relationship be­
tween policy variables and economic vari­
ables such as GNP. A reduced-form model
does not attempt to capture each of the steps

3For a more detailed description of these models than
what follows, see Intriligator, especially Chapters 2
and 15.




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BUSINESS REVIEW

JANUARY/FEBRUARY 1983

in the process by which a change in economic
policy affects the economy. Instead, a re­
duced-form model seeks to explain the over­
all net effect. Such a model need contain only
a few equations, so it is relatively cheap to
build.
Although reduced-form models of GNP do
not explicitly take account of the interre­
lationships of GNP with all other economic
variables, they do capture a quantitative
relationship between GNP and policy vari­
ables. Thus, these models are used to answer
such questions as, “How fast will GNP grow
if money grows at X percent instead of Y per­
cent?” Reduced-form models often are used
to evaluate the effect of fiscal or monetary
policy on economic activity. Monetary
policy usually is repesented by the rate of
growth of some measure of the money stock.
Fiscal policy is measured by aggregate fed­
eral spending, aggregate taxes, or the budget
deficit. The historical relationship of these
policy variables to GNP can be statistically
estimated in this reduced-form context, and
then this estimated relationship is used to
forecast next year’s GNP, assuming a par­
ticular setting for the policy variables. By
plugging different values of policy measures
into the model’s equations, policymakers
might make judgments about the relative
attractiveness of different policies. The ef­
fect on GNP of alternative choices of next
year’s policy variables might be evaluated in
this context.
These small reduced-form models are us­
ually used to evaluate the effects of broad
economic policies—such as total govern­
ment spending, total tax revenues, or growth
of the money supply—on aggregate economic
activity such as GNP, inflation, or unem­
ployment. They are not typically used for
evaluating the effects of the narrow instru­
ments of monetary and fiscal policy. For
example, the effects of changes in tax rates
or in depreciation rules, or the impact of
changes in reserve requirements or in the dis­
count rate, cannot be readily examined in




reduced-form models. To study these effects, a
model that includes more detail about the
economy is required. The model must attempt
to lay out the relationships among an expan­
ded number of economic variables, and there­
fore it must be larger in scope. Larger models
(or parts or sectors of them] frequently are
employed to study the impact of changes in
policy instruments because they provide
details about economic relations that small
models lack.
Large-Scale Structural Models. Largescale structural models are used for all types
of policy evaluations. The term ‘structural’
means that the model attempts to capture the
structure of the economy—the interrelation­
ship of all relevant economic variables.
These models are built by analyzing the
individual sectors of the economy.
For example, a large-scale structural
model could have equations explaining the
supply and demand for various products
such as autos, steel, and consumer install­
ment credit. But steel is a significant input in
the production of autos, and consumers
often purchase autos on installment credit,
so the large model’s equations would tie
these sectors together. Large-scale structural
models can be large indeed; they typically are
composed of several hundred equations.
Variables representing monetary and fis­
cal policies also are included in structural
models. Indeed, these large models typically
attempt to specify in detailed fashion the
channels through which policy actions affect
the economy. By assuming particular values
for the settings of policy variables, they
might be used to forecast next year’s GNP
under alternative economic policies—for
example, how next year’s GNP will change if
money grows at different rates. In addition,
these large models are used to answer ques­
tions about how particular industries—housing,
autos, agriculture—will behave as economic
policies change.
The equations that comprise large-scale
structural models are, in principle, based on
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FEDERAL RESERVE BANK OF PHILADELPHIA

these models because the “other factors” that
are included in the models’ equations vary
from one model to another. Some economists
have argued that too often a researcher
chooses a particular specification of the
equations in a model because it tends to sup­
port his preconceived idea of what the re­
lationship should be.5
This multiplicity of specifications arises,
in part, because the field of economics is not
amenable to experimental examination in­
volving replications of the same events.
Unlike experiments in physics or chemistry
which can allow one thing to change while
all others are kept the same, empirical
studies of economic theories are done by
examining a system—the economy—in
which almost everything is changing at the
same time. Statistical techniques that esti­
mate economic relations can take account of
changes in the variables that alter the eco­
nomic environment, but only if data on these
variables are included in the econometric
model. Yet data and tim e lim itations prevent
the inclusion of all variables that could be
remotely related to the variables of interest to
policymakers.6*

economic theory. Because of their founda­
tion in economic theory and their attempt to
capture the detailed structure of the economy,
these models have a wider range of uses than
either autoregressive or reduced-form mod­
els. Large models are used to predict and to
evaluate alternative economic policies as
well as to evaluate economic theories. But
these models have been subject to serious
criticisms in regard to their usefulness in
evaluating alternative economic policies,
and even in regard to their ability to provide
reliable estimates of the structure of the
economy.
CAN MODELS CAPTURE
ECONOMIC REALITY?
Building an econometric model that cap­
tures the structure of the economy is a tall
order. Despite their size, large-scale struc­
tural models are still very simple compared
to the complexity of a nation’s economy. Do
these models reflect reality—or at least are
they close enough approximations that they
do not substantially misrepresent reality?
Economists have hotly debated this subject
in recent years.
Specifying the Model. One problem in
formulating a model to represent reality
involves whether the model’s equations ade­
quately specify the relationships among the
economic variables being examined.4 Eco­
nomic theories do not necessarily make clear
which variables can be safely omitted when
building models of economic relationships.
For this reason, different model-builders
include different sets of economic variables
in their models’ equations in order to improve
their models’ predictive ability. Consequent­
ly, there are a number of different structural
models of the U.S. economy. Estimates of
the relation between two variables—such as
between GNP and money—differ across

5For example, in a recent American Economic Re­
view, Cooley and Leroy investigate alternative specifi­
cations for a money demand function—which is a
cornerstone of monetary theory and policy— and find
widely varying results. Specification problems are cru­
cial since policymakers use estimated equations to
decide among alternative policies. See Thomas F.
Cooley and Stephen F. Leroy, “Identification and
Estimation of Money Demand,” American Economic
Review 71 (December 1981), pp. 825-844.
®Another problem in specifying an econometric
model is that, in general, economic theory does not pro­
vide sufficient information to write down the precise
form of the relationship between two variables—whether
their relation is linear or nonlinear. In a linear relation,
the separate effects of several variables can be added
together to obtain the total effect on the variable being
explained in the model. In a nonlinear relation, how­
ever, the effects of several variables cannot be simply
added together since their effects on the variable being
explained are multiplicative.

4 For a general discussion of specification problems in
economic models, see Intriligator, Chapter 2.




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JANUARY/FEBRUARY 1983

BUSINESS REVIEW

Choosing a “best” specification of a model
of the economy has proved difficult because
no one model has proved consistently
superior to others in its forecasting ability or
in its ability to agree with economic theory.
But if important variables are inadvertently
omitted from one of these models, the model
is misspecified. And a misspecified model is
likely to give erroneous estimates of the
effects of different policy options on eco­
nomic activity.
Identification Problems. Another pro­
blem that affects large structural models of
the economy is the difficulty of identifying
the source of a change in an economic vari­
able. For example, consider a situation in
which a researcher observes that the price of
oil is changing. Oil prices can change be­
cause either the supply of oil is changing or
the demand for oil is changing, or because
both are changing. In general, the researcher
would like to identify which factors are
changing the price of oil. To do so, the
analyst must specify those factors that affect
demand for oil but not supply, as well as
those factors that affect supply but not
demand. By doing so he ensures that his
model is identified—that he can determine
why the price of oil is changing.7
In a large-scale structural model of the
economy, this process of identifying the
model’s equations for each market or sector
is a large undertaking. That is, the sector
explaining the price and quantity of oil must
be identified, the sector explaining the price
and quantity of labor must be identified, and
so on—and then these separately identified
sectors are tied together into the large model.
Is the large model as a whole then identified?
Many argue it is not. The reason is that this
market-by-market identification process
often ignores common factors among markets
and sectors which become apparent once

these markets and sectors are aggregated into
a large model.8
If a model’s equations are not approp­
riately identified, a change in one variable
(such as GNP) could be incorrectly attributed
to a change in another variable. The true
relationship between the variables could be
obscured. Estimates of the model’s behavior
would not adequately represent the way the
economy actually behaves.
Policymakers hope that a model’s iden­
tification problems do not significantly
obscure the effect of policy variables on
economic activity. Some economists believe
that this hope is well-founded.9 But the
general problem of identification in economic
models is likely to continue to call into ques­
tion the reliability of large-scale models.10
While specification and identification pro­
blems call into question the reliability of
large-scale structural models in representing
reality, there is another criticism of the use of
all econometric models—structural, reducedform, and autoregressive—in the evaluation

7See Intriligator, Chapter 2, for a general discussion
of the identification problem.

10Malinvaud discusses the question of reliability in
more detail; see Econometrica 49 (November 1981].




8Sims, in a recent article in Econometrica, calls the
current identification procedure of large models “in­
credible identification.” He argues that “the style in
which large-scale macroeconomic model-builders con­
struct claims for a connection between these models and
reality—the style in which identification is achieved for
these models—is inappropriate, to the point at which
claims for identification in these models cannot be taken
seriously.” Malinvaud, in a 1981 Econometrica article,
agrees with Sims on this point, although he disagrees
with Sims on many others. See Christopher Sims, "M ac­
roeconomics and Reality,”Econometrica 48 (January
1980], pp. 1-48, andE. Malinvaud, “Econometrics Faced
with the Needs of Macroeconomic Policy,” Economet­
rica 49 (November 1981], pp. 1363-1375.
9Sims argues that large-scale models still are useful
for forecasting and policy analysis. He says, “For
forecasting and policy analysis, structural identification
is not ordinarily needed, and false restrictions may not
hurt, may even help a model to function in these
capacities.” See Sims, Econometrica 48 (January 1980],
p. 11.

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FEDERAL RESERVE BANK OF PHILADELPHIA

volve simply varying the value of a policy
instrument (without changing the way in
which policy is executed).13 For example,
consider a situation in which there has been
an excise tax on liquor for many years and
the government has changed the tax a num­
ber of times. Using this historical experien­
ce, researchers can estimate the effect of a
change in the excise tax on the amount of
liquor sold. Such estimates then can be used
to address the question of what effect a new
change in the excise tax of 10 percent will
have on liquor sales, compared to a change in
the tax of 5 percent.
The situation is much different, however,
when the excise tax is first introduced. Since
there is no historical experience to measure
the past impact on liquor sales of changes in
such a tax, the researcher must obtain more
specific information on both the supply and
demand for liquor before being able to
evaluate the impact of the new tax. In this
case the Lucas critique certainly applies.
Similar situations could exist for more
general fiscal and monetary policies. That is,
if the Federal Reserve has been setting mon­
etary growth targets for many years and has
changed them over time, researchers can
estimate past effects of changes in money
growth on economic activity. This suggests
that the Fed can get a reasonable answer to
the question of “what happens to the eco­
nomy if money increases at X percent in 1983
rather than Y percent.” But this is the case
only if the model used to make these com­
parisons was estimated over a period when
there were no changes in the way monetary
policy was conducted. If the Fed switches
the way it tries to control the economy, then
the Lucas critique becomes a more serious
problem.

of alternative economic policies. This criti­
cism -called the Lucas critique—has become
the subject of much debate among econo­
mists and policymakers.
THE LUCAS CRITIQUE: DO POLICY
CHANGES INVALIDATE MODELS?
In 1976, Robert Lucas wrote an article in
which he argued that “any change in policy
will systematically alter the structure of
econometric models.” 11 His argument basi­
cally goes as follows.
The structure of an econometric model
embodies and reflects the behavior of eco­
nomic agents (consumers and producers).
The decisions of consumers and producers,
however, depend on their perceptions of the
rules being followed by economic policy­
makers. If policymakers change their poli­
cies (the economic rules of the game),
producers and consumers might change their
actions and decisions as well, and hence
change the structure of the economy.
Lucas viewed this conclusion as a fun­
damental criticism of the use of econometric
models for policy evaluation. In his view,
“comparisons of the effects of alternative
policy rules using current macroeconometric
models are invalid regardless of the perfor­
mance of these models over the sample
period or in ex ante short-term forecas­
ting.”12 Since policymakers want to evaluate
the effects of different policy actions, the
Lucas critique is important.
How severe is Lucas’s criticism? Its seve­
rity is still an open issue (see Appendix).
Some argue that the Lucas critique is not cru­
cial if the policy alternatives in question in­

■^Robert Lucas, “Econometric Policy Evaluation: A
Critique,” T he Phillips Curve and Labor Markets, sup­
plement to the Journ al o f Monetary Economics, ed. by
Karl Brunner and Allan Meltzer (1976), p. 41.

13For example, see Sims, Econom etrica48 (January
1980); or Christopher A. Sims, “Policy Analysis with
Econometric Models,” Brookings Papers on Economic
A ctivity(1: 1982), pp. 107-152.

12On the other hand, Lucas viewed this critique as “of
only occasional significance” for the issues involved in
using just the short-term predictions of econometric
models. Lucas, p. 41.




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JANUARY/FEBRUARY1983

BUSINESS REVIEW

policies probably seems arcane to most peo­
ple. But since econometric models and fore­
casts based on those models are used by
policymakers in making their decisions, the
general public is affected by the outcome of
these debates. Robert Solow cryptically
pointed out the relevance of such debates to
the public in terms of monetary policy at a
1978 conference:
I would like to assure the practical
people in this room and also the
ones out in the streets of
Edgartown [where the conference
was held] that although the battles
that are fought in conferences like
this appear to be fought with anti­
que pop guns, the bullets are real
and they may soon be fired at you
by the Federal Reserve.16

In a recent article, Christopher Sims
argues that the types of policy changes that
are subject to the Lucas critique rarely
occur.14 According to Sims, policymakers
do not often make radical changes in mon­
etary or fiscal policy. Instead, changes in
economic policies are made slowly over time,
so that any resulting change in the structure
of the economy would occur slowly over
time as well. Sims concludes from this line of
reasoning that econometric models can be
used to evaluate alternative policies, although
he has suggestions about the type of model to
be used. In particular, he argues in favor of
an expanded version of the reduced-form
approach that involves elements of autore­
gressive models as w ell.15
The debate about the significance of the
Lucas critique is of particular concern to the
Federal Reserve. Prior to October 1979 the
Fed attempted to influence money growth
mainly by changing short-term interest rates.
Since then the Fed has focused principally on
manipulating the growth of reserves to con­
trol money growth. Whether this change in
the conduct of policy is subject to the Lucas
critique and, if so, how sensitive the struc­
ture of the economy is to such a change in
policy, are questions still being worked on by
many researchers today.

14See Sims, Brookings Papers on E con om ic A ctivity
(1: 1982).

The possibility that an econometric model
misrepresents reality—because of specifica­
tion or identification problems, or because of
the Lucas critique—does pose risks to eco­
nomic policymaking. Resolving some of these
issues will require a lot of work. Economic
theory must be pushed to provide better
specification and identification of the rela­
tionships among variables. Econometricians
and statisticians will have to put more
emphasis on testing specifications in eco­
nometric models and on testing the sen­
sitivity of the models’ structures to policy
changes. When these problems are better
resolved by the economics profession, eco­
nomic forecasting and the formulation of
economic policies will be able to be more a
science, and less an art.

15Sims’s approach is called vector autoregression.
For more about this type of model, see Thomas J.
Sargent, “Estimating Vector Autoregressions Using
Methods Not Based on Explicit Economic Theories,”
Q uarterly Review , Federal Reserve Bank of Min­
neapolis (Summer 1979), pp. 8-15.

16Robert M. Solow, “Summary and Evaluation,”
After the Phillips Curve: P ersisten ce o f H igh Inflation
and High U nem ploym ent, Federal Reserve Bank of Bos­
ton, Conference Series No. 19 (June 1978), p. 203.

SUMMARY
The debate about the validity of using
econometric models to analyze economic




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FEDERAL RESERVE BANK OF PHILADELPHIA

APPENDIX. . .
ECONOMISTS SHARPLY DIVIDED
OVER ECONOMETRIC MODELS
In the 1970s, the issues of identification, specification, and the Lucas critique were raised in
attacking the usefulness of standard econometric models. Robert Lucas and Thomas Sargent
expressed strong views on this subject at a June 1978 conference:
First, and most important, existing Keynesian macroeconometric models are
incapable of providing reliable guidance in formulating monetary, fiscal and other types
of policy. This conclusion is based in part on the spectacular recent failures of these
models and in part on their lack of a sound theoretical or econometric basis. Second, on
the latter ground, there is no hope that minor or even major modification of these models
will lead to significant improvement in their reliability.*
These criticisms were not left unanswered, however, by the proponents and users of the standard
macromodels. Not everyone agrees with the Lucas-Sargent views that these models do not and can­
not capture reality. At the same conference, Franco Modigliani commented that the problem was not
that econometric models fail to capture the real world, but that the real world is difficult for
policymakers to control:
To a large extent the sweeping indictment of the Lucas and Sargent paper con­
fuses two kinds of crises. One is the crisis of whether these models have captured the
world itself. The second crisis, which I believe is the real problem, is that the world we
capture is extremely hard to tame, to cure from inflationary shocks, the new disease of
‘73-‘74 and thereafter. So the crisis is right there in the structure of the world, not in our
ability to capture that structure.!

*RobertE. Lucas and Thomas J. Sargent, “A fter Keynesian M acroeconom ics,” A fte r th e P hillipsC urve: Persis­
ten ce o f High Inflation and High U nem ploym ent, Federal Reserve Bank of Boston Conference Series No. 19 (June
1978), p. 69.
tFranco Modigliani, “Discussion,” A fter the Phillips Curve: P ersisten ce o f H igh Inflation and H igh U nem ploy­
ment, Federal Reserve Bank of Boston, Conference Series No. 19 (June 1978), p. 195. This position is also suppor­
ted by Richard G. Lipsey, “The Understanding and Control of Inflation: Is There a Crisis in M acroeconomics?”
Canadian Journ al o f Economics(November 1981), pp. 544-576.




11

JANUARY/FEBRUARY1983

BUSINESS REVIEW

Both Benjamin Friedman and Robert Solow commented that Lucas and Sargent had overstated the
problems that standard econometric models have had in representing and forecasting economic
activity. Friedman criticized Lucas and Sargent’s claim that Keynesian models have fundamental
methodological problems that are not shared by alternative models proposed by them.f And both
Friedman and Solow complained about the strong terms in which Lucas and Sargent condemned the
standard models:
[Lucas and Sargent] describe what happened in the 1970s in a very strong way
with a polemical vocabulary reminiscent of Spiro Agnew. . . .1 share Franco Mod­
igliani’s view that the alarmism, the very strong language that I read to you, simply
doesn’t square with what in fact actually happened. If you give grades to all the standard
models, some will get a B and some a B minus on occasion, especially for wage equa­
tions, but I don’t see anything in that record that suggests suicide. §
For policymakers’ use of econometric models to evaluate alternative economic policies, the Lucas
critique—that changes in policy will alter the structure of the economy—is most important. Lucas
had made this point at an earlier conference:
Given that the structure of an econometric model consists of optimal decision
rules of economic agents, and that optimal decision rules vary systematically with
changes in the structure of series relevant to the decision maker, it follows that any
change in policy will systematically alter the structure of econometric models.
For the question of the short-term forecasting or tracking ability of econometric
models, we have seen that this conclusion is of only occasional significance. For issues
involving policy evaluation, in contrast, it is fundamental; for it implies that com­
parisons of the effects of alternative policy rules using current macroeconometric mod­
els are invalid regardless of the performance of these models over the sample period or in
ex ante short-term forecasting. ||
Not all economists agree on the severity of the Lucas critique. Lucas’s conference paper was
criticized by Robert Gordon, who was less pessimistic about the usefulness of econometric models in
evaluating alternative policies:
While Lucas’ critique effectively demonstrates an important weakness of
econometric simulations, his paper overstates the impossibility of remedy: and hence its
implications are likely to be misunderstood by policymakers. . . .
My conclusion from Lucas’ analysis is much less pessimistic. While I am pre-

fBenjam inM . Friedman, “Discussion,” A fter the Phillips Curve: P ersisten ce o f H igh Inflation and H igh Unem­
ploym ent, Federal Reserve Bank of Boston, Conference Series No. 19 (June 1978], pp. 73-80.
§Robert M. Solow, “Summary and Evaluation,” A fter the P hillips Curve: P ersisten ce o f High Inflation and
High Unemployment, Federal Reserve Bank of Boston, Conference Series No. 19 [June 1978], pp. 203-204.
||Robert E. Lucas, Jr., “Econometric Policy Evaluation: A Critique,” T he Phillips Curve and Labor Markets,
Carnegie-Rochester Conferences on Public Policy, supplement to the Journ al o f Monetary E con om ics, ed. by
Karl Brunner and Allan H. Meltzer (1976), p. 41.




12

FEDERAL RESERVE BANK OF PHILADELPHIA

pared to grant the validity of the proposition that the mechanical extrapolation of a
model with fixed parameters cannot provide useful information on the effects of all
policy changes, on the other hand the effects of some policy changes can be determined
if parameter shifts are allowed and are either (a) estimated from the response of
parameters to policy changes within the sample period or (b) are deduced from a priori
theoretical considerations. #
After examining several different cases of different types of policy changes, Gordon concluded that
Lucas’s argument was overstated and that some types of policy changes could be evaluated in
econometric models.***
The extent to which the Lucas critique applies is still being debated, but it seems clear that
econometric models should be used with special care when analyzing large changes in economic
policies. William Poole described the range of policy changes that could be considered in evaluating
the relevance of the Lucas critique:
First of all, there is no model builder in this room who would expect his model to
hold up if we were to consider an experiment, let’s say, of 100 percent rate of money
growth in the next 12 months. No model builder expects his model to stand up in that
kind of an experiment. Clearly the institutional structure in the model, the lag structure,
and so forth, simply would fall apart. Now, what about 50 percent money growth? Or 25
percent money growth? As we go down to ranges that are closer to those that we are
familiar with, and we have more confidence that we are within the ballpark of the his­
torical range of observation, then we are more confident that the models can tell us some­
thing. But that is not the end of the story.. .we can mention a long list of apparently minor
changes. . .They don’t involve major changes in the institutional structure, and it’s hard
to see how they make much difference.
But that is not the point, it seems to me. The point is. . .whether the changes in
institutional structure in response to policy changes are large compared to the changes in
forecasts of economic variables in response to policy adjustments within a fixed
institutional structure. After all, none of us expects very big effects from policy
experiments that involve a change in the annual rate of growth of money of 1 percent for
six months. If we talk about 2 percentage points for six months, or 3 or 4, as we raise the
policy dose, we expect larger policy effects. But, of course, we also expect larger
changes in institutional structure.tt
In Poole’s view, most economists agree in principle with the Lucas critique about policy evaluation.
But the practical implications of this criticism are still under study. As Poole points out, the Lucas
critique has given model builders further impetus to refine and improve econometric models.

♦ Robert J. Gordon, “Can Econometric Policy Evaluations Be Salvaged?—A Comment,” The P hillips Curve
and L a b o r M arkets, Carnegie-Rochester Conferences on Public Policy, supplement to the Journ al o f M onetary
Economics, ed. by Karl Brunner and Allan H. Meltzer (1976), p. 47.
**Gordon, p. 57.
ttW illiam Poole, “Summary and Evaluation,” A fter the Phillips Curve: P ersisten ce o f H igh Inflation and High
U nem ploym ent, Federal Reserve Bank of Boston, Conference Series No. 19 (June 1978), pp. 212-213.




13

Philadelphia/ RESEARCH

The Philadelphia Fed’s Research Department occasionally publishes working
papers based on the current research of staff economists. These papers, dealing
with virtually all areas within economics and finance, are intended for the
professional researcher and are relatively technical. In 1982, twelve papers
were added to the Working Papers Series.
A list of available papers may be ordered from WORKING PAPERS, De­
partment of Research, Federal Reserve Bank of Philadelphia, 100 North Sixth
Street, Philadelphia, Pennsylvania 19106. Copies of papers may be ordered
from the same address.




FEDERAL RESERVE BANK OF PHILADELPHIA

Deregulation:
A New Future
For Thrifts
by Jan G. Loeyd*
The nation’s thrift institutions are among
the businesses most severely hit by the recent
combination of recession and record-high
interest rates. During the last two years, the
savings industry has suffered larger losses
than the beleaguered auto and airline indus­
tries combined. Faced with the possibility of
more losses this year, hundreds of thrift
institutions may not survive.
A complex network of regulatory con­
straints and a sharp increase in both the level
and variability of interest rates are the root

causes of the industry’s problems. The con­
straints, which were designed to promote
low-cost mortgage financing, have made
savings institutions vulnerable to interest
rate fluctuations and to changing conditions
in local housing markets. Removing restric­
tions that limit the ability of thrifts to adapt to
changing economic circumstances is an
essential element in any program to restore
the viability of the thrift industry. Although
thrifts face a difficult adjustment period,
reversing or even delaying current deregula­
tion efforts can only make thrifts worse off.

*Jan G. Loeys is an economist in the Banking and Fi­
nancial Markets section of the Philadelphia Fed’s De­
partment of Research. He received his Ph.D. in eco­
nomics from UCLA. Excellent research assistance for
this project was provided by Sabrina Lee.

EARNINGS CRISIS
IN THE THRIFT INDUSTRY
Like other financial institutions, thrifts
borrow money in the hope of lending it out at




15

BUSINESS REVIEW

JANUARY/FEBRUARY 1983

a higher interest rate.1 Until a few years ago,
the spread between the return on assets and
the cost of funds amounted to a comfortable 1
percent to 1.5 percent (Figure 1). Unlike com­
mercial banks, however, thrifts hold most of
their assets in the form of long-term, fixedrate mortgages. When interest rates rose
unexpectedly in 1979, their mortgage income
failed to keep up with their cost of funds. By
late 1980, the spread (return on assets minus
cost of funds) had turned negative, and thrift
institutions were incurring heavy losses.
Commercial banks were able to maintain
their profitability by raising the interest rates

on their loans as their cost of funds rose
(Figure 2). Thrifts had to spend their accu­
mulated reserves to cover their losses, and
their net worth position dropped from $44.7
billion in December 1980 to $33.6 billion in
August 1982. These aggregate data, while
disquieting enough as they stand, hide the
still more ominous fact that many individual
institutions have used up almost completely
their net w orth and face liquidation or merger
into stronger firms. Since the beginning of
1981, more than 700 thrift institutions, out of
a total of 5,016, were merged or acquired by
other institutions. Also, these net worth data
are based on book values, and may overstate
the financial strength of an institution (see
NET WORTH AND THE BANKRUPTCY
DECISION).
The problems of the thrifts are not apt to
disappear overnight. Increasing competition
from commercial banks and nonbank finan­
cial institutions will erode further their usual
source of low-cost funds—passbook accounts.
More and more depositors are demanding

■*The term ‘thrifts’ usually includes credit unions as
well as savings and loan associations and mutual
savings banks. Credit unions are excluded here because
they do not have nearly as high a proportion of mortgage
loans and thus their earnings are not impaired to the
same degree as those of other thrifts.

FIGURE 1

AVERAGE RETURN DROPS
BELOW AVERAGE COST
OF FUNDS AT SAVINGS
AND LOAN ASSOCIATIONS

FIGURE 2

PROFITABILITY
OF THRIFTS
TAILS OFF SHARPLY

Percent

Retained earnings
as a percent of assets

1.25

Average Return
on Mortgages

1.00

0.75
0.50
0.25
0.00
-0.25
-0.50
-0.75

Average Cost
of Funds
J__ 1__ 1__ 1__ I__ I__ I__ I__ I__ L_
1970 1972 1974 1976 1978 1980 1982

-

SOURCE: Federal Home Loan Bank Board Jour­
nal, November 1973 - May 1982, Tables S.4.8
and S.4.10.




1.00

1970

1972

1974

1976

1978

1980

SOURCE: National Association of Mutual Savings
Banks, National Fact Book 1981, Table 51.

16

FEDERAL RESERVE BANK OF PHILADELPHIA

NET WORTH AND THE BANKRUPTCY DECISION
In the thrift industry, the deposit insurance agencies — the Federal Deposit Insurance Corporation
(FDIC) and the Federal Savings and Loan Insurance Corporation (FSLIC) — are the main agents that
deal with failing thrift institutions. When should they declare a thrift bankrupt? In competitive
markets, a good measure of a firm’s efficiency is its profits. The present value of future profits (and
losses) is what constitutes the value of a firm as a going concern. If a firm is not using its resources
efficiently, its assets could find a more valuable use somewhere else. Selling the assets and liabilities
will yield a premium over the firm’s going concern value (assuming no liquidation costs). Thus, ide­
ally, a firm should close down when its liquidation value exceeds its value as a going concern.
Under current regulations, the insurance agencies are required to take action whenever the book
net worth of a thrift institution threatens to fall below a certain threshold, defined as a percentage of
total assets. Book net worth is the difference between assets and liabilities as they appear on the
balance sheet.
The relationship between this book measure and a thrift’s going concern value, however, is
tenuous at best. For one thing, book values reflect historical costs, such as the price paid or obtained
at the time the asset or liability was first acquired. And book values do not necessarily provide infor­
mation about future cash flows. For another, by concentrating on a firm’s balance sheet, net worth
measures tell us something about existing assets and liabilities but nothing about future investment
and funding opportunities. By relying on book net worth criteria, the FDIC and FSLIC risk being too
late when institutions are failing and too hasty when they are temporarily insolvent but have profit­
able opportunities in the long run.
The federal thrift insurance agencies are aware that their net worth measure can be misleading,
and they prefer to underplay its importance. Currently they are considering alternative measures.
One proposal is to focus on market net worth. This measure involves valuing assets and liabilities at
their current market price. The market value of a financial instrument is the present value of the
future cash flow it generates. This value will differ from the book value if the yield of the asset is dif­
ferent from the market rate. Thrift mortgage portfolios, when marked to market value, are heavily
discounted because, on average, they earn less than the yield on new mortgages. This discount is a
reflection of the earnings which thrifts lost because they held on to these low-yielding mortgages
while the rate on new mortgages was rising.*
The difference between book and market value will be greater the longer the maturity and the
larger the difference between current market rate and original contract rate. Given that the average
maturity of thrift assets is longer than that of thrift liabilities, the market net worth of thrifts will be
lower than their book value. Andrew Carron of the Brookings Institution made a tentative calcula­
tion of the market value of thrift net worth. He found that the market value had been declining since
1978 although the book value started to decline only after 1980. As of June 30, 1981, his estimate of
market net worth was -$44.1 billion versus a reported book value of -+$42.4 billion.!
Information on the market value of net worth is useful to thrift managers as an estimate of future
net cash flows that are imbedded in the assets and liabilities acquired up to that moment. This
estimate still does not correspond exactly to what we have termed the going concern value of a firm,
however, since it excludes those assets and liabilities that the firm has not acquired yet but can be
expected to acquire in the future. For thrifts in particular, since the new mortgages they are currently
(continued)

*See Richard W. Kopcke, “The Condition of Massachusetts Savings Banks and California Savings and Loan
A ssociations,” The Future of the Thrift Industry, Federal Reserve Bank of Boston, Conference Series No. 24,
October 1981, p. 5.
tAndrew S. Carron, The Plight of the Thrift Institutions, Washington D.C., The Brookings Institution, 1982.
Note that Carron is not unaware of the limitations of using market net worth data.




17

BUSINESS REVIEW

JANUARY/FEBRUARY1983

acquiring yield more than what they have to pay for new deposits, measures based on existing assets
and liabilities underestimate the present value of future profits. The fact that many newly esta­
blished thrifts are very profitable is certainly an indication that, without the burden of the past,
thrifts would be profitable at this moment.
To judge the financial strength of a thrift institution, the FDIC and FSLIC must go beyond evalu­
ating current assets and liabilities. Assessing a thrift’s future viability requires a close look at invest­
ment opportunities in its market area, the expertise and efficiency of its management, and its ability
to attract funds at or below market rates. The fact that most failing thrifts are acquired by firms that
are willing to pay a premium over the market value of assets and liabilities does seem to suggest that
there is optimism about the ability of troubled thrifts to become profitable in the future.

market rates of return on their savings.
Thrifts must pay market rates or face losing
their funding base to competitors like money
market funds. Yet, thrifts are unlikely to be
able to offset higher interest expenses by
earning substantially higher returns on their
assets. By late 1980, more than two-thirds of
thrift mortgages still yielded less than 10 per­
cent. Although new mortgages yield around
15 percent, the replacement of old mortgages
has slowed down because of the current
slump in housing and because people are try­
ing to hold on to their low-cost mortgages.2
Thus, thrifts appear to be in quite a fix.
Thrifts must have been aware of the risks
they were taking by attracting short-term
deposits and by making long-term loans.
What made them take such risky positions?
A major part of the answer lies in govern­
ment regulations.

defining what thrifts can and cannot do have
created a very specialized kind of financial
institution to support the housing industry.
Prior to 1980, these regulations almost com­
pletely limited thrift portfolios to mortgages
andU.S. government securities. In addition,
regulations impose restrictions on the types
of mortgage contracts which thrifts can
make, such as maturity and loan-to-value
limitations, and until recently they pro­
hibited adjustments in mortgage rates.4 There
are also severe geographic constraints on
lending areas. On the incentive side, thrifts
have received certain tax benefits directly
linked to the percentage of total assets they
hold in the form of mortgages.5
By and large, these portfolio regulations
grew out of previously existing operating
conventions. Thrifts grew up as mutual
organizations devoted to the financing of

HOW REGULATIONS
HURT THE THRIFTS
Thrift institutions as they exist today are
essentially a creation of Congress, which has
long tried to encourage home ownership by
promoting home financing.3 Regulations

Bank System (1932) and the Federal Deposit Insurance
Corporation (1934).
4 Loan-to-value limitations impose ceilings on the
ratio of the size of the loan to the value of the house that
is mortgaged. Adjustable mortgage loans were autho­
rized in April 1981.
5 Savings and loans receive a bad debt tax deduction
equal to 40 percent of taxable income if they have 82 per­
cent or more of their portfolio in “qualifying assets” con­
sisting mainly of residential mortgages and U .S. gov­
ernment obligations. For every 1 percent of a portfolio in
which qualified assets are below 82 percent, the baddebt allowance is reduced by three quarters of 1 percent.
For more details see Kenneth R. Biederman and John A.
Tuccillo, Taxation and Regulation o f the Savings and
Loan Industry, Lexington Books, 1976, Chapter 2.

2By mid-1981 the turnover rate of mortgages had
dropped to 7.7 percent from a high of 13.1 percent in
1978. A recent law enforcing non-assumability of mort­
gages, however, should increase turnovers.
3 Current federal regulations are mostly based on
Congressional legislation in the 1930s, authorizing
federal savings and loan associations (Home Owners
Loan Act of 1931) and creating the Federal Home Loan




18

FEDERAL RESERVE BANK OF PHILADELPHIA

Interest rate volatility also brought about
more instability in the construction industry
because the demand for housing is highly
sensitive to mortgage rate fluctuations (Figure
4 overleaf]. Since thrifts have been forced to
concentrate their investments in mortgages
and in limited geographic areas, they are
highly dependent upon local housing mar­
kets. 7 Lack of sectoral and geographic diver­
sification helps to explain why savings
institutions in the depressed Northeast are
worse off than those in comparatively vig­
orous areas such as Florida and California.8*

home construction in their immediate neigh­
borhood. 6 Regulations brought legal force to
what thrifts were doing already because they
found it profitable. To finance their port­
folios of long-term, fixed-rate mortgages,
thrifts typically attracted savings deposits
that had short-term maturities. Borrowing
short and lending long was quite profitable
because interest rates were stable and short­
term rates were below long-term rates. This
favorable interest rate environment lasted
until the mid-1960s and made thrifts a boom­
ing and prosperous industry. Their assets
grew from around $17 billion in 1935 to $111
billion in 1960, or twice as fast as the rate
of inflation.
Economic Conditions Change. In 1966,
the economic environment started to change.
Short rates frequently rose above long rates
and interest rates became much more volatile
(Figure 3). With short rates relatively high,
borrowing short and lending long ceased to
be a sure way to make money. And with
interest rates taking huge swings, thrift
balance sheets and the housing industry both
showed weakness.
Because most thrifts have locked them­
selves into fixed-rate assets, sudden upward
movements in interest rates raise their cost of
borrowing a lot faster than their average
return on assets, squeezing their profit mar­
gins. But if interest rates decline, borrowers
tend to pay off their loans and refinance at
the lower rate. As a result, thrifts’ yields on
assets are more flexible downwards than
upwards. Thrifts lose money when interest
rates rise but they do not gain much when
rates drop; the effect of volatility is not sym­
metric. Thus, on average, interest rate fluc­
tuations impose a loss on thrift institutions.

7The existence of a secondary mortgage market,
however, makes it possible to reduce their exposure to
local conditions by allowing them to take part in
mortgage pools that consist of loans from different
geographic areas.
8Insured S&Ls in the New York FHLBB district had an
average net income-to-assets ratio of -.36 percent over
the 1979-81 period, compared with .22 percent for the
San Francisco district and .02 percent for the nation
as a whole.

FIGURE 3

SHORT RATES
RISE ABOVE LONG RATES
AS VOLATILITY
INCREASES
Percent

Q __L. ■

1930
^Thomas G. Gies, Thomas Mayer, and Edward C.
Ettin, “Portfolio Regulation and Policies of Financial
Intermediaries,” p. 177, Private Financial Institutions, a
Series of Research Studies Prepared for the Commission
on Money and Credit, Prentice Hall, Englewood Cliffs,
1963.




1____I___ I______ I____ I______I____ I______I____I______ I__

1940

1950

1960

1970

1980

SOURCE: Economic Report of the President, 1982,
Table B-67.

19

JANUARY/FEBRUARY 1983

BUSINESS REVIEW

Commercial banks suffer much less from
rate volatility, since they usually are not as
dependent upon a single local industry. 9
Regulations that restrict investments to
mortgages thus are harmful to thrifts because
they make these institutions vulnerable to
interest rate fluctuations and to adverse con­
ditions in their local housing market. When
the interest rate environment started chang­
ing in 1966, regulators did not recognize that
thrifts needed the opportunity to match more
closely maturities of assets and liabilities and
to diversify their assets in order to protect
themselves against interest rate volatility.
Instead, regulators decided to try to insulate
thrifts further from the market. In 1966, Con­
gress passed the Interest Rate Control Act
which empowered the Federal Home Loan
Bank Board (FHLBB) and the Federal De­
posit Insurance Corporation (FDIC) to set
deposit rate ceilings for all thrifts under their
jurisdiction. These agencies were to coor­
dinate their actions with the Federal Reser­
ve’s administration of Regulation Q, which
imposes ceilings on commercial bank deposit
rates. In this kind of regulatory environment,
it was thought, thrifts would not lose funds to
banks which had the flexibility to pay cur­
rent market rates because of their shorter
asset maturity.
For some time, Regulation Q was able to
restrain thrift borrowing costs, but at the
expense of more variable deposit flows.
Each time market interest rates rose above
the ceiling rate on thrift deposits, depositors
in search of higher yields pulled their savings
out of the thrifts and invested them with an
unregulated institution or even lent directly
to borrowers. Increased interest rate vola­
tility in the 1970s created several episodes of
this so-called disintermediation and caused

severe liquidity problems for the thrifts.
Although these rate-ceiling regulations were
intended to help thrifts, they actually harmed
these institutions over the longer run by pre­
venting them from adjusting their policies to
suit the new environment of volatile interest
rates and increasing competition.
What if Thrifts Had Not Been Regulated?
This is not to say that if thrifts had been left
unregulated, they all would have started to
match maturities and to diversify their assets
as early as 1966. Adapting to changing
economic conditions is no easy task. Uncer­
tainty about what changes are actually oc­
curring and how to react to them makes it
difficult to make timely decisions. However,
there were several episodes of sharp interest
rate movements during the late 1960s and
early 1970s, and most thrifts no doubt would
have learned the benefits of diversification
and the costs of maturity mismatches by
1979, when interest rates became still more
volatile.10 As a result, fewer institutions
would have been hit as hard by recent interest
rate fluctuations.
Support for this view can be found by com­
paring thrifts with institutions not subject to
these constraints. Commercial banks, while
they also were subject to Regulation Q, had
wider asset powers and were able to diversify
their assets and to eliminate most of their
maturity g ap .11 Their profits remained rela­
tively unaffected by recent interest rate sur­
ges, while thrift profits took a dive (Figure 2,
page 16].
Canadian trust and mortgage loan com­
panies provide another interesting com-

^Smaller banks in states that severely limit geographic
expansion, however, can also suffer from a lack of
diversification when a single industry dominates their
lending area.

^ F o r some evidence see Mark J. Flannery and Chris­
topher James, Market Evidence on the Effective
Maturity of Bank Assets and Liabilities, Mimeo, Federal
Reserve Bank of Philadelphia, August 1982.




10In fact, the thrift industry has been lobbying for a
variable rate mortgage instrument since the early 1970s,
although what they were requesting probably would not
have been “variable” enough to have protected them
fully against recent interest rate fluctuations.

20

FEDERAL RESERVE BANK OF PHILADELPHIA

by interest rate fluctuations.
In short, stability in interest rates and the
positive spread between long and short rates
before 1966 made it profitable to borrow
short and lend long. Portfolio restrictions
that sanctioned this policy were not resisted
by the thrift industry. Increasing interest rate
volatility since 1966, however, pressured
financial institutions to match maturities and
to diversify their assets. Investment regula­
tions and deposit rate ceilings prevented
thrifts from adjusting their policies to this
new economic reality and left them highly
vulnerable to interest rate fluctuations and to
local housing conditions. Thus a sizable
body of opinion now favors a move toward
deregulation. Disagreement remains, how­
ever, on how much to deregulate and how to
handle the transition period.

parison.12 Until 1978, most of their deposits
had a maturity of five years. These institu­
tions, although they specialized in mortgages
that were amortized over 20 to 30 years, ad­
justed the rates on these mortgages every five
years, so that there was no gap between asset
and liability maturities. When customers
started buying shorter term certificates in
1979, Canadian mortgage lending institutions
issued one-year or two-year rollover mort­
gages, thereby again matching maturities.
The few institutions that did not reduce the
effective maturity of their mortgage assets
incurred substantial losses and had to be
merged into stronger firms. Most Canadian
thrifts, however, avoided problems caused

12For more details see Robert W. Eisenmenger, “The
Experience of Canadian Thrift Institutions,” in The
Future of the Thrift Industry, Federal Reserve Bank of
Boston, Conference Series No. 24, October 1981, pp.
112-139.

DEREGULATION: CURE OR CALAMITY?
In response to recurring crises in the finan­
cial sector, the government has on several
occasions commissioned studies on financial
reform. These studies, such as the Report of
the Hunt Commission (1970) and the FINE
study (1976), concluded that only a lifting of
deposit rate ceilings and a removal of many
other regulatory constraints could assure the
viability of the thrift industry.13* Despite
these recommendations, it took several major
liquidity crises to bring home the message
that most thrifts would not survive if regu­
lations were not relaxed.
First Attempts at Deregulation. The ini­
tial response of the regulatory agencies to the
problems of the thrifts focused on the ability
of these institutions to attract deposits at
market rates. Rather than removing existing
Regulation Q ceilings, regulators authorized
new types of liabilities without deposit rate

FIGURE 4

ANNUAL
HOUSING STARTS
ALSO BECOME
MORE VOLATILE
Millions
2.4
2.1
1.8
1.5

A

A A
- h
/\A
v M Vva / V s' 1/ \

1.2 /

A

^

^

V

V

V

0.9.
O1 J ____ i_____i_____ i_____ i_____i_____ i------1947 1952 1957 1962 1967 1972 1977 1982*

* 3For a short survey of these studies, see John Tuccillo and Kevin Villani, “Current Initiatives and Reform
of the Housing Finance System,” in Occasional Papers
in Housing and Community A ffairs, Vol. 9, HUD,
July 1981.

*1982 is an average based on the first eight
months.
SOURCE: Data Resources, Inc.




21

JANUARY/FEBRUARY 1983

BUSINESS REVIEW

ceilings or with yields linked to rates of U. S.
Treasury obligations of comparable matu­
rity. These new deposits were not all intro­
duced at the same time (Figure 5). A long-term
deposit with no interest rate ceiling was
authorized only in 1982, four years after the
introduction of the six-month money mar­
ket certificates.
In reaction to complaints by thrifts that
these new instruments merely raised the cost
of borrowing without improving their earn­
ings capacity, Congress started expanding
thrift asset powers. Part of this thrust was
realized in the Depository Institutions De­
regulation and Monetary Control Act of
March 1980. The Act allowed savings and
loan institutions to invest up to 20 percent of
their assets in consumer loans, commercial
paper, and corporate debt securities, while
mutual savings banks were authorized to
make commercial, corporate, and business
loans up to 5 percent of their assets. In addi­
tion, the Act established the Depository
Institutions Deregulation Committee to over­
see the gradual phase-out of interest rate
ceilings over a six-year transition period.
More recently, the Thrift Institutions Restruc­
turing Act of October 1982 authorized savings
and loans to make commercial loans up to 10
percent of their assets and further broadened
their asset powers.14 The Federal Home
Loan Bank Board, in another regulatory
change, allowed all institutions it regulated
to issue mortgages with payments that can be
adjusted on a regular basis. The interest rate
on these Adjustable Mortgage Loans (AMLsj
is tied to any index that is readily verifiable
by the borrower and beyond the control of the
lender. The effective maturity of an AML is
equal to the period over which the interest
rate is fixed. Since their nationwide intro­

duction in April 1981, AMLs have grown in
popularity to the point where they now con­
stitute more than half of all newly issued
mortgages.
These new asset and liability powers con­
stitute definite progress in loosening regula­
tory restraints on thrifts. But they cannot
produce a quick fix for the industry’s pro­
blems. Thrifts will have to invest time,
energy, and resources in gearing up to take
advantage of these new powers. Not all
institutions will choose to get involved in
each of these newly permissable areas. But
some diversification seems almost a nec­
essary condition if thrifts are to regain their
long-run viability.
There Are No Alternatives to Deregula­
tion. Although the need for deregulation
seems clear, not all thrift industry represen­
tatives are equally convinced of its merits.
Some thrift representatives, noting that their
net worth started declining at the same time
that regulators began relaxing deposit rate
ceilings, view deregulation more as the cause
of their problem than as the solution. They
argue that the government should extend de­
posit rate ceilings, reserve requirements, and
other regulations to unregulated competitors
such as money market mutual funds.
The history of financial controls suggests
that, although such a policy may have some
of the intended effects in the short run, in the
long run it will be ineffective. Whenever
authorities try to limit voluntary exchange,
people always seek ways to circumvent these
controls. The emergence and continued popu­
larity of commercial paper, negotiable cer­
tificates of deposit, repurchase agreements,
Eurodollar markets, and money market
mutual funds are partly due to the fact that
each allows people to escape, to some degree,
such regulations as deposit rate ceilings. And
some of the same instruments allow institu­
tions to avoid reserve requirements. Forcing
money market mutual funds to operate under
the same rules as commercial banks and
thrifts would create incentives for financial

14The Act permits greater thrift asset investments in
nonresidential real property, state and local obligations,
consumer loans, tangible personal property, education
loans, and small business investment corporations.




22

FEDERAL RESERVE BANK OF PHILADELPHIA

FIGURE 5

LEGISLATION AND REGULATION HAVE CREATED
NEW FORMS OF LIABILITIES
Ceiling*
based on

Minimum
deposit

6 months

6-month Treasury
Bill +

$10,000§

July 1, 1979

2V2-3V2
years +

2 V2

year Treasury
Security t

No minimum Called “Small Savers
Certificate”.

October 1, 1981

1 year

70 percent of 1-year
Treasury Bill rate

No minimum Called “All Savers
Certificate”; interest
is tax-exempt up to
$1,000 for individuals
and $2,000 for joint
returns; expired Dec­
ember 31, 1982.

December 1,1981

IV2 years or
more

No ceiling

No minimum IRA and Keogh ac­
counts only.

May 1, 1982

3 V2

years or
more

No ceiling

No minimum First step in Regula­
tion Q phase-out
schedule.

May 1, 1982

91 days

91-day Treasury
Bill t

$7,500§

September 1, 1982

7-31 days

91-day Treasury
Bill +;removed
January 5, 1983

$20,000§

December 14, 1982

Available
upon demand

No ceiling

$2,500

This “Money Market
Deposit Account”al­
lows limited thirdparty transfers.

January 5, 1983

Available
upon demand

No ceiling

$2,500

Called “Super NOW
Account”; allows unlimited checking, but
is subject to a 12 per­
cent reserve require­
ment.

Date
in effect

Maturity

June 1, 1978

Comments
Called “Money Mar­
ket Certificate”.

*The actual calculation of the deposit rate ceiling is quite complicated. For details see Table 1.16 in
any recent Federal Reserve Bulletin.
tlncludes a V« of 1 percentage point advantage for thrifts over commercial banks.
^Initially the maturity was 4 years or more. It changed several times until it was fixed at 2 V2 - 3 years
on May 1, 1982.
§Reduced to $2,500 effective January 5, 1983.




23

BUSINESS REVIEW

JANUARY/FEBRUARY1983

markets to come up with still other unregu­
lated liabilities.
Other thrift spokesmen feel that their cur­
rent problems are temporary, and that all will
be well again when interest rates come down
from their historically high levels. They argue
that since high and variable interest rates are
the government’s fault and since thrifts were
essentially excercising a public mandate to
specialize in mortgages, the government
should subsidize thrift losses. Currently,
government agencies provide some form of
aid but focus mainly on merging failing
thrifts into new entities (see DEALING
WITH FAILING THRIFTS].
Several aid programs have been suggested
by the thrift industry. Some involve direct aid
in the form of outright cash infusions, sub­
sidized loans, or mortgage warehousing
(purchase of low yielding mortgages at face
value]. Others require regulators to assure
that thrifts are able to maintain a certain
minimum net worth position.15 Thrift argu­
ments for aid are understandable, but the fact
remains that a subsidy does not remove the
ultimate cause of their problems—regulation.
If the government bails out the thrifts with­
out loosening regulatory constraints, they
will still be vulnerable to future interest rate
fluctuations.
The current programs to aid thrifts are
designed to smooth the transition to a dere­
gulated environment. After all, there does
seem to be something to the argument that
thrift institutions are not fully responsible
for the dilemma they find themselves in.
Perhaps more significantly, if no assistance
were forthcoming, the severe difficulties of
some individual institutions could have a
spillover effect on others, perhaps including
financial firms outside the thrift industry.

Still another reaction to deregulation is
that it has happened too fast and has not pro­
ceeded in an even-handed manner. Thrifts’
managers often feel that recent efforts at
deregulation have not been well planned and
that this is the worst of all times to change the
industry. The current earnings crisis makes it
difficult for thrifts to pay market rates on
deposits and to invest resources and acquire
skilled personnel to take advantage of their

new asset powers.
No one can deny that the thrifts face high
costs of adjusting to the new environment,
yet it seems clear that the faster the financial
sector is deregulated, the more quickly thrifts
will be able to protect themselves against
changing interest rates, cycles in housing
construction, and outside competition. The
losses incurred in the past are sunk and can­
not be recouped by postponing deregulation,
but they can occur again. The longer thrifts
are restricted in their investment and funding
powers, the more customers they will lose to
commercial banks or to unregulated com­
petitors such as Merrill Lynch, Sears, and
others.
If stretching out deregulation over time
has pitfalls, so does focusing on certain
assets and liabilities for special treatment.
The initial focus of recent deregulatory efforts
was to relax deposit rate constraints on short­
term liabilities. Although this step did help to
lessen the outflow of savings towards money
market mutual funds, it made the cost of
borrowing more sensitive to interest rate
fluctuations and did not allow thrifts to narrow
their maturity gap. In short, it is not clear that
this regulatory change helped rather than
hurt the thrifts.
Some thrifts have argued that regulators
should have given priority to new asset
powers and should have postponed any fur­
ther lifting of interest rate ceilings. Such a
move indeed might have prevented a rise in
the cost of funding, but it also would have
prolonged the maturity gap (because thrifts
would have been less able to extend long-

•^The Net Worth Certificate Act, as part of the GarnSt. Germain Depository Institutions Act of 1982, autho­
rizes the FDIC and FSLIC to purchase capital instruments
of thrifts with a net worth of less than 3 percent of
assets.




24

DEALING WITH FAILING THRIFTS
Deposits up to $100,000 at most depository institutions are insured by either the Federal Deposit
Insurance Corporation (FDIC) or the Federal Savings and Loan Insurance Corporation (FSLIC). Not
surprisingly, these insurance corporations are the main government agencies in charge of dealing
with failing thrifts. The FDIC and FSLIC can follow several alternative procedures when confronted
with a troubled thrift. First, they can choose to liquidate the institution, acting as a receiver of the
assets and making direct payments to insured depositors. Second, they can help the institution to sur­
vive on its own by providing subsidized loans or direct aid. Third, they can take over the institution,
arrange for new ownership and management, or facilitate a merger, thereby protecting all de­
positors.
The first alternative — selling off the assets and paying off the liabilities — is a solution that the
insurance corporations prefer to avoid because this option is usually the most costly. At liquidation,
the tangible nonfinancial assets (such as buildings) will probably yield less than replacement cost,
while the intangible assets (expertise, reputation) are destroyed in the liquidation. The liabilities, on
the other hand, will have to be paid off at face value, not at the value they have to the institution as a
going concern. The benefit of marking liabilities to market is lost. By mid-1981, this difference added
up to an estimated $24.7 billion for the thrift industry as a whole.*
To avoid the high costs of liquidation, the FDIC and FSLIC usually have tried to provide direct
assistance or to arrange a merger. Direct aid can take the form of outright cash grants, subsidized
loans, or mortgage warehousing (purchase of low yielding mortgages at face value). To be effective,
an aid program must be set up as a temporary device to help an institution bridge some transitional
adverse conditions and should only be granted to thrifts that have a clear prospect of becoming pro­
fitable in the future. Compared with liquidation, direct assistance leaves insured depositors equally
well off, but it provides a subsidy to uninsured depositors, to the owners, and to management; and if
financial institutions expect the government to cover their losses each time things turn bad, they will
be more apt to take excessive risks. To circumvent this problem, FDIC/FSLIC aid programs usually
require increased stockholder participation, profit-sharing with the insuring agency, or increased
supervision of management.!
A third approach that the insuring corporations are now using more frequently is merger of failing
thrifts into healthier organizations. If the market net worth of the failing institution is negative, the
price that the acquirer will pay is likely to be negative also: the FDIC/FSLIC will have to subsidize the
acquisition. There are reasons to believe, however, that the acquiring firm will be willing to pay a
premium above the failing thrift’s going concern value. First, given that geographic constraints have
created a multitude of small thrifts operating at less than optimal scale, a merger could lead to
economies of scale.! Second, if the acquiring firm is not a thrift or operates in a different geographic
area, diversification gains could be realized. Third, if the acquiring firm has superior management,
the new combination could raise earnings due to increased efficiency. Fourth, nonthrifts could be
attracted by the tax advantages that thrifts enjoy. §
To minimize the impact on their insurance funds, the FDIC/FSLIC must try to get the best price for
the thrifts they put up for sale. This approach explains the insurers’ recent efforts to attract not only
healthy thrifts but also commercial banks, out-of-state institutions, and even nonfinancial firms as
potential acquirers of failing thrifts.

‘ Andrew S. Carron, T he Plight o f the Thrift Institutions, p. 19.
tS e e Paul M. Horvitz and R. Richardson Pettit, “Short-Run Financial Solutions for Troubled Thrift
Institutions,” T he Future o f the Thrift Industry, Federal Reserve Bank of Boston, Conference Series No. 24,1981,
pp. 44-67.
tF o r some evidence on these economies of scale, see James E. McNulty, "Economies of Scale in the S&L Indus­
try: New Evidence and Implications for Profitability,” Federal H om e Loan B an k B oard Journal, February 1981,
pp. 2-8. Andrew Carron calculated that more than 400 on average smaller thrifts should be able to save them­
selves by expanding through voluntary mergers (Carron, Chapter 2).
§John T. Mingo, “Short-Run Structural Solutions to the Problems of Thrift Institutions,” The Future of the
Thrift Industry, p. 94.




BUSINESS REVIEW

JANUARY/FEBRUARY1983

term liabilities). In addition, retaining ceilings
would have made it difficult for thrifts to
attract sufficient funds. Thrifts would have
had the power—but not the funds—to make
new investments. And while profits might
have increased, the source of such a gain
would be a continued subsidy from small
savers who do not have the opportunity to
escape the interest ceilings via a money
market fund. Given the disruptive nature of
an unbalanced process of deregulation,
across-the-board reductions in regulations
are preferable to deregulating one asset or
liability at a time.

high and volatile interest rates, a slump in
housing, and competition from other insti­
tutions. To regain their long-run viability,
thrifts must be able to protect themselves by
diversifying their assets, paying market rates
on deposits, and matching maturities.
Many thrift institutions may not survive
the long and hazardous road to a competitive
financial system, but there is no alternative.
Prolonging deregulation or deregulating
selectively will only cause thrifts to lose
many customers to nonregulated firms.
Broadening regulations to include currently
unregulated competitors would be ineffec­
tive, because markets always seem to find
ways to circumvent financial controls. Pro­
viding aid without relaxing regulations would
merely alleviate current thrift losses; it would
not remove the ultimate cause of their
troubles.

CONCLUSION
The current depressed condition of the
thrift industry is the result of adverse eco­
nomic conditions and years of regulatory
constraint that left the thrifts unprepared for




26




New
from the
Philadelphia
Fed
This new pamphlet out­
lines some of the many
savings options currently
being offered by deposi­
tory institutions. Copies
are available without
charge from the Depart­
ment of Consumer Af­
fairs, Federal Reserve
Bank of Philadelphia,
P. O. Box 66, Philadel­
phia, PA 19105

100 North Sixth Street
Philadelphia, PA 19106