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Federal Reserve Bank of Cleveland
Economic Review




ISSN 0013-0281

Spring 1982

Spring 1982
Federal Reserve Bank of Cleveland

Economic Review

Contents
P ersonal Bankruptcy:

Theory and E v id e n c e ..................... 1

After the new bankruptcy code became effective October 1,
1979, the number of personal bankruptcy filings (PBFs)
in the United States sharply increased to record highs.
Some analysts believe that the new code is primarily
responsible for this increase. To evaluate this belief, K J.
Kowalewski examines the theoretical factors behind a con­
sumer’s decision to file for bankruptcy; in the aggregate
these factors are broadly consistent with the behavior of
PBFs in the past 20 years. Using these theoretical factors,
he develops a regression model to explain PBFs and to eval­
uate the impact of the new code. He finds that the new code
may have had a smaller impact on PBFs than previous
studies have reported.
The Case for S taggered -R eserve A ccou ntin g..................... 3 0
The Federal Reserve System rations the supply of money to
the economy by rationing the supply of reserves to the
banking system. Most U.S. banks are required to settle
their reserve accounts simultaneously each Wednesday. If
their total reserve needs differ from the amount made avail­
able by the System on settlement day, then the discrepancy
must be made up at the discount window. This means that
the System cannot directly control the supply of total
reserves. William T. Gavin argues for an institutional
reform to lengthen the reserve-accounting period from one
week to four weeks and to stagger the reserve-accounting
periods among four groups of banks. Such staggered-reserve
accounting would allow the Federal Reserve to set operating
targets for total reserves.




Personal Bankruptcy: Theory and Evidence
by K.J. Kowalewski

In the statistical year ending June 30, 1981,
total personal bankruptcy filings (PBFs) in the
United States rose to a record high of 452,730,
about 44 percent higher than the previous record
of 314,862 set in statistical year 1980 and about
102 percent higher than in 1975.1 This increase
is a major concern of lawmakers and consumer
lenders; it has swamped the already overloaded
bankruptcy court system and increased loan
losses of some consumer lenders by as much as
124 percent over 1979.2
Some analysts agree that slow real economic
growth, high interest rates, and distortions to
consumer budgets caused by unexpectedly rapid
inflation during the late 1970s have forced many
consumers into bankruptcy. Yet, a large number
of analysts contend that other factors are at
1. A statistical year begins on July 1 and ends on the follow­
ing June 30.
The term personal bankruptcy filings refers to the number
of bankruptcy petitions filed by employees and others not in
business. They include filings under both Chapters 7 and 13
of the U.S. Code, Title 11. Joint husband and wife petitions
are counted twice to make them comparable with past filing
statistics. If joint petitions under the new bankruptcy code
are not counted twice, the filing figures become 241,430 and
313,499 for 1980 and 1981, respectively. These numbers are
reported by the Administrative Office of the U.S. Courts.
2. There are no figures on total loan losses resulting from
personal bankruptcy available from the Administrative
Office of the U.S. Courts. However, many consumer lenders
record their own losses from bankruptcy. For example, Con­
tinental Illinois reported a 74 percent increase in credit
losses due to bankruptcy in 1980 from 1979; Sears reported a
109 percent increase in 1980 and a 16.5 percent increase in
the first 11 months of 1981; Citibank reported a 56 percent
increase in 1980 from 1979; in the first nine months of 1980,
Household Finance Company reported its highest loan
charge-off due to bankruptcy—40.3 percent of its total loan
charge-off; Chase Manhattan Bank’s VISA card plan lost $5
million in 1980, up 300 percent from 1979, and about $12
million in 1981.




work, factors that have changed the behavior of
PBFs since 1978, if not before. These factors
include advertising by lawyers, a changing atti­
tude toward the stigma of bankruptcy, an in­
creased awareness of consumer rights, and, ef­
fective October 1, 1979, a new bankruptcy
code—the Bankruptcy Reform Act of 1978. Many
analysts claim that the new code is responsible
for the vast majority of the increase in PBFs
since late 1979.3 In response, the Subcommit­
tee on Courts of the U.S. Senate Judiciary Com­
mittee has begun hearings on possible changes
in the code.4
The appropriate responses of lawmakers and
consumer lenders depend on a careful analysis
of the impact of the new code. If the new code has
created an unintended and undesired increase in
loan losses arising from personal bankruptcy,
then legislative changes may be necessary. If the
new code is blameless or thought to be an equi­
table law, then consumer lenders will need to
tighten their lending policies to lessen their
exposure to loan-default risk in this new envi­
ronment. Tighter consumer-lending policies are
a concern of policymakers, because the availabil­
ity of credit affects the pace of personal con­
sumption expenditures, the largest component
3. See, for example, Pfeilsticker (1978); Carter (1982); and
Brimmer (1981).
4. Bankruptcy Reform A ct o f 1978, Hearings before the
Subcommittee on Courts of the Committee on the Judiciary,
97 Cong. 1 Sess. (Government Printing Office, 1981).

K.J. Kowalewski is an economist with the Federal Reserve Bank
o f Cleveland. Marcia Fortunato and Douglas Fox provided
research assistance fo r this paper; John Davis, Charles Luckett,
Joe Snailer, and especially M ark Sniderman made helpful
comments. Steve Suddaby’s generous efforts in providing accu­
rate bankruptcy statistics are also gratefully acknowledged.

2

Economic Review □ Spring 1982

of the gross national product. For example, one
of the major reasons why forecasts of a recession
occurring in 1979 were incorrect was because
consumer spending was stronger than expected,
financed by unexpectedly high levels of con­
sumer credit. Moreover, some analysts suspect
that the Consumer Credit Restraint Program
contributed to the sharp 9.8 percent decline in
real personal consumption expenditures during
the second quarter of 1980, a postwar record (see
Cox 1980).
This paper evaluates the impact of the new
bankruptcy code by examining aggregate PBFs
since 1961. Aggregate PBFs are used, because
they are the only data readily available to study
the personal bankruptcy issue. Although aggre­
gate data cannot be used to evaluate the individ­
ual and societal costs and benefits of the new
code, they can be used to estimate the aggregate
impact of economic forces. The first section of
this paper presents a theoretical framework for
analyzing the PBF data. The second section
reviews the historical behavior of aggregate
PBFs and suggests an interpretation based on
the implications of the theoretical model. The
third section develops and estimates an empiri­
cal model of quarterly aggregate PBFs that is
broadly consistent with the theoretical model
and uses it to examine the impact of the new
bankruptcy code. The important result is that
the new code may account for about one-third of
the increase in PBFs. The question of whether
the new code may have changed the empirical
model is also examined. The final section con­
tains concluding remarks.

I.

The Elements of the PBF Issue

Framework
It is useful to view the PBF issue as two separ­
ate questions. First, why do some consumers fall
into financial distress, unable to pay their con­
tractual obligations—installment and other reg­
ularly scheduled debt payments, insurance, rent,
and utility payments, for example—with either



current income or savings? Second, why do some
financially distressed consumers file for bank­
ruptcy, while others do not?
Failure to meet contractual obligations is, of
course, a necessary condition for bankruptcy,
and it occurs for a variety of reasons.5 Income
loss resulting from layoff or unemployment and
burdensome expenses, such as alimony, childsupport payments, hospital and doctor bills, and
judgment debts from personal liability suits, can
put considerable pressure on the budgets of con­
sumers with insufficient savings. Past studies
of individual personal bankrupts also have found
that poor money management can precipitate a
financial crisis.6 Apparently, some consumers
do not have the willpower or knowledge to live
5. Intuitively, this seems true. If a consumer makes all of
his/her contractual payments on time, he/she will be in good
standing with his/her creditors and need not worry about
bankruptcy or legal actions by creditors. However, the bank­
ruptcy laws usually have included other conditions for
bankruptcy. Section 3a, Chapter III of the bankruptcy law in
effect until October 1979 specifies six possible “acts of bank­
ruptcy,” the last of which permits an individual to file for
bankrupcty by admitting “in writing his inability to pay his
debts and his willingness to be adjudged a bankrupt.” Sec­
tion 623, Article IV, Chapter XIII of the same law requires
that “a petition filed under this chapter shall state that the
debtor [in this case a wage earner and not a business] is
insolvent or unable to pay his debts as they mature
The new bankruptcy code does not explicitly define “acts of
bankruptcy.” To be eligible for relief under the new Chapter
13, Section 109e, Title 11 of the U.S. Code states that an
individual must have a “regular income” and owe less than
$100,000 in unsecured debts and $350,000 in secured debts.
The new bankruptcy code apparently does not require con­
sumers to claim that they are insolvent or having difficulty
meeting their contractual payments, but this requirement
probably did not prevent many, if any, consumers from filing
under the old law.
6. See, for example, Brunner (1964); Dolphin (1965); Herr­
mann (1965); Mathews (1969); Misbach (1964); Reed (1967);
Sadd and Williams (1933); and Stanley and Girth (1971).
These studies find poor money management to be the single
most important precipitator of financial distress. Unfortu­
nately, the term poor money management is never clearly
defined by these studies. Depending on the judgments of the
researchers and the people they interviewed, this term may
be confused with income loss or dishonesty (the willful
assumption of debts to take an unfair advantage of creditors
and the bankruptcy laws) as the cause of financial distress
for a particular consumer.

Federal Reserve Bank of Cleveland

within their means. They save little or nothing
and assume a contractual payment burden that
they quickly find they cannot meet.7 Most con­
sumers who fall into financial trouble for this
reason are presumably young, lower-income
individuals with few savings or consumer goods
necessary to raise a family, but the past crosssection studies are not clear on this point.8
Financial distress does not necessarily lead to
bankruptcy, because consumers may be able to
refinance their debts directly through their cur­
rent creditors or indirectly through proraters,
consumer credit counseling services, finance
companies and financial institutions, or wageearner trusteeship programs such as the one
administered by the Cleveland Municipal
Court.9 When a financially distressed consumer
knows about these alternatives and can choose
among them and bankruptcy, he/she examines
the expected cost of each option in terms of fore­
gone current and future consumption and
chooses the option that yields the maximum
present value of his/her expected future utility.
However, when there are constraints on the
ability of a consumer to borrow against his/her
future income, the only utility-maximizing
options available may be the bankruptcy options.
These issues are best understood by extend­
ing the intertemporal utility maximization
7. It is ironic that many personal bankrupts fell into finan­
cial distress through poor money management. These con­
sumers were able to obtain all the credit they needed to place
themselves into financial distress, but they could not obtain
sufficient credit to get themselves out. This presumably
stems from the absence of perfect information in consumer
loan markets.
8. In fact, these studies made very few attempts to under­
stand the relationships among the characteristics of per­
sonal bankrupts. For example, it was never made clear
whether the younger personal bankrupts had different kinds
and amounts of debts than older personal bankrupts. Nor
were attempts made to understand the dynamics of financial
distress. For example, did the consumers spend all of their
savings to avoid financial distress, or were there no savings
to fall back on when financial crises occurred?
9. That a financially distressed consumer may get out of
financial distress by refinancing the existing debt with new
debt implies that the availability of consumer credit alone is
not sufficient to explain PBFs or financial distress.




3

model, which pertains to an individual con­
sumer. For simplicity, assume a world with no
uncertainty or inflation and consider a con­
sumer who has a known life span of T periods
and is early in his/her life cycle, just starting a
family, and unconcerned about bequests. This
basic framework is illustrated in figure 1. The
horizontal axis denotes the dollar value of con­
sumption in period 1, Ci, and the vertical axis
denotes the present value of consumption in
periods 2 through T, CF2, discounted to period 2;
that is,
CF2 = Ci + Q / a + r) + . . .
* CT/( 1 + r)T~2 ,
where r is the one-period interest rate. The con­
sumer’s utility is a function of Ci and CF2, and
his/her preferences for combinations of Ci and
CF2 are summarized by a family of indifference
curves. Two such curves are shown in figure 1.
The consumer is indifferent to alternative com­
binations of Ci and CF2 along a particular indif­
ference curve but prefers combinations that lie

4

Economic Review □ Spring 1982

on indifference curves above or to the right. The
slope of the indifference curve at any point mea­
sures the consumer’s preference in trading Ci for
CF2 at that point and depends on the rate at
which the consumer discounts future utility.
The larger the rate, called the rate of time prefer­
ence, the more the consumer values Ci relative
to CF2 , and the steeper the indifference curve
at every point.
The consumer’s labor income in period 1 is Y\
,
and YF2 is the present value of labor income
known to be earned in periods 2 through T,
discounted to period 2. The consumer can bor­
row against future income to consume more
than Yi in period 1 or save some of Yi to con­
sume more than YF2 in the future. In this sim­
ple model, with the borrowing and lending inter­
est rates equal to rand constant across time, the
consumer can choose any combination of Ci and
CF2 as long as it is within his/her budget, that
is, within the area (AF2)AiO. The intertemporal
budget constraint, (AF2)Ai, defines the maxi­
mum combinations of Ci and CF2 that the con­
sumer can purchase. Along this constraint, the
consumer can trade 1 dollar of Ci for (1 + r) dol­
lars of CF2. At Ai the individual would consume
Yi + (YF2)/( 1 + r) dollars today and nothing in
the future, while at AF2 future consumption is
YF2 + (1 + r)Y\ and current consumption is
zero.10 At the point where the slope of the indif­
ference curve equals the slope of the budget con­
straint, point C* in figure 1, the rate at which the
consumer prefers to trade Ci for CF2 equals the
rate at which the consumer can do so in the
market. The present value of the consumer’s
utility is maximized at this point. To achieve
this consumption bundle, the consumer in fig­
ure 1 borrows C*1 - Y\ today and repays the
loan with YF2 - CF2 * in the future. However, if
the consumer had a high or low enough rate of
time preference, the consumer would choose A\
or AF2, even though the slope of the indifference
curve would not equal the slope of the budget
constraint at that point. When the consumer
10. Henceforth, the set of affordable consumption bundles
will be referred to only by its budget constraint designation.
For example, the set (i4F2)i4iO is designated (AF2)A i .




chooses a point where the slopes are unequal,
he/she is said to be at a corner solution.
Nonhuman wealth—for example, savings ac­
counts and real estate—is easily incorporated
into the model. When the consumer owns Wi
dollars of nonhuman wealth in period 1, the
budget constraint shifts to (ZF2)Z i in figure 1,
where
Xi = Yi + Wu X F2 = YF2 + (1 + r)W u
Z\ - Ai + W i, and
ZF2 = AF2 + (1 + r)Wu
The consumer achieves a higher present value
of utility at C**, consuming Ci** and borrowing
Ci** - Xi today while consuming CF2** and re­
paying the loan with YF2 - CF2 ** in the future.
Up to this point it has been assumed that
capital markets are perfect. Consumers can bor­
row and lend at the same interest rate, con­
sumption plans are constrained only by the
present value of the consumer’s human and
nonhuman wealth, and loan horizons are essen­
tially infinite. It is widely recognized, however,
that capital markets are not perfect. Transac­
tions and information costs drive a wedge be­
tween borrowing and lending interest rates, and
imperfect information about the credit worthi­
ness of potential borrowers prompts lenders to
impose down-payment, collateral, and collateral
maintenance requirements on loan contracts
(see Stiglitz and Weiss 1981; Smith 1980). More­
over, transactions costs and imperfect informa­
tion act to shorten loan horizons, and thin resale
markets make it difficult to sell or borrow
against many tangible assets. For consumers
whose income streams mesh quite well with
desired consumption plans or whose nonhuman
wealth is sufficiently large and liquid, capitalmarket imperfections are not crucial. For other
consumers, especially consumers contemplating
bankruptcy, these imperfections, known as li­
quidity constraints, can restrict actual con­
sumption plans to be less than they would be in
perfect capital markets.

Federal Reserve Bank of Cleveland

5

Figure 2 illustrates how liquidity constraints
can affect the intertemporal budget constraint.
When the borrowing rate, rb, is greater than the
lending rate, r[t the budget constraint has a
“kink” at the initial endowment point, X. A
representative constraint is {ZF2)XA\. If, in
addition, there is a collateral requirement for
borrowing or a limit to the amount of nonhuman
wealth that can be used for period 1 consump­
tion, then the constraint resembles (ZF2)UCi**.
The constraint (ZF2)VX\ occurs when all of the
nonhuman wealth is illiquid in period 1. If bor­
rowing is not permitted, the constraint becomes
(.ZF2)VYi or (ZF2)XXi, depending on whether
nonhuman wealth today is completely illiquid or
completely liquid, respectively. Shorter loan
horizons, with rb imply constraints similar
to (ZF2)C**Ci** in figure 2. In this case, the
expression Ci** - X\ represents the maximum
permissible amount of borrowing, where

Zx = Yi

+

Wi

+

■

yf2

Cl** = Yi + Wi + T T 7 ’
y3
y f 2 = y2 +-—

r4
yt
+---- - + . . . +
T
1 + r (1 + rf " ' (1 + r)T~2

and
Y
YF'o = Y2 +--- +. . . +■
1 +r
(1 + r)T~2

for a t < T period loan. It is clear that liquidity
constraints can increase the likelihood of corner
solutions and force a borrowing consumer to a
present value of utility below the perfect capitalmarket level; liquidity constraints do not affect
consumers who are saving along the (ZF2)V
segment of the budget constraint.
To distinguish between financial distress and
the decision to file for bankruptcy, and to com­
plete the model, we must introduce the element
of uncertainty. Ideally, the model would include
uncertainty about future labor income, con­



sumption needs, and interest rates. To keep the
analysis simple, only uncertainty about future
income will be considered. Financial distress
then can arise when actual future income is less
than its expected value. Again for simplicity,
assume creditors compensate for this uncer­
tainty by offering only one-period loans at a rate,
rb, higher than the lending rate, r[t and assume
the consumer owns only human wealth. The
consumer’s consumption decision in any period
depends on current income and interest rates,
expected future income, and actions taken in
previous periods. In future periods, the con­
sumer may not (be able to) consume in the pat­
tern he/she planned or expected in past periods,
but will change plans in ways consistent with
revised expectations of future labor income and
unfulfilled or exceeded expectations of past
labor income.
Consider the consumer in figure 3. Current
(period 1) labor income is Fi, known with cer­
tainty, and YF2* is the consumer’s and the credi­

6

Economic Review □ Spring 1982

Fig. 3

Initial B udget Constraint

CF2 Future consumption

Fig. 4

B udget Constraint with Full Paym ent

CF3 Future consumption

G

Ci Period 1 consumption

tors’ expectations of the present value of the
consumer’s labor income in periods 2 through T,
discounted to period 2. The consumer has no
borrowings or savings from previous periods.
The maximum amount of expected future con­
sumption, AF2, equals Yi(l + r{) + YF2 *; the
maximum possible amount of current consump­
tion in the absence of limits on loan horizons, A i,
is Y\ + (YF2*)/( 1 + rb)\the maximum amount of
current consumption with only one-period loans,
Ci*, is Yi + (Y2*)/(l + rb), where Y2* is the
expected labor income in period 2. The optimal
consumption point in period 1 is C*, entailing
borrowing of Ci* - Yi and a loan repayment of
YF2* - CF2* in the future (period 2, since the
loan matures in one period).
If actual labor income in period 2, Y2, is Y2* as
expected in period 1, then in period 2 the con­
sumer faces the problem shown in figure 4. The
initial endowment point would be F, and EFG H
would be the budget constraint in period 2 in the
absence of the loan repayment. Because the con­
tractual loan payment of Y2 - Y 2 must be
repaid in period 2, the expected initial endow­
ment point, or more properly the expected discre­



Period 2 consumption

tionary funds point, is Ek*, and the consumer’s
expected budget constraint in period 2 is
(AF3)B2*JQ,
where
AFz = Y'2(l + rt) + YF3*,
a2=

r2+

YF3*

1

rb

’

y3*

Q=K +TT7b'

Y3 * is the expected labor income in period 3, and
YF3* is the expected present value of labor
income in periods 3 through T, discounted to
period 3.11
11. Previous life-cycle models imposed borrowing con­
straints by restricting the choice of debt-income ratios. In
this model, the borrowing constraint is more natural,
depending on the amount of debt repayments that the con­
sumer can afford. Only in the special case where debt
repayments are a fixed proportion of outstanding debt are
the two constraints equivalent. Subsistence or nondiscretionary consumption also may be incorporated into this
model.

Federal Reserve Bank of Cleveland

If actual labor income in period 2 turns out to
be less than Y2*, then both E F G H and
(AF3)B2*JQ would shift to the left. Suppose
actual labor income in period 2 is L, not Y2* as
first assumed. The consumer is now in financial
distress, because L is insufficient to cover the
loan repayment. Even if all of L is used to repay
the loan, the consumer is in arrears for Y2 * Y'2 - L, defined as a. To keep matters simple,
assume financially distressed consumers have
only three options—Chapter 7 bankruptcy,
Chapter 13 bankruptcy, or personally refinancing
the loan with the creditors. This problem is
illustrated in figure 5. Actual labor income in
period 2 is L, the same as in figure 4, and YF3* is
the consumer’s and the creditors’ expectation of
the present discounted value of the consumer’s
future labor income. The budget constraint in
the absence of the loan repayment and other
constraints, (A F 3)B2*JQ, is not attainable but is
shown for reference. Creditors stand willing to
refinance the debt at the current loan rate, rb,
without collateral or other requirements, pro­
vided that the whole debt be repaid by the third
period. The creditors will not extend additional
credit, however, thereby restricting G to be no
greater than L .12 Under these conditions,
K IM L is the intertemporal budget constraint
with refinancing.
The derivation of this constraint is straight­
forward. If the consumer repays all of L in period
2, then he/she must repay the remaining a
dollars with interest in period 3. This amounts
to a (l + rb) dollars. The maximum possible ex­
pected value of CF3 is then YF3* - a(l + rb),
shown as point K in figure 5, as long as I 3* is at
least a (l + rb). If the consumer prefers a positive
value for G, then a + C2 with interest must be
repaid in period 3. The maximum value of G is
the lesser of L or the value of G that satisfies
the equation (G + «) (1 + rb) = Y3*. This is
point M in figure 5, assuming for simplicity that
L satisfies the equation. Note that there is no
saving in period 2 with this constraint. W hat­
ever is not consumed is used to repay part of the
12. This is another liquidity constraint that may be im ­
portant to financially troubled consumers.




7

debt. The two points K and M determine the
equation of the constraint:
CF3 = YF3* - (G + a) (1 + rb),
Y3* > (G + a) (1 + rb), 0 < G < L.
The position of K IM L in the G(CF3) plane, or
in other words the cost of debt refinancing in
terms of foregone consumption in period 2 and
the future, depends on the parameters YF3*, a,
and rb, as well as other loan terms not explicitly
incorporated here. Lower values of YF3* and
higher values of a and rb increase the cost of
refinancing the debt. In period 2, a is predeter­
mined by actions taken in period 1 and by L, but
YF3* and rb are determined by creditors. Based
on the income shortfall in period 2, creditors
may lower their expectations about the con­
sumer’s future labor income in period 3 and
beyond and/or may demand a higher loan rate. A
lower value of YF3* produces a downward
parallel shift in K IM L, resulting in a decline in
the maximum value of CF3. A higher rb shifts
K IM L down and twists it clockwise, also re­
sulting in a decline in the maximum value of
CF2 . In both cases, the maximum value of

8

Economic Review □ Spring 1982

Ci may also decline. Other loan terms, such as
collateral requirements or other borrowing
limits, lower the maximum value of G . Tighter
loan terms of any form represent tighter liquidity
constraints, and, clearly, if these constraints are
tightened too far, K IM L can vanish; that is, the
costs of financing the debt will be essentially
infinite, and the option will be unavailable.13
The bankruptcy constraint is complicated by
the fact that there are two types of bankruptcy
available to a financially troubled consumer.
The first type of bankruptcy is straight bank­
ruptcy, defined in Chapter 7 of the new bank­
ruptcy code (11 U.S.C. § 701). Under this option,
all of the consumer’s nonexempt assets are li­
quidated; secured creditors are paid first, and
any remaining proceeds go to the unsecured
creditors. The second type of bankruptcy, re­
habilitation of consumer debtors, is not techni­
cally considered as bankruptcy. Defined in
Chapter 13 of the new bankruptcy code, this
option allows the consumer to establish a courtprotected debt repayment plan.14The consumer
can retain all of his/her assets, and specified
payments are made each month to repay the
debt. The major requirement of a Chapter 13
bankruptcy is that the unsecured creditors re­
ceive at least as much as they would have
received had the consumer alternatively filed for
straight bankruptcy (see Kowalewski 1981).
Moreover, the same consumer can face differ­
ent bankruptcy costs in different states and
bankruptcy court districts; exemption provisions
vary across states, and bankruptcy court judges
have considerable discretion in approving bank­
ruptcy plans (see Misbach 1964; Stanley and
Girth 1971). Exemption provisions define exempt
13. On the other hand, creditors may not demand complete
repayment if they think they can receive more than they
would if the consumer filed and completed bankruptcy. The
debt financing constraint would then shift upward and pos­
sibly twist counterclockwise if creditors accepted a lower
interest rate. Thus, creditor lending policies and liquidity
constraints can depend on existing bankruptcy laws.
14. 11 U.S.C. § 1301 (1978). Though not technically a bank­
ruptcy, a filing under Chapter 13 will be considered a bank­
ruptcy in this paper because a filing under either chapter is a
measure of consumer financial distress and creditor losses.




assets, that is, the amounts of various assets
that the consumer can retain after a straight
bankruptcy, and they affect the minimum repay­
ment unsecured creditors are entitled to receive
under Chapter 13. Consumers can choose be­
tween federal and state exemption levels unless
state law permits the use of only state levels.
Chapter 13 plans do not necessarily require
complete repayment of the debts like the refi­
nancing option described earlier. Bankruptcy
court judges can specify that only a fraction of
unsecured debts be repaid, and some Chapter 13
cases have been approved with zero payment to
unsecured creditors. Hence, the types and the
amounts of assets and debts that the consumer
owns significantly affect the costs of the bank­
ruptcy alternatives.15
The consumer in figure 5 has a very simple
portfolio in period 2: L is the only asset, and
Y2 * - Y 2 is the only debt, which is unsecured
because the consumer holds only human wealth.
The consumer’s exempt assets are assumed to
be H. Under straight bankruptcy, L - H is paid
to the creditors, and the remaining debt is dis­
charged or forgiven.16 This constrains the con­
sumer’s resources to be H in period 2 but leaves
unchanged the expected resources of YF3 * in the
future. Because the consumer is free to save any
portion of H, the budget constraint under
straight bankruptcy is FGIH . One possible
budget constraint under a Chapter 13 bank­
ruptcy is TIH, which assumes that the court
requires full repayment of the debt with inter­
est, in amounts L - H in period 2 and
(a + H) (1 + rb) in period 3. The initial endow­
ment point under this option is I. If the bank­
ruptcy court decided in favor of less than full
payment, the initial endowment point could lie
anywhere between K IM L and FGNML. The GN
portion of this boundary arises from the re-

15. The new bankruptcy code also permits consumers to
avoid nonpurchase money security interests on household
goods to facilitate the consumers’ “fresh start” after
bankruptcy.
16. For simplicity, filing, attorney, and court fees are
assumed to be zero; in practice, these fees have priority over
any payment to creditors.

Federal Reserve Bank of Cleveland

quirement that the creditors must receive at
least L - H, which equals YF3* - R, the
amount they would receive if the consumer
alternatively filed a straight bankruptcy. If the
court requires repayment of the debt without
interest, the constraint becomes KIH.
The union of the three budget sets—KIM L,
FGIH, and TIH — determines the set of all pos­
sible consumption bundles available to the con­
sumer; this grand budget set is FG IM L. Of
course, other grand budget sets are possible,
depending on the exemption provisions, the dis­
position of the bankruptcy court judge, and the
tightness of liquidity constraints. The consumer
chooses the consumption bundle that maximizes
the present value of his/her utility and, in doing
so, decides among the three options: Chapter 7
bankruptcy, Chapter 13 bankruptcy, or debt
refinancing through creditors. For example, if
the consumer in figure 5 chooses the consump­
tion bundle represented by point G, he/she can
obtain that point only by filing a Chapter 7
bankruptcy. Similarly, if the consumer chooses
a bundle along the segment IM , then the con­
sumer refinances through the creditors.
Two additional comments deserve mention.
The non-convexity of the grand budget set may
leave the consumer indifferent to using more
than one of the options. For example, the con­
sumer may be indifferent between point G and
point M. Generalizing the model to incorporate
uncertainty about consumption needs or inter­
est rates does not appreciably affect the formu­
lation of the grand budget set, though it may
affect the creditors’ willingness to refinance.

Alternatives to Bankruptcy
The grand budget set in the previous section is
conceptually very simple, incorporating only
one alternative to bankruptcy. It could be very
complex, however, depending on the composi­
tion of the consumer’s portfolio, the exemption
levels, and the creditors’ opinions of the con­
sumer’s credit worthiness. The grand budget
set becomes even more complicated when the
other bankruptcy alternatives are incorporated,
and it is impossible to specify one general grand



9

budget set applicable to all consumers. It would
be useful, however, to have some general notion
of the actual constraints facing financially dis­
tressed consumers to make the model more con­
crete. Unfortunately, this is difficult to do, as
there are no empirical studies about the bank­
ruptcy alternatives. However, some past studies
of individual personal bankrupts criticize the
alternatives and provide anecdotal evidence about
their usefulness. Moreover, some of these studies
attempt to learn why personal bankrupts choose
bankruptcy over other alternatives. None of this
evidence contradicts the view that these alterna­
tives are imperfect responses to an imperfect
consumer loan market. Not all alternatives have
been or are available to all financially distressed
consumers; when they are, their relative costs
can be very high, principally through lack of pro­
tection against creditors’ legal actions, and their
eligibility requirements exclude certain finan­
cially distressed consumers.17 That is, this evi­
dence does not contradict the view that liquidity
constraints have been an important element of
the PBF problem.
17. These legal actions include garnishment of wages and
property, repossession of goods, setoff of checking and sav­
ings accounts, and attachment of wages and goods. Gar­
nishm ent is a legal action of a creditor to compel a third
party—such as an employer or a bank—owing money to or
holding money or property for a debtor to pay the money or
turn over the property to the creditor instead of the debtor.
Secured creditors take a security interest in the good pur­
chased with the loan or in the property already owned by the
debtor, usually specifying that if the consumer defaults on
the loan, the full amount of the loan immediately becomes
due. When the debtor misses a debt payment, the creditor
has the right to repossess the security. If the security is worth
less than the balance of the loan, the creditor may get a court
judgment requiring the debtor to make up the deficiency,
called a deficiency judgm ent. Consumers have been known to
file bankruptcy to avoid what they believe are unfair defi­
ciency judgments. In the case of a loan default, a setoff is
used by a depository institution to take the defaulting con­
sumer’s checking, savings, and time accounts that it holds
for the consumer to pay the loan in full and obtain a defi­
ciency judgment for any remainder. Attachment is a process
by which a debtor’s wages and/or property are placed in the
custody of the law and held as security pending the outcome
of a creditor’s suit. Until the case is decided, the debtor
cannot dispose of or use the wages or property, or place them
beyond the reach of the creditor.

10

Economic Review □ Spring 1982

Proraters, also known as financial or credit
counselors, credit doctors, or debt poolers, are
entrepreneurs who make their profit by mediat­
ing between creditors and financially distressed
consumers. For a fee, a prorater establishes a
debt-repayment plan for a consumer having dif­
ficulty meeting his/her contractual obligations.
The prorater collects a fixed payment from the
consumer each month and disburses this pay­
ment on a pro rata basis to the creditors. Some­
times budgeting advice also is offered to the
financially distressed consumer.
There are problems with proraters’ services.
The repayment plan obtains only the voluntary
participation of the creditors. Creditors can drop
out of the plan at any time and try to collect from
the consumer directly or indirectly through legal
means, such as garnishment or attachment.
Even if the plan collapses, the consumer must
pay the prorater’s fee. Stanley and Girth (1971)
argue that some consumers may have been
misled by proraters’ advertising, believing mis­
takenly that creditors’ cooperation was manda­
tory, not voluntary. These researchers claim
that “the fees charged usually have been uncon­
trolled and the safeguards against misuse of the
collected funds few. Thus the debtor’s financial
burden frequently has been increased rather
than diminished by debt pooling. And creditors,
too, have had no assurance that they will be
treated fairly” (p. 71). In response to these and
other shortcomings, 40 states as of 1971 had
absolutely prohibited, drastically curtailed, cir­
cumscribed, or regulated proraters’ practices.
Other states “have judicially imposed restraints
that render proration difficult, if not impos­
sible” (Stanley and Girth, p. 71). Misbach (1964)
notes that, until 1963, proraters in many states
required a fee equal to 15 percent of the money
handled. He also observed that, after the Utah
legislature imposed tighter controls on proraters
and set a maximum fee of 10 percent of the
money handled, most of Utah’s proraters dis­
continued business.18
18. A recent article in The Wall Street Journal reported that
average proraters’ fees are currently 12 percent of the debt
outstanding (see Vicker 1981).




Reed (1967) argues that proration services
were not applicable to all consumers in Oregon.
Proraters in Oregon apparently accepted only
about one-third of their applicants; another onethird of the applicants were severely financially
distressed and were rejected because they were
likely to drop out of the service. The remaining
one-third were not in serious financial trouble
and also were rejected. Of the accepted appli­
cants, 50 percent dropped out after the first year,
and only 15 percent to 17 percent completed the
basic repayment plan.
The wage-earner trusteeship is a debt-repayment program offered by only a few state and
local governments. A local resident can volun­
tarily join the program by agreeing to pay a fixed
percentage of his/her disposable earnings to
court trustees for pro rata distribution to credi­
tors. A consumer who makes regular payments
is protected from wage garnishment. Another
advantage is that the costs are quite low. A trus­
teeship program administered by the Cleveland
Municipal Court requires a one-time $5.00 filing
fee, a $0.50 fee for each listed creditor, and a debt
repayment equal to 17.5 percent of disposable
earnings each pay period.
Unfortunately, wage-earner trusteeships are
not useful to all financially distressed consumers.
Cleveland’s program, for example, has the fol­
lowing drawbacks:
1. secured creditors are not compelled to
participate,
2. creditors may garnishee the wages of co­
signers on loan agreements,
3. creditors are free to take other legal
actions against consumers,
4. personal checking and savings accounts
can be attached by creditors,
5. budget counseling is not offered,
6. debts pertaining to rent, home mortgage,
and current utilities do not apply, and
home foreclosure may occur, and
7. if a trusteeship is dissolved for nonpay­
ment, it cannot be reopened before six
months has passed unless the nonpay­
ment resulted from illness, lack of work,
or a strike.

Federal Reserve Bank of Cleveland

In their study, Stanley and Girth (1971) found at
least 4 percent of the personal bankrupts in their
northern Ohio sample previously had been in
wage-earner trusteeship proceedings.
The Consumer Credit Counseling Service
(CCCS) is an increasingly popular alternative to
bankruptcy. Begun in 1955, there are now over
200 offices nationwide in communities with
populations of at least 100,000. In 1980 this notfor-profit service advised 130,000 consumers
nationwide. Under the direction of the National
Foundation for Consumer Credit and mostly
funded by business, the CCCS educates finan­
cially distressed consumers in practical budget­
ing techniques and provides proration services
to severely distressed consumers at little or no
cost to the consumer. While legal protection
against garnishment and attachment is not
guaranteed because of the funding arrangement,
creditors are more likely to participate voluntar­
ily in a CCCS-sponsored repayment plan, in­
creasing the chances that a consumer will suc­
cessfully complete a plan. Though not widely
available or recognized before the 1970s, today
the CCCS may be the best alternative to bank­
ruptcy available through a third party.19
A financially distressed consumer can always
try to refinance his/her debts directly with cred­
itors or indirectly through debt-consolidation
loans provided by consumer finance companies
and other consumer lenders. In dealing directly
with creditors, the consumer can appeal to the
common-law devices of composition and exten­
sion or both for informal out-of-court settle­
ments. A composition is an agreement between
the consumer and at least two of his/her credi­
tors specifying that a partial payment is ade­
quate to satisfy the debts owed these creditors.
An extension permits the consumer to extend the
maturity of a debt without fear of attempts to
collect by the participating creditors, as long as
the payments on the new loan are made dili­
gently. Either arrangement conceivably can be
arranged through a third-party creditor, such as
19. Both Reed (1967) and Mathews (1969) praised the
CCCS, saying that, at the time, its only shortcoming was not
being widely available.




11

a consumer finance company, though the old
debts usually would be paid in full with the
consolidation loan.
Composition and extension offer the advan­
tages of being quick and requiring little effort.
Their disadvantages are that they provide con­
sumers no legal protection against actions by
creditors who choose not to participate in the
scheme and no advice on proper budgeting prac­
tices. Moreover, creditors probably view debtconsolidation loans as riskier than other loans
and hence charge a higher interest rate and
demand more stringent collateral requirements
to compensate for the additional risk, raising the
costs of these schemes relative to the costs of
bankruptcy or other alternatives.20
Other researchers have commented on the
inefficiency of these schemes for many con­
sumers. Herrmann (1965) argues that composi­
tion is difficult to arrange directly with creditors
and that it is designed primarily for use by busi­
nesses and not by consumers with few or no
assets. Stanley and Girth (1971) report that
these schemes “are most likely to be used when
the debtor seems to be in temporary trouble and
creditors expect to do satisfactory business with
him in the future” (pp. 73-74). They also suggest
that creditors’ attorneys do not always recom­
mend composition. They found that when asked
what is best for creditors of individual con­
sumers, 22 out of 42 attorneys responded Chap­
ter 13, while only 15 replied composition agree­
ment (p. 74).
More to the point, Haden (1967) argues that
one purpose of Chapter 13 was to make exten­
sions and compositions available to those con­
sumers who could not get them in the market­
place. That is, the originators of Chapter 13 felt
that the consumer loan market failed to provide
deserving consumers with extension and com­
position options, and that a correctly formulated
Chapter 13 option would leave both creditors
20. Consolidation loans can be particularly risky under the
new bankruptcy code, because they change purchase money
security interests into nonpurchase money security inter­
ests, and certain nonpurchase security interests pertaining
to household goods necessary for a “fresh start” may be
avoided.

12

Economic Review □ Spring 1982

and consumers better off. In justifying repeated
use of Chapter 13 by an individual consumer,
Haden writes:21
Anyone who questions the need for the service
[Chapter 13] should first ask how many times in
the last twenty years he has become overloaded
with debts and borrowed enough to pay off
everyone. In our present economy, where it
seems unpatriotic to be out of debt, stones
should not be thrown at Chapter 13 repeaters
when typical upper-class procedure is to borrow
a lump sum at the bank. Many wage-earners’
[bankruptcy] petitions are made under the pres­
sure of several thousand dollars of debt. The
debtor cannot go to the bank and borrow this
much money. He must use the only device open
to him.

A common fault of all the alternatives is their
inadequate protection against legal actions by
creditors, actions that bring a financial crisis to
a head. Like other problems with the alterna­
tives, these legal actions raise the (expected) cost
of the alternatives in terms of present and future
consumption. Repossession of an automobile or
other durable goods and garnishment or setoff of
checking and savings accounts disrupt life-cycle
spending and savings plans, forcing consumers
to readjust their plans and bear the costs asso­
ciated with the loss of these items and their
future reacquisition. Even more serious is the
possibility that an employee can be fired if
his/her wages are garnisheed. Under the gar­
nishment provisions in the Consumer Credit
Protection Act, effective in 1970, an employee
cannot be fired for garnishment against one
indebtedness, but depending on state law can be
fired for garnishments against a number of
21. See Haden (1967), p. 596. In practice, Chapter 13 of the
old bankruptcy act seems to have been a poor alternative to
straight bankruptcy. Herrmann (1965) reports that critics of
Chapter 13 believe that “the administrative expenses charged
debtors are too high and that the length, austerity and inflex­
ibility of the payment plans often drive debtors using the
plan into straight bankruptcy. The plan is clearly of use only
to those who meet the eligibility requirements and have
sufficient income to repay all or most of their debts within
three years” (p. 30). Also see Reed (1967), pp. 73-75; Mathews
(1969), p. 91; Stanley and Girth (1971), chapters 4 and 5;
Misbach (1964), p. 39; and Haden (1967).




debts. Moreover, wage garnishments may leave
the consumer with insufficient income to meet
basic living expenses or other contractual obli­
gations, perhaps resulting in additional legal
actions by other creditors.
Past studies of individual personal bankrupts
found that threatened or actual legal action by
creditors was crucial in many consumers’ bank­
ruptcy decisions.22 Brunner (1964) estimates
that between 1956 and 1961 an average of about
36 percent of all consumers who filed for straight
bankruptcy in Ohio were defendants in legal
suits brought by creditors. Dolphin (1965) con­
cludes that bankruptcy “apparently is used as a
tool for avoiding garnishment” (p. 111). He
found that 75 percent of the Flint (Michigan)
area bankrupts indicated that they filed for
bankruptcy because of actual or threatened gar­
nishment; in most cases it was the threat of
garnishment, since only 10 percent had been
garnisheed within 4 months of their filing for
bankruptcy. Mathews (1969) found that 70 per­
cent of his sample “had been threatened with
wage attachments by creditors in the period
immediately preceding the filing of the bank­
ruptcy petition” (p. 82). About 30 percent were
named as defendants in suits brought by credi­
tors in the year preceding the bankruptcy filing,
and about 78 percent of these consumers had
personal or real property repossessed during
this time and owed deficiency balances on this
debt.23 Thirty-two percent of the attorneys,
bill collectors, and credit bureau managers inter­
viewed by Reed (1967) mentioned actual or
22. Most of these studies fail to distinguish clearly between
the reason for financial distress and the reason for choosing
bankruptcy over the alternatives. For example, when Stan­
ley and Girth (1971) asked debtors why they went into bank­
ruptcy court, they received answers such as poor money
management, poor health, and marital and other family
problems, which are really precipitators of financial dis­
tress. They remarked that these reasons were the same as
those given in response to a question about the reasons for
financial distress, but they failed to see that these reasons
alone were not sufficient for those bankruptcies. Sadd and
Williams (1933), Mathews (1969), and Reed (1967) also seem
to be unclear about the distinction.
23. Repossessions and deficiency balances are described in
footnote 17.

Federal Reserve Bank of Cleveland

threatened wage garnishment, and eight per­
cent mentioned deficiency judgments as “causes”
of personal bankruptcy. Sadd and Williams
(1933) concluded that 15.4 percent of the con­
sumers in their sample filed for bankruptcy “to
avoid payment of judgment debts; 87.8 percent
of these judgments were obtained against en­
dorsers of notes for others” (p. 14). Stanley and
Girth (1971) found that 43 percent of the con­
sumers in their sample mentioned threats of
legal action and 18 percent mentioned actual
legal action in response to the question about
why they went into bankruptcy court. “Other
persons we interviewed—referees in bankruptcy,
attorneys (both for debtors and creditors), and
welfare authorities—also emphasized fear of
garnishment or suit as a leading cause of bank­
ruptcy” (p. 47).24
Without empirical studies about the expe­
riences of financially distressed consumers in
using these bankruptcy alternatives, it is diffi­
cult to estimate the relative costs of these pro­
grams. However, the evidence considered here
does not contradict the view that for some finan­
cially distressed consumers, these alternatives
involve very high costs relative to those of the
bankruptcy options. The inability to borrow
against future income appears to be an effective
constraint for some consumers, possibly forcing
them into a bankruptcy decision they would not
make in the absence of this constraint.
It should be clear that the PBF issue is a very
complicated one. A consumer’s decision to file
for bankruptcy depends on the interaction of
his/her preferences for current versus future
consumption, the types and amounts of tangible
and financial assets and liabilities owned, the
24. They also show that the fraction of wages exempt from
garnishment is negatively related to the number of personal
bankruptcies per capita (see Appendix B, pp. 236-41).
This discussion should not be construed as a condemna­
tion of consumer lenders. Imperfect information about a
consumer’s ability to repay debts is not necessarily the fault
of creditors. Creditors may find it difficult to refinance the
debts of some consumers and not those of others without
appearing to violate the provisions of the Consumer Credit
Protection Act of 1968. Under the old bankruptcy law, how­
ever, creditors were rewarded for swift action against con­
sumers who defaulted on their debts.




13

consumer’s and the creditors’ expectations of
his/her future income, creditors’ risk prefer­
ences, loan interest rates, the consumer’s nondiscretionary outlays, the available bankruptcy
alternatives, and the existing bankruptcy and
consumer lending legislation.

II.

Historical Overview
of Aggregate PBFs

Figure 6 shows the annual PBF rate—the total
number of PBFs during a statistical year per
100,000 people aged 20 years and over—since the
total PBF data were first collected in 1940. The
unusual behavior of this series stands out clearly.
The PBF rate rose steadily from 1946 through
1967, falling only once, in statistical year 1962.
After 1967, the PBF rate displayed a pronounced
procyclical pattern, rising during recessions and
falling between them. In statistical years 1980
and 1981, the PBF rate grew at historically rapid
growth rates to historically high levels; in 1981,
about 0.3 percent of the population aged 20 years
and over filed for personal bankruptcy.
Some researchers have argued that the new
bankruptcy code is primarily responsible for the
rapid growth of PBFs in 1980 and 1981 (see
Brimmer 1981; Carter 1982; Pfeilsticker 1980).
However, business bankruptcy filings (BBFs)
grew as fast as PBFs since the new code was
enacted. The ratio of PBFs to total bankruptcy
filings, also shown in figure 6, suggests that the
new bankruptcy code may not be responsible.
This ratio was 0.87 in statistical year 1979,
before the new code became effective, and re­
mained at 0.87 in 1980 and 1981, after the new
code was effective. Because the major changes in
the new code deal with PBFs, the rapid increase
in PBFs since late 1979 suggests that economic
forces may have had a large impact on PBFs, as
they apparently had on BBFs (see King 1981,
p. 196). Moreover, the increase in the PBF rate
began in statistical year 1979, before the new
code became effective. The unusual behavior of
PBFs across time can be explained largely by
aggregate economic forces and their impact on

14

Economic Review □ Spring 1982

Fig. 6

P ersonal Bankruptcy Filings:

1940-81

Per 100,000 population, age 20 and over

a.

Percent

PBF rate based on a statistical year, beginning on July 1 and ending on June 30 of the following calendar year.

consumer financial positions, an important factor
in a consumer’s decision to file for bankruptcy.25
25. Legal changes in the late 1960s and the 1970s dealing
with actions creditors can take against consumers who
default on debts and the legal rights of consumers involved
in credit transactions may also have had some impact on the
PBF rate. These laws include the Consumer Credit Protec­
tion Act, Fair Debt Collection Practices Act, Truth in Lend­
ing Act, Fair Credit Reporting Act, Fair Credit Billing Act,
Equal Credit Opportunity Act, and the Uniform Consumer
Credit Code. Other changes were made at various intervals
by individual states to update their laws regarding wage
garnishment and wage and property attachment and
assignment.




The PBF rate fell in the late 1960s, when con­
sumer financial positions were remarkably
strong. Real disposable income per capita grew
at an annual rate of 3.3 percent from 1964 to
1969, after growing 1.7 percent between 1954
and 1959 and 2.3 percent between 1959 and 1964.
The aggregate debt-income ratio—the ratio of
total outstanding household liabilities to nomi­
nal disposable personal income—was essentially
flat from 1965 to 1969 at about 0.72, after rising
steadily from 0.47 at the end of 1954. Moreover,
the real value of financial assets accounted for
over 78 percent of the real value of household net

Federal Reserve Bank of Cleveland

worth from year-end 1963 to year-end 1968;
nondiscretionary spending fell to about 60 per­
cent of disposable personal income in the late
1960s, from about 62 percent in 1961.26 Thus,
by the late 1960s probably fewer consumers
found themselves in severe liquidity-constrained positions.
Consumer financial positions remained strong
until the 1973-75 recession. Although the debtincome ratio remained at about 0.72 and nondis­
cretionary spending accounted for 61 percent of
disposable personal income throughout the re­
cession, interest rates reached historic levels in
1974, real per capita disposable personal income
grew at an annual rate of onlyl.7 percent from
1972 to 1975, and the real value of household
portfolios grew slowly and shifted in composi­
tion, with the real value of financial assets
accounting for about 70 percent of real house­
hold portfolios at year-end 1974. This shift in
consumer financial positions contributed to a
record 224,354 PBFs in statistical year 1975.
It is important to understand the role of con­
sumer portfolios. Liquid assets—mostly finan­
cial assets—provide a readily available source of
funds to cushion a shortfall in income. During
recessions, incomes decline, liquid assets are
drawn down, and tangible assets, such as houses,
automobiles, and refrigerators, may be difficult
26. The real value of household net worth is defined as the
end-of-year constant dollar sum of financial assets, con­
sumer durables and housing stocks, and land minus constantdollar household liabilities. The asset and liability figures
come from the household sector of the Flow of Funds
accounts. The financial asset and nonmortgage liability fig­
ures are deflated by the personal consumption expenditure
(PCE) implicit price deflator, and the mortgage liabilities are
deflated by the fixed weight deflator for gross fixed private
residential investment. The land figure comes from the
household sector of the Balance Sheets for the U.S. Econ­
omy, compiled by the Flow of Funds division of the Board of
Governors of the Federal Reserve System; it is deflated by
the fixed weight deflator. The durables and housing stocks
are computed from the flows of constant-dollar consumer
durables and nonfarm residential structures expenditures
using a benchmark computed by the Bureau of Economic
Analysis and constant straight-line depreciation. The non­
discretionary spending series comes from Luckett (1980) and
begins in 1960. Gasoline-company credit-card liquidations
were removed to avoid a discontinuity in the series in 1971.




15

to liquidate quickly at full market value. The
simultaneous occurrence of these events may
push some consumers into very tight liquidityconstrained positions, referred to as corner solu­
tions in the previous section. In such positions
small changes in income may have abnormally
large effects. In the aggregate, if many con­
sumers are in tight liquidity-constrained posi­
tions, small changes in income may lead to large
changes in PBFs.
This nonlinear response helps explain the
behavior of the PBF rate after 1975. Even though
consumer portfolios were weak coming out of
the 1973-75 recession, the PBF rate fell sharply
as real per capita disposable income growth
accelerated to an annual rate of 2.6 percent
between 1975 and 1979. At the same time,
household income continued to be bolstered by
the employment of additional household
members. After a slight reliquification in 1975
and 1976, consumer portfolios became highly
levered as consumers purchased houses and real
estate to guard against inflation.
Consumers were able to maintain better life
styles and purchase many tangible assets in the
late 1970s because consumer and mortgage
credit were widely available. This trend proba­
bly dated back to the optimism prevalent in the
late 1960s. Having experienced the remarkably
prosperous 1960s, many creditors expected such
prosperity to continue. Baily (1978) argues that
in the late 1960s the business press was confi­
dent that activist policy measures could and
would keep the growth of the real economy high
and inflation rates low. This optimism also was
reflected in the rapid growth in the number of
bank-credit-card programs in the late 1960s and
early 1970s, especially with the introduction of
National BankAmericard, Inc., and Interbank
Systems (see Fitzpatrick 1973). This type of
unsecured lending probably would not have
evolved as it did without the expectation and at
least partial realization in the early 1970s that
associated default risks were low. By the late
1970s, creditors’ expectations probably changed
but the credit programs remained; financial
institutions needed the programs to attract con­
sumer deposits from money market mutual

16

Economic Review □ Spring 1982

funds, and consumers demanded and probably
needed such credit to finance consumption.27
When energy prices doubled and real per cap­
ita disposable personal income growth slowed in
1979, consumers held very weak financial posi­
tions; the real value of financial assets repre­
sented only 67 percent of the real value of house­
hold portfolios, nondiscretionary spending
amounted to 65 percent of disposable personal
income, and the debt-income ratio was up to
0.81. It is likely that PBFs increased in 1980-81
through the combination of weak financial posi­
tions and income growth and high interest rates.
The remaining question is whether the new code
affected PBFs as well. This analysis also sug­
gests that the type of consumer who filed for
bankruptcy in the late 1970s and early 1980s
may be unlike the type who filed in earlier years.
Now, more affluent consumers, who own rela­
tively many more tangible assets than con­
sumers in the past, may be filing because they
cannot manage their highly levered portfolios.
Perhaps many of these consumers would have
filed for bankruptcy without a change in the
bankruptcy law.

III. Em pirical Model
of Aggregate PBFs

Specification and Estimation
The empirical model is a multiple regression
model and draws its specification from the spirit
of the theoretical model outlined in the first sec­
tion. Although that model pertains to an indi­
vidual consumer (or consumer unit such as a
household), it highlights the types of variables
that may be useful for explaining aggregate
PBFs. The dependent variable is the natural
logarithm of PBFs per capita (LBKPOP^), which
is measured as the ratio of seasonally adjusted
quarterly PBFs to quarterly population aged 20
27. As mentioned in footnote 24, creditors may have ex­
perienced legal restrictions in rationing consumer credit.




years and over. The quarterly PBF data were
seasonally adjusted using the standard default
options of the X-ll seasonal adjustment pro­
cedure, and the quarterly population figures are
interpolations of annual figures.
The explanatory variables are seasonally ad­
justed and include the following:28
YLP^ = real, per capita, after-tax
“permanent” labor income
in the current quarter.
Labor income includes
wages and salaries and other
labor income components of
personal income
YLT, = real, per capita, after-tax
“transitory” labor income
in the current quarter
RTB, = the three-month Treasury
bill rate in the current
quarter
NONDPAY^j = nondiscretionary payments
relative to disposable per­
sonal income in the previous
quarter. Nondiscretionary
payments are total food, fuel
oil and coal, and housing
services expenditures; 20
percent of household oper­
ating services; 25 percent of
other services; 50 percent of
gasoline and oil expenditures
(all of these being compo­
nents of personal consump­
tion expenditures in the Na­
tional Income Accounts) plus
repayments of consumer in­
stallment credit except gasoline-company credit-card
debt plus repayments of
mortgage debt
RTAPC^_j = real, per capita stock of con­
sumer durables and residen­
tial structures in the pre­
vious quarter, measured at
end of quarter
28. Further detail about the construction of these variables
can be obtained from the author.

Federal Reserve Bank of Cleveland

RDBTPC^j = real, per capita outstanding
household liabilities in the
previous quarter measured
end-of-quarter and taken
from the Flow of Funds
accounts
RDEPPC/_1 = real, per capita household li­
quid assets in the previous
quarter, measured end-ofquarter and taken from the
Flow of Funds accounts. L i­
quid assets are defined as de­
mand deposits and currency
plus time and savings ac­
counts plus money market
mutual fund shares.
A constant term and a lagged dependent variable
round out the list of independent variables.
Labor income is used, as it is the primary
source of income for most consumers. In the first
quarter of 1981, for example, labor income
accounted for 69 percent of total personal income.
More importantly, past cross-section studies
found that the majority of personal bankrupts
worked in blue-collar or lower-paying whitecollar jobs, both of which pay wages and salar­
ies. The before-tax figures were adjusted by
average tax rates for both personal income taxes
and personal contributions for social insurance.
The permanent component was computed by
first calculating an eight-quarter moving aver­
age of the real, after-tax per capita figure and
then projecting this average ahead one quarter,
using the previous eight-quarter growth rate of
the average. The transitory component is then
the difference between the actual income figure
and the permanent component. Both income
terms should be negatively related to the PBF
rate, because higher incomes provide a greater
cushion against financial distress. The impacts
of these two income terms should be different, as
they have different impacts on consumption and
saving decisions. The permanent component
can be thought of as the expected future income
term, YF, in the theoretical model, the income
measure used by consumers in determining cur­
rent consumption and saving. When actual



17

income is different from that expected, or in
other words when transitory income is non-zero,
consumption and savings plans may be dramat­
ically altered, especially when transitory income
is negative, and difficulty in meeting nondiscretionary payments is encountered. Thus, the co­
efficient of the transitory income component
may be larger in absolute value than the coeffi­
cient on the permanent income component be­
cause transitory income is more important for
financially distressed consumers.
The theoretical model points out the distinc­
tion between borrowing and lending rates of
interest. Unfortunately, few data on consumer
credit interest rates are available, and there are
a variety of assets, and hence interest rates,
relevant to consumer savings decisions. The
incorporation of many interest rates would only
introduce a multicollinearity problem. In addi­
tion, savings interest rates are probably irrele­
vant for financially distressed consumers. Thus,
only one short-term interest rate is used as a
proxy for short-term consumer credit interest
rates, and it should be positively related to the
PBF rate.
The theoretical model also stresses the impor­
tance of nondiscretionary payments. When such
payments command a high percentage of dis­
posable income, little income is available to meet
unexpected expenses, and it may be difficult to
obtain additional credit. Thus, N O N D P A Y ^
should be positively related to LBKPOPr There
are obvious problems with defining and con­
structing nondiscretionary payments with ag­
gregate data, but the series described by Luckett
(1980) seems reasonable, with a minor modifica­
tion.29 There is a break in the consumerinstallment-credit liquidation series in 1971,
when gasoline-company credit-card figures were
29. There are two partially offsetting problems with this
series. The installment-debt liquidation figures include not
only contractual payments but also discretionary payments.
W ith the rise in the use of credit cards as transactions media
instead of debt media, the installment-debt liquidation fig­
ure is probably an over-estimate of contractual installmentdebt repayments. The lengthening of loan maturities in the
past five years to ten years works in the opposite direction,
lowering liquidations relative to earlier liquidations.

18

Economic Review □ Spring 1982

moved from noninstallment to installment debt.
Since the figure for gasoline-company creditcard liquidation is small relative to the figure for
total installment debt liquidation—for example,
equal to 2 percent of total liquidations in
1981:IVQ—it was removed from total liquida­
tions to eliminate the break. The personal con­
sumption expenditure categories and their
weights included with the debt repayment fig­
ures are crudely designed to measure basic liv­
ing expenses that all consumers must pay.
The importance of the three portfolio terms
has been discussed in the preceding sections as
well. The composition of consumers’ portfolios
has direct bearing on the costs and benefits of
filing for bankruptcy and on the ability of con­
sumers to weather unexpected income losses or
large consumption needs such as medical bills.
When consumers hold many liquid assets rela­
tive to other portfolio items, LBKPOP/should be
low; when consumers hold relatively many
tangible assets or debts, LBKPOP/ should be
high. The durables and residential structures
stocks were built from expenditure flows using
straight-line depreciation and benchmark values
for year-end 1950 computed by the Bureau of
Economic Analysis. The financial assets used in
RDEPPC^ are quite liquid compared with other
financial assets that consumers may own and
probably comprise the majority of financial
assets held by financially distressed consumers.
The differences in the timing of the explana­
tory variables, contemporaneous or lagged one
quarter, result from the discrete decision-making
framework of the theoretical model. Recall that
consumption and savings decisions are made in
the theoretical model by considering what is
already owned and contracted to be paid at the
beginning of the period and what income and
interest rates will be during the current and
future periods. Hence, in the empirical model, a
bankruptcy decision in the current quarter de­
pends on last quarter’s portfolio composition
and nondiscretionary payments, and the cur­
rent quarter’s income and interest rates.
The theoretical model by itself cannot define
the complete specification of the empirical model,
because the theoretical model pertains to an



individual consumer, whereas the empirical
model uses data aggregated across time and con­
sumers to consider all consumers together. Such
aggregation obscures the characteristics and
behavior of any particular consumer and imparts
a considerable degree of inertia or autocorrela­
tion to such data. What this means is that past
values of the explanatory variables will be use­
ful in examining PBFs. In fact, last quarter’s
portfolio composition and nondiscretionary pay­
ments depend on all past consumption and sav­
ings decisions, income flows, and interest rates,
so that a current bankruptcy decision conceiva­
bly depends on all other past values of the
explanatory variables as well. However, all of
these past values cannot be included in the
model, and the use of only a few past values is an
arbitrary decision, could omit important past
values, and would introduce multicollinearity
among the explanatory variables, thereby con­
founding the estimation of the coefficients. A
parsimonious way to include the influence of all
other past values is to use a lagged dependent
variable as an explanatory variable.30 This
approach is employed here, even though it may
make the impact of the new code difficult to
evaluate. The coefficient on this lagged term
should be less than one in absolute value.
Finally, the log-linear functional form was
assumed so that the elasticity of an explanatory
variable changes with the value of that variable.
In this way, large imbalances in the indicators of
consumer financial strength can have large
effects on PBFs, as noted in the previous section.
The model was estimated by maximum likeli­
hood with a correction for first-order serially
correlated errors (see table 1). Because the
empirical model will be used to evaluate the
impact of the new bankruptcy code, it is impor­
tant that the estimated coefficients are stable.
Equations 1 through 5 in table 1 show the coeffi­
cients estimated over different sample periods.
The first observation in the estimation period is
always 1961:IQ, but the last observation varies
across the columns as shown. Equation 5 con30. This assumes that the lag distributions of the explana­
tory variables are proportional to each other.

Federal Reserve Bank of Cleveland

Table 1

19

R egression R esults under the Old Bankruptcy Law

Dependent variable is LBKPOP; standard errors are in parentheses
Equation
1

2

3

4

5
75

60

64

1961:IQ1975:IVQ

1961:IQ1976:IVQ

68
1961 :IQ1977:IVQ

72
1961:IQ1978:IVQ

1961:IQ1979:IIIQ

0.7810
(0.0444)

0.7705
(0.0389)

0.7715
(0.0370)

0.7711
(0.0363)

0.7598
(0.0356)

-0.7675
(0.5881)

-0.7784
(0.5547)

-0.7335
(0.3851)

-0.8348
(0.2924)

-0.6154
(0.2481)

-0.3274
(0.0673)

-0.3193
(0.0621)

-0.3152
(0.0560)

-0.3089
(0.0534)

-0.3180
(0.0530)

-0.4128
(0.0751)

-0.4378
(0.0642)

-0.4416
(0.0560)

-0.4382
(0.0539)

-0.4409
(0.0538)

0.0075
(0.0044)

0.0081
(0.0040)

0.0080
(0.0037)

0.0084
(0.0034)

0.0066
(0.0031)

rtapcm

0.1201
(0.0378)

0.1093
(0.0338)

0.1078
(0.0312)

0.1062
(0.0302)

0.1101
(0.0300)

RDBTPC m

0.3018
(0.0534)

0.3090
(0.0489)

0.3077
(0.0446)

0.3067
(0.0435)

0.3108
(0.0432)

RDEPPC m

-0.1998
(0.0506)

-0.1978
(0.0469)

-0.1980
(0.0435)

-0.1983
(0.0428)

-0.1995
(0.0427)

NONDPAY^ j

1.6793
(0.8986)

1.7305
(0.8450)

1.6580
(0.5785)

1.8121
(0.4288)

1.4793
(0.3583)

0.0302
0.9615

0.0293
0.9683

0.0291
0.9680

0.0289
0.9675

0.0287
0.9659

0.1110
-0.2855
0.0002

0.0400
-0.3635
0.0002

-0.0330
-0.3620
0.0002

-0.1620
-0.3533
0.0002

-0.0110
-0.3360
0.0002

Number of observations
Sample period
Explanatory variables
LBKPOPM
CONSTANT
YLP,

YLT,

RTB,

Equation standard error
Adjusted R2
Durbin h
Serial correlation coefficient
Residual mean

tains the coefficients estimated with all of the
quarterly PBF data available under the old
bankruptcy law, 1961 :IQ through 1979:IIIQ.
Looking first at equation 5, the model appears
to fit the data very well. All of the coefficients
have the expected signs and are statistically
significant at the 5 percent level using a twotailed test. Only the coefficient on RTB^ is sur­



prising. Although positive, it has a small impact
on PBFs. As expected, transitory income has a
larger coefficient in absolute value than per­
manent income, and the composition of con­
sumer portfolios significantly affects PBFs. In
absolute value debt has a greater impact than
liquid assets, which in turn have a greater
impact than tangible assets. After accounting

20

Economic Review □ Spring 1982

for scale differences, N O N D P A Y ^ has about
the same impact as RTAPC^j, and the coeffi­
cient on LBKPOP^j is statistically different
from one at the 5 percent level.
The means and the elasticities, evaluated at
the means, of the explanatory variables for the
estimation period 1961:IQ through 1979:IIIQ are
shown in table 2 and provide another measure of

T able 2 Equation 5: Old Law Period
1961:IQ-1979:IIIQ
Explanatory
variable
LBKPOP, j
CONSTANT
YLP,
YLT,
RTB,

1.2104

0.9197
-0.6154
-1.1782
-0.0270
0.0341
0.8168
1.2637
-0.9064
0.9065

1.0000
3.7050
0.0612
5.1673
7.4190
4.0659
4.5432
0.6129

rtapcm

RDBTPC, !
R D E P P C ,,
NONDPAY, j

Table 3

Elasticity
at mean

Mean

F -T ests for Structural Stability8
Equation

Equation

1

2

0.189
(4,51)
0.454
(8,51)
0.560
(12,51)
0.577
(15,51)

3
4

5

2

3

4

—

—

—

—

—

0.764
(4,55)
0.792
(8,55)
0.763
(11,55)

1.700
(4,59)
0.774
(7,59)

—

0.703
(3,63)

a. The numbers in parentheses are the numerator and
denominator degrees of freedom.
Following are the corresponding 5 percent points for
various F-distributions:
F(3,60) = 2.76
F(4,60) = 2.53
F(8,60) = 2.10




F(12,60) = 1.92
F(15,60)= 1.84

the relative importance of these variables. PBFs
show the greatest elasticity with respect to YLP^
and RDBTPC^j and the least elasticity with
respect to RTB, and YLTt, the latter because its
mean is very small.
Comparing equation 5 with the preceding four
equations in table 1 suggests that the coeffi­
cients are stable. The coefficients do not change
by alarming amounts, an almost surprising
result when using models with lagged depen­
dent variables and aggregate time series data.
Indeed, none of the ten pairwise F-tests in table 3
can reject the null hypothesis of structural sta­
bility with a 5 percent significance level.31
The out-of-sample forecasting results shown
in table 4 for the first four equations also support
this view.32 The root mean squared errors
(RMSEs) are all the same order of magnitude as
the equation standard errors, although two
RMSEs of dynamic forecasts are almost double
in size. The correlations between actual and
forecast values are very high, especially for the
first two equations, whose forecast intervals

31. This is loosely speaking, of course, since these tests
cannot test the equality of the coefficients (see Rea 1978).
Criticism about the power of F-tests whose numerator
degrees of freedom are greater than the number of explana­
tory variables is misdirected. The difficulty in obtaining
precise parameter estimates using small samples of aggre­
gate time series data is well known. Moreover, there is little
knowledge about the small properties of many of the estima­
tion techniques used by macroeconometricians. Wilson
(1978) provides a useful example of when these tests are
uniformly most powerful. Multicollinearity does not appear
to be a severe problem here. Standard errors of the coeffi­
cients and condition numbers are small, and auxiliary R2s of
the explanatory variables vary from about 0.6 to 0.9.
32. The terms static and dynamic refer to two types of
forecasts computed for each equation. Static forecasts are
computed with the actual values of the lagged dependent
variable, LBKPOPM . Dynamic forecasts are computed suc­
cessively, using last quarter’s forecast value as the value of
the lagged dependent variable for the current quarter’s fore­
cast. The static forecasts are usually best for checking how
well the model explains the dependent variable outside the
estimation period, since the dynamic forecasts can be
thrown “off-track” by a single large error. However, when
the dynamic results do not differ greatly from the static
results, there is additional evidence in favor of the adequacy
of the model.

Federal Reserve Bank of Cleveland

Table 4

21

Forecasting R esu lts of LBKPOP
Equations
1

2

3

4

1976:IQ-1979:IIIQ

1977:IQ-1979:IIIQ

1978:IQ-1979:IIIQ

1979:IQ- 1979:IIIQ

Static Dynamic

Static Dynamic

Static Dynamic

Static Dynamic

1.176

1.158

1.182

1.277

1.194 1.232

1.168 1.180

1.189 1.189

1.307 1.324

0.971
0.029
0.024
0.368
0.147
0.485

0.965
0.028
0.024
0.126
0.222
0.652

0.969
0.030
0.025
0.054
0.295
0.651

0.999
0.030
0.023
0.954
0.044
0.002

Actual mean
Forecast mean
Correlation be­
tween actual
and forecast
RMSE
Theil U
Bias
Regression
Disturbance

0.970
0.059
0.050
0.868
0.014
0.117

contain turning points. There appears to be
some bias in both the static and dynamic fore­
casts, but it is generally small. More impor­
tantly, the regression component of the Theil U
decomposition, an indicator of systematic error
originating from the equation, is small for both
forecasts of all equations. Thus, it appears that
the specification fairly accurately captures the
dynamic behavior of aggregate PBFs under the
old bankruptcy law.33

E stim ated Impact
of the New Bankruptcy Code
Seasonally adjusted PBFs increased from
57,496 in 1979:IIIQ to 112,469 in 1981:IVQ.
About 44,000 PBFs, or 80 percent of this increase,
occurred in the first three quarters of the new
code period. The coincidence of this sharp in­
crease and the date the new code took effect has
led many analysts to believe that the new code is
primarily responsible for the increase. Two
techniques can be used to evaluate this belief.
33. The lagged dependent variable is necessary for obtain­
ing stable coefficients in this model.




0.974
0.033
0.028
0.444
0.212
0.344

0.976
0.028
0.023
0.062
0.368
0.570

0.999
0.050
0.039
0.842
0.158
0.000

One is to determine how well the model esti­
mated with data from the old bankruptcy law
forecasts the new code PBFs. If the forecasts are
very inaccurate, especially if they are biased,
there is reason to believe that factors outside the
model are important determinants of PBFs.
This technique must be used w ith care, how­
ever. First, incorrect seasonal factors bias quar­
terly forecasts, although annual forecasts based
on quarterly forecasts should not contain this
source of error. Second, forecasting error may
bias estimates of the new code’s impact. That is,
comparisons of actual and forecast PBFs attri­
bute all forecasting error to the impact of the
new code.34 Confidence intervals around the
forecast values may be used to account for fore­
casting error when evaluating the impact of the
new code. Third, static forecasts with this model
may underestimate the impact of the new code.
For example, say the new code caused a one-time
increase in PBFs to a permanently higher rate.
With static forecasts, the lagged dependent vari34. Carter (1982) and Brimmer (1981) ignore this point and
thus may bias their conclusions in favor of the new bank­
ruptcy code having a large impact.

22

Economic Review □ Spring 1982

Table 5

Static Forecasts of Equation 5 in the N ew Bankruptcy Code Period

Quarter

Forecast
value

0.050 Confidence interval
Part A.

Forecast
error

Actual
value

LBKPOP

1979:IVQ
1980:IQ
1980:IIQ
1980:IIIQ
1980:IVQ

1.448
1.607
1.816
1.904
1.952

1.383
1.537
1.746
4.829
1.861

-

1.514
1.678
1.886
1.979
2.043

0.053
0.151
0.082
0.068
0.036

1.501
1.758
1.898
1.972
1.988

1981:IQ
1981:11Q
1981:IIIQ
1981 :IVQ

1.977
1.999
1.965
1.919

1.884
1.898
1.867
1.831

-

2.070
2.100
2.064
2.008

0.063
-0.016
0.019
0.054

2.040
1.983
1.985
1.973

- 68,596
- 81,763
- 100,680
- 110,870
- 118,310

3,512
12,309
7,972
7,217
3,930

67,680
87,896
101,530
109,850
112,030

122,400
125,740
122,220
116,490

7,223
-1,818
2,143
5,928

118,600
112,530
113,210
112,470

Part B.
1979:IVQ
1980:IQ
1980:IIQ
1980:IIIQ
1980:IVQ

64,168
75,587
93,555
102,630
108,100

59,741
69,411
86,433
94,397
97,892

1981:IQ
1981 :IIQ
1981:IIIQ
1981:1VQ

111,380
114,340
111,060
106,540

100,360
102,950
99,913
96,592

-

PBFs

Statistics for Part A:
Forecast mean
Actual mean
Correlation
RMSE

1.8432
1.8998
0.9742
0.0712

Theil U
Bias
Regression
Disturbance

0.037
0.632
0.111
0.257

Note: Discrepancies are due to rounding.

able feeds this increase, with declining weights,
into subsequent forecasts in a purely mechanical
way. After the first forecast quarter, static fore­
casts will underestimate that increase in PBFs
resulting from the new code. Dynamic forecasts,
however, do not suffer from this problem, because
they use previously forecast values, which do not
include any new code shift, for the values of the
lagged dependent variable. Of course, if the new
code had no impact on PBFs, then the two types of
forecasts should be similar. Finally, the occur­
rence of other events not captured by the model
but important for PBFs during the new code



period will obscure estimates of the fraction of
forecasting error stemming from the new code.
For example, if liquidity constraints tightened in
the new code period in ways not captured by the
model and increased PBFs, this technique could
not distinguish the forecasting errors arising
from the liquidity constraints from those arising
from the new code.
Tables 5 and 6 display the forecasting results
of equation 5 in the new code period. The
numbers in part A pertain to LBKPOP, and
those in part B are translations of the confidence
intervals and forecast values into corresponding

Federal Reserve Bank of Cleveland

Table 6

23

D ynam ic Forecasts of Equation 5 in the N ew Bankruptcy Code Period

Quarter

Forecast
value

0.050 Confidence interval

Forecast
error

Actual
value

LBKPOP

Part A.

1980:IIQ
1980:IIIQ
1980:IVQ

1.448
1.567
1.671
1.732
1.769

1.383
1.498
1.605
1.664
1.688

-- 1.514
-- 1.636
-- 1.737
-- 1.800
-- 1.850

0.0533
0.191
0.227
0.241
0.218

1.501
1.758
1.898
1.972
1.988

1981:IQ
1981:IIQ
1981:IIIQ
1981:IVQ

1.811
1.825
1.845
1.814

1.728
1.735
1.754
1.732

-- 1.895
-- 1.916
-- 1.937
-- 1.896

0.229
0.158
0.139
0.160

2.040
1.983
1.985
1.973

1979:IVQ
1980:IQ

Part B.

PBFs

1980:IIQ
1980:IIIQ
1980:1VQ

64,168
72,588
80,897
86,365
90,044

59,741
66,509
74,178
78,895
81,005

-

68,596
78,667
87,615
93,835
99,082

3,512
15,308
20,630
23,486
21,986

67,680
87,896
101,530
109,850
112,030

1981 :IQ
1981 :IIQ
1981:IIIQ
1981:IVQ

94,346
96,098
98,515
95,861

84,453
85,914
88,179
86,630

-

104,240
106,280
108,850
105,090

24,258
16,429
14,694
16,608

118,600
112,530
113,210
112,470

1979:IVQ
1980:IQ

Statistics for Part A:
Forecast mean
Actual mean
Correlation
RMSE

1.7202
1.8998
0.9486
0.1882

Theil U
Bias
Regression
Disturbance

0.099
0.911
0.017
0.073

Note: Discrepancies are due to rounding.

measures for PBFs.35 These results suggest
that there is an unexplained increase in PBFs
during the new code period. The static forecasts
miss the sharp increase in 1979:IVQ through
1980:IIQ; the 1980:IQ and 1980:IIQ static fore­
casts have the largest errors, and the confidence
intervals exclude their actual values. The dy­
35. The confidence intervals for LBKPOP are only approxi­
mate, because they ignore the complications arising from the
lagged dependent variable. The confidence intervals for PBFs
are first-order Taylor series expansions of the LBKPOP inter­
vals. The correct intervals in both cases would be wider.




namic forecasts also miss the initial increase,
and these errors throw the subsequent dynamic
forecasts “off-track,” inflating the Theil U and
RMSE statistics. The bias in the dynamic fore­
casts is quite clear, since every forecast error is
positive and every confidence interval after
1979:IVQ excludes its actual value. The bias and
the RMSE are much less for the static forecasts,
but this improvement seems to arise primarily
from the lagged dependent variable, which feeds
this unexplained increase into subsequent fore­
casts and hence lowers their forecast error.

24

Economic Review □ Spring 1982

T able 7

Dynam ic Forecasts of Equation 5 Beginning in 1980:IIIQ

Quarter

Forecast
value

Forecast
error

0.050 Confidence interval
Part A.

Actual
value

LBKPOP

1980:IIIQ
1980:IVQ

1.904
1.900

1.829 - 1.979
1.812 - 1.988

0.068
0.087

1.972
1.988

1981:IQ
1981 :IIQ
1981:IIIQ
1981 :IVQ

1.911
1.901
1.903
1.857

1.822
1.806
1.808
1.773

0.129
0.082
0.082
0.116

2.040
1.983
1.985
1.973

7,217
9,370

109,850
112,030

14,375
8,873
8,862
12,327

118,600
112,530
113,210
112,470

-

Part B.

2.000
1.996
1.998
1.942

PBFs

1980:IIIQ
1980:IVQ

102,630
102,660

94,397 - 110,870
92,807 - 112,510

1981:IQ
1981 :IIQ
1981:IIIQ
1981:IVQ

104,230
103,650
104,350
100,140

93,687
92,964
93,630
90,623

-

114,770
114,340
115,060
109,660

Statistics for Part A:
Forecast mean
Actual mean
Correlation
RMSE

1.8961
1.9901
0.4718
0.0964

Theil U
Bias
Regression
Disturbance

0.049
0.951
0.005
0.044

Note: Discrepancies are due to rounding.

Like the actual PBF increase, much of the
unexplained increase occurs by 1980:IIIQ. When
the dynamic forecasts begin in that quarter, as
shown in table 7, they are much better than the
dynamic nine-quarter forecasts. The RMSE falls
by almost one-half; the bias is much less in abso­
lute terms but a bit higher relative to the RMSE;
only two of six confidence intervals exclude
their actual values.
The explained increase in PBFs does not arise
from any one variable, but from the combined
influence of all the variables. Table 8 shows the
means and elasticities of the explanatory varia­
bles in the new code period. Comparing these
figures with those of table 2, the most obvious
differences are found in the figures for R T B ^nd



Table 8

Equation 5: N ew Code Period

1979:IVQ-1981:IVQ
Explanatory
variable

Mean

Elasticity
at mean

LBKPOP, j
CONSTANT
YLP,
YLT,
RTB,
R T A P C ,j
RDBTPC, j
RDEPPC, 1
NONDPAY, x

1.72023
1.0000
4.2136
-0.0930
12.6313
9.3853
4.6512
5.7745
0.6463

1.30703
-0.6154
-1.3399
0.0410
0.0835
1.0333
1.4456
-1.1520
0.9559

a. These figures are derived from the dynamic forecast.

Federal Reserve Bank of Cleveland

YLTt\
the mean of RTB^ in the new code period is
over twice its mean in the old law period, and
transitory income is negative on average in the
new code period. However, none of the means of
the remaining variables has changed sufficiently
to suggest that one or several variables have an
inordinate effect on the forecasts. The mean of
the dynamic forecast values of L B K P O P ^ also
increased in the new code period, but it arises
simply from the collective current and past
impacts of the income, interest rate, portfolio,
and nondiscretionary spending terms.
This is clear in figure 7, which plots the
impact of the lagged dependent variable, XLBK,



25

and the total impact of all of the other variables
but the constant term, TOT, on the predicted
LBKPOP values. These impacts are simply the
products of the actual values of the explanatory
variables and their coefficients from equation 5.
There are quarters when TOT has a larger
impact than XLBK, and others when XLBK has
the larger impact. In the new code period it
appears that XLBK, which is computed with the
dynamic forecasts of LBKPOP, has a much
larger impact relative to TOT, perhaps leading
some readers to criticize the importance of the
TOT variables in the new code period. Such
criticism is unfounded, however. First, TOT

26

Economic Review □ Spring 1982

assumes its largest values in the new code
period; that is, the financial pressures measured
by the TOT variables are the greatest that they
have been in at least 20 years. Thus, it is not
surprising that LBKPOP increased in the new
code period. Second, XLBK captures the past
effects of the TOT variables, as argued earlier.
Figure 7 clearly shows that changes in TOT
precede changes in XLBK. The increasing fi­
nancial pressures beginning in 1978 raise
LBKPOP and the subsequent XLBK values as
well, and the sustained large TOT values in the
new code period push up LBKPOP and XLBK
further.36 Thus, the explained increase in PBFs
is solely a function of current and past values of
income, interest rate, portfolio, and nondiscretionary payments terms.
Although an unexplained increase seems to
have occurred, the dynamic forecasts shown in
table 6 suggest this increase is not very large.
Using the confidence interval for 1981:IVQ, the
unexplained increase in PBFs may range from
13 percent, or 7,380 filings, to 47 percent, or
25,840 filings, of the actual increase of 54,973
PBFs over the nine quarters of the new code.
The predicted values imply the midpoint of 30
percent, or 16,609 filings. Other researchers
measure the unexplained increase differently.
Carter (1981) looks at the increase in PBFs
between statistical years 1979 and 1981 and
concludes that 72 percent of the increase is
unexplained, whereas the results in table 6 show
34 percent. Brimmer (1981) examines the first
five quarters of the new code period and argues
that between 28 percent and 32 percent of all the
PBFs over these five quarters are unexplained,
whereas the results in table 6 indicate 18 percent.
A second technique that can be used to study
the impact of the new code is to test hypotheses
36. Another way to see this is to view equation 5 as
LBK PO P,« TOT',+0.76 LBKPOP, lt where TOT',= TOT,
+ CONSTANT, or LBKPOP,« TOT', +0.76 TOT'M +0.58
TOT',_2 + 0.44 TOT',_3 +0.33 TOT',_4 +0.25 TOT',_5 + . . .,
obtained by repeated substitution for LBKPOP,_j. In the long
run, when TOT', is constant in every quarter, LBKPOP,
4.2 TOT',. Thus, when TOT' increases to a higher, sus­
tained level, as it did in the new code period, LBKPOP should
increase by a much larger amount to a higher, sustained
level, as it also appeared to do in the new code period.




about how it may have changed the empirical
model. One test is whether the coefficients esti­
mated with the old bankruptcy law data remain
unchanged when estimated with data from the
new code.37 The results of estimating the em­
pirical model with the full sample 1961:IQ
through 1981:IVQ are shown in equation 6 of
table 9. In comparing these coefficients with
those of equation 5, shown for convenience in
table 9, all of the coefficients in equation 6 are
larger in absolute value. That is, the high levels
of PBFs after 1979:IVQ forced all of the explana­
tory variables to “work harder” to explain PBFs.
The first-order serial correlation coefficient fell
by about one-half as the sharp increase in PBFs
immediately after the new code took effect broke
up the autocorrelation in the errors. The F-test
rejects the structural stability hypothesis at the
1 percent significance level; the F-statistic with
9 and 75 degrees of freedom is 4.29, greater than
the 1 percent point for an F distribution with 9
and 80 degrees of freedom equal to 2.64. That is,
there is a high probability that some factor or
factors in the new code period have changed the
coefficients as estimated in equation 5.
Based on these results, it would be useful to
learn how the model changed in the new code
period. Does the relationship between some or
all of the variables and PBFs change, or are there
additional variables that are now important for
explaining PBFs? With only nine quarters of
data available on the new code experience, few
hypotheses can be tested. A simple test is
whether the change is merely an intercept shift.
Two such tests are shown in equations 7 and 8 of
table 9. In equation 7, NEWCODE1 is a simple
dummy variable whose value is 1 throughout
the new code period and zero otherwise. In equa­
tion 8, NEWCODE2 has a zero value through
1979:IIIQ, increases sharply in the first few
quarters of the new code period, and increases

37. Rea (1978) is relevant again here. To avoid ambiguous
results, all relevant factors, except the new code, must be
included in the null hypothesis. Other factors not captured
by the model but important for PBFs in the new code period
will affect the outcome of the test and thus obscure the
estimated effect of the new code.

Federal Reserve Bank of Cleveland

Table 9

27

R egression R esu lts under the N ew Bankruptcy Code

Dependent variable is LBKPOP; standard errors are in parentheses
Equation
5

6

7

8

75
1961:IQ1979:IIIQ

84
1961 :IQ1981:IVQ

84
1961:IQ1981:IVQ

84
1961 :IQ1981:IVQ

0.7598
(0.0356)

0.7650
(0.0243)

0.6946
(0.0256)

0.6719
(0.0379)

CONSTANT

-0.6154
(0.2481)

-1.1601
(0.2815)

-0.6920
(0.2545)

-0.9125
(0.2774)

YLP,

-0.3180
(0.0530)

-0.3357
(0.0672)

-0.3512
(0.0556)

-0.3562
(0.0638)

YLT,

-0.4409
(0.0538)

-0.4935
(0.0665)

-0.4725
(0.0556)

-0.4936
(0.0627)

RTB/

0.0066
(0.0031)

0.0072
(0.0025)

0.0021
(0.0024)

0.0022
(0.0029)

rtapcm

0.1101
(0.0300)

0.1253
(0.0342)

0.1479
(0.0285)

0.1576
(0.0339)

rdbtpcm

0.3108
(0.0432)

0.3520
(0.0442)

0.3759
(0.0368)

0.4002
(0.0445)

RDEPPC m

-0.1995
(0.0427)

-0.2368
(0.0444)

-0.2640
(0.0371)

-0.2888
(0.0452)

nondpaym

1.4793
(0.3583)

2.2879
(0.4086)

1.5644
(0.3723)

1.9059
(0.4048)

Number of observations
Sample period
Explanatory variables
lbkpopm

0.1076
(0.0235)

NEWCODE1

0.1227
(0.0397)

NEWCODE2

Equation standard error
Adjusted R2
Durbin h
Serial correlation coefficient
Residual mean

0.0332
0.9857

-0.0110
-0.3360
0.0002

0.0970

0.0800

0.1300

-0.1468

-0.2640

-0.1566

0.0001

0.0001

0.0001

slowly later in the period.38 Both intercept
shifts have the correct sign and are statistically
significant at the 5 percent level, but the coeffi­
cients of CONSTANT, LBKPOPM , RTB,, and
N O N D P A Y ^ change considerably. The reason
for these changes is the reason why tests of the



0.0314
0.9874

0.0297
0.9907

0.0287
0.9659

38.

The values of NEW C0DE2 are computed with the for­

mula 1.0-EXP(-0.461 J), where /h a s value 1 in 1979:IVQ, 2
in 1980:IQ, and so on. The weight -0.461 was chosen so that
NEWCODE2 would be 0.99, or close to 1 after 10 quarters.
The first five values are 0.369,0.602,0.749,0.842, and 0.900;
NEWCODE2 has zero value before 1979:IVQ.

28

Economic Review □ Spring 1982

new code’s impact on the empirical model await
more data. Most of the explanatory variables
achieve their largest values late in the sample
period, when the new code was in effect. The
variables LBKPOPM , RTB„ and NONDPAYM
in particular achieve values much larger than
their previous values, and these large values are
quite highly correlated with the values of NEWCODE1 and NEWCODE2. Because the correla­
tion is positive, the coefficients on these three
variables are negatively correlated with those of
the intercept shifts. Thus, the coefficients on
these three variables fall from their values in
equation 6.
Another way of making the point is to say that
the particular combination of values for the
explanatory variables in the new code period is
unique to the period 1961:IQ to 1981:IVQ. These
values have very high leverage in determining
the coefficient estimates. If the PBF values are
thought to be unrelated to factors outside the
model, then these values add precision to the
coefficient estimates, and equation 6 is the
appropriate equation for the whole sample. Oth­
erwise, the coefficients in equation 6 are biased,
and the impact of the new code and/or other
factors needs to be explicitly incorporated.

IV.

Conclusion

The shape of consumer financial positions is
the key to understanding the behavior of aggre­
gate PBFs. Income provides the cash flow to
finance nondiscretionary spending, and the size
and composition of consumer portfolios help
determine nondiscretionary spending, the cush­
ion against unforeseen income loss and spend­
ing, and the vulnerability to liquidity constraints.
The level of interest rates is also important,
because it determines the cost of carrying and
refinancing debt. In the aggregate, these factors
are very powerful in explaining PBFs. Indeed,
these factors may explain about 70 percent of
the increase in PBFs in the new code period. The
remaining 30 percent may result from the impact
of the new code. Apart from the forecasting
error, the Consumer Credit Restraint Program,
effective from March 14, 1980, to July 3, 1980,



also may have influenced PBFs. The reduction
in the supply of consumer credit during these
months, or, in other words, the tightening of
liquidity constraints, may have forced some
financially distressed consumers to file for bank­
ruptcy.39 However, the impact of this program
on PBFs probably was small.
PBFs should have been expected to increase
under the new code, if only because the new
federal exemption levels are more consistent
with past inflation rates. Under the old bank­
ruptcy law, only state exemption levels were
available, and these were infrequently and im­
perfectly adjusted for inflation. Hence, real ex­
emption levels fell over time, possibly supressing the number of PBFs until the new code took
effect. Much of the unexplained increase in
PBFs may be just a natural reaction to an
inflation-adjusted new law. Assuming lawmak­
ers expected PBFs to increase for this reason,
the relevant question to answer is how much of
the increase in PBFs is an undesired result of the
new code?
Much of the recent increase in PBFs occurred
in the first three quarters of the new code period,
paralleling the sluggish growth in real GNP.
Since then, PBFs have grown more slowly and
actually have fallen; preliminary figures for
1982:IQ show PBFs falling further. The argu­
ment that the new code has a large impact on
PBFs would be supported by future PBFs re­
maining at very high rates. Arguments for
changing the new code would be severely under­
cut if PBFs declined to rates found in the old
bankruptcy law period. The future course of
PBFs will help decide this issue.
39. Cox (1980) argues that the Consumer Credit Restraint
Program reduced both the supply of and the demand for
consumer credit during these months.

References
Baily, Martin Neil. “Stabilization Policy and
Private Economic Behavior,” Brookings Pap­
ers on Economic Activity, 1:1978, pp. 11-50.

Federal Reserve Bank of Cleveland

Bankruptcy Laws of the United States. House of
Representatives, Washington: GPO, 1960.
Bankruptcy Reform Act of 1978. Title 11, U.S.
Code, Bankruptcy. 95 Cong. 2 Sess. 1978.
Brimmer, Andrew F. “Statement,” in Bank­
ruptcy Reform Act of 1978. Hearing. U.S.
Senate. Committee on the Judiciary. Subcom­
mittee on Courts. 97 Cong. 1 Sess. Wash­
ington: GPO, April 3, 1981.
Brunner, George Allen. “Personal Bankruptcies
in Ohio.” Ph.D. dissertation, Ohio State Uni­
versity, 1964.
Carter, Charlie. “The Surge in Bankruptcies: Is
the New Law Responsible?,” Economic Review,
Federal Reserve Bank of Atlanta, vol. 67, no. 1
January 1982), pp. 20-30.
Cox, Donald. “The March 14 Credit Controls,
Consumer Credit and Spending—Progess Re­
port.” Research Paper 8010. Federal Reserve
Bank of New York, November 1980.
Dolphin, Robert, Jr. “An Analysis of Economic
and Personal Factors Leading to Consumer
Bankruptcy.” Occasional Paper 15. Michigan
State University, Graduate School of Business
Administration, Bureau of Business and Eco­
nomic Research, 1965.
Fitzpatrick, Dennis B. “An Analysis of Limited
Aspects of the Past, Present and Future Opera­
tions of Commercial Bank Card Systems.” D.B.A.
dissertation, University of Colorado, 1973.
Haden, Harry H. “Chapter XIII Wage Earner
Plans—Forgotten Man Bankruptcy,” Kentucky
Law Journal, vol. 55, no. 3 (1967), pp. 564-617.
Herrmann, Robert O. “Causal Factors in Con­
sumer Bankruptcy: A Case Study.” Occasional
Paper 6. University of California, Davis, Insti­
tute of Governmental Affairs, December 1965.
King, Lawrence P. “Statement,” in Bankruptcy
Reform Act of 1978. Hearing. U.S. Senate.
Committee on the Judiciary. Subcommittee on
Courts. 97 Cong. 1 Sess. Washington: GPO,
April 3,1981.
Kowalewski, K.J. “Consumer Lending and the
Bankruptcy Reform Act of 1978,” Economic
Commentary, Federal Reserve Bank of Cleve­
land, January 12, 1981.



29

Luckett, Charles. “Recent Financial Behavior of
Households,” Federal Reserve Bulletin, vol. 66,
no. 6 Qune 1980), pp. 437-43.
Mathews, H. Lee. “Causes of Personal Bank­
ruptcies,” Bureau of Business Research Mono­
graph 133. Ohio State University, College of
Administrative Science, 1969.
Misbach, Grant L. “Personal Bankruptcy in the
United States and Utah.” M.B.A. thesis, Uni­
versity of Utah, 1964.
Pfeilsticker, Paul J. “Soaring Personal Bank­
ruptcies: The Reality of the New Act,” Journal
of Retail Banking, vol. 2, no. 3 (September
1980), pp. 7-15.
Rea, John D. “Indeterminacy of the Chow Test
when the Number of Observations Is Insuffi­
cient,” Econometrica, vol. 46 (January 1978),
p. 229.
Reed, Edward W. Personal Bankruptcies in
Oregon. Eugene, Ore.: University of Oregon
Press, 1967.
Sadd, Victor, and Robert T. Williams. “Causes
of Bankruptcies among Consumers.” Domes­
tic Commerce Series 82. U.S. Department of
Commerce, Bureau of Foreign and Domestic
Commerce. Washington: GPO, 1933.
Smith, Clifford W., Jr. “On the Theory of Finan­
cial Contracting: The Personal Loan Market,”
Journal of Monetary Economics, vol. 6, no. 3
(July 1980), pp. 333-57.
Stanley, David T., and Marjorie Girth. Bank­
ruptcy: Problem, Process, Reform. Washington:
Brookings Institution, 1971.
Stiglitz, Joseph E., and Andrew Weiss. “Credit
Rationing in Markets with Imperfect Informa­
tion,” American Economic Review, vol. 71
(June 1981), pp. 393-410.
U.S. Congress. Senate. Subcommittee on Courts,
Committee on the Judiciary. Bankruptcy Re­
form Act of 1978. Hearings. 97 Cong. 1 Sess.
Washington: GPO, 1981.
Vicker, Ray. “Demand for Credit Counseling
Rises as Personal Bankruptcy Rates Grow,”
Wall Street Journal, November 19, 1981.
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American Statistician, vol. 32, no. 2 (May
1978), pp. 66-68.

The Case for
Staggered-R eserve Accounting
by W illiam T. G avin
accounting proposal, was not warranted under
the old operating procedures. With the change in
operating procedures adopted on October 6,
1979, interest rates have become significantly
more volatile.3 Increased volatility and uncer­
tainty under the new operating procedures have
led the Morgan Guaranty Company (1981) to
reissue the call for staggered-reserve account­
ing. Under the Morgan Guaranty proposal, each
bank would have a four-week period for averag­
ing reserve holdings to meet its reserve require­
ments.4 All banks would be divided into four
groups, each with approximately one-quarter of
all deposits. The reserve-maintenance periods
would be staggered so that one group would
settle its reserve accounts each Wednesday.
The argument for this proposal is based on
two premises: (1) that short-run fluctuations in
the demand for money and reserves should be
accommodated by monetary policy and (2) that
monetary control mechanisms should be struc­
tured so that total reserves could be the operat­
ing target of monetary policy. Extensive research
based on the theoretical framework of Poole
(1970) supports the first premise. Brunner (1973)
uses his macroeconomic model with markets for
money, credit, and goods to extend Poole’s anal­
ysis. He concludes, as did Poole, that the central
bank should accommodate changes in the de­
mand for money. However, he argues that the

The fundamental role of the Federal Reserve
System is to ration the supply of money to the
economy. The Federal Reserve does this by
rationing the supply of reserves to the banking
system. Control of reserves implies control of
the money supply in our banking system, because
banks are required to hold reserves against the
deposits that are included in the money supply.
Since the 1920s the larger banks have been
required to settle their reserve accounts simul­
taneously on a weekly basis. This simultaneous
settling occurs each Wednesday and can lead to
hectic trading in the market for reserves on the
settling day.1
Eighteen years ago Cox and Leach (1964) pro­
posed an institutional reform that would lengthen
the reserve-accounting period from one week to
one month and stagger the reserve-accounting
periods among four groups of banks. The gen­
eral argument for their proposal was that it
would reduce volatility and uncertainty in shortrun financial markets. However, there was rela­
tively little short-run volatility in financial mar­
kets under the operating procedures and mone­
tary control mechanisms of the 1960s and 1970s.2
A major institutional change to prevent shortrun volatility, such as the staggered-reserve1. See Johnson (1981), p. 14. Between 1978 and 1980, the
average trading range for the federal funds rate, the interest
rate on reserves that banks lend to one another, was three to
ten times larger on Wednesdays than on other days.

3. For a detailed description of the new operating proce­
dure, see Stevens (1981).

2. Cox and Leach (1964) show that there is volatility or
“churning” in the market for government securities, but
they do not show that it causes volatility in interest rates.
Coats (1976) provides some evidence on volatility in the
federal funds rate before and after the 1968 changes in Regu­
lation D. Johnson (1981) provides evidence on interest-rate
volatility before and after the introduction of the new operat­
ing procedure in October 1979.




4. The term bank is used in a generic sense to include all
depository institutions subject to reserve requirements.

William T. Gavin is an economist with the Federal Reserve
Bank o f Cleveland. June Gates provided research assistance for
this article.

30

Federal Reserve Bank of Cleveland

volatility in financial markets stemming from
variation in money demand is a very short-run
transitory phenomenon. He goes on to argue that
other sources of instability in financial markets
are longer lasting and should not be accommo­
dated. The problem for the central bank is that it
has proven difficult, if not impossible, to identify
the sources of volatility in financial markets
while they are occurring.
To finesse this problem, some observers have
suggested that the central bank abandon mone­
tary targets in favor of interest-rate or credit
targets. Presumably, this would allow for flexi­
ble monetary growth in the short run but not in
the long run. The Morgan Guaranty proposal
offers another solution. This proposal would
create flexibility in the short run so that a given
total reserve path would support a wide range of
interest-rate and deposit paths. This flexibility
would dampen the interest-rate effects of shortrun variation in money demand.
The Morgan Guaranty proposal would pro­
vide two channels for handling short-run fluc­
tuations in financial markets. The first channel
is internal to each bank. Each bank could aver­
age reserves over four weeks. Under the current
week-long reserve-accounting periods, each bank
has its own “seasonal” pattern for holding
reserves within the week. This allows each bank
to accommodate offsetting day-to-day fluctua­
tions in reserves. Week-to-week variations are
smoothed by banks’ trading in the federal funds
market or borrowing from the Federal Reserve
at the discount window. Under the Morgan
Guaranty plan, each bank would accommodate
offsetting week-to-week fluctuations by choos­
ing its own “seasonal” pattern for holding
reserves within the month.
The second channel is external to the individ­
ual banks, but internal to the private banking
system. Staggering reserve-settlement days
among four groups of banks would allow settling
banks to trade reserves with nonsettling banks.
This trading would tend to accommodate offset­
ting week-to-week and month-to-month fluctua­
tions in reserves.
The staggered-reserve-accounting proposal is
also based on the premise that the Federal Re­



31

serve should retain close control over total
reserves. Any proposal that gives the Federal
Reserve close control over total reserves must
include a mechanism to prevent the “crunches”
that can occur when all banks have to settle
simultaneously.
Lack of control over total reserves in the past
may or may not be the reason why monetary
targets were missed so often in the 1970s. In any
event, there would be an advantage to targeting
total reserves, because the operating procedures
would be simplified. Under the current arrange­
ment, the stance of monetary policy depends on
uncertain estimates of interest rates, borrowed
reserves, and excess reserves. The financial
press is again monitoring and reporting “free
reserves” as an indicator of policy stance. The
actual stance of policy depends on nonborrowed
reserves, the discount rate, and the slope of the
borrowing function. The Federal Open Market
Committee sets the targets for money growth
and the initial borrowing assumption from which
the target for nonborrowed reserves is derived.
The Board of Governors decides on the discount
rate. There is no evidence that these separate
decisionmaking processes impede the formula­
tion and implementation of policy, but the ar­
rangement does little to enhance the public’s
understanding of policy.
The advantages of the Morgan Guaranty
proposal are that it would lengthen the reserve-accounting period from one week to four
weeks, and it would allow the adoption of total
reserves as the operating target for monetary
policy. Going to a four-week reserve-accounting
period would mute the impact on reserve
markets of unpredictable week-to-week varia­
tion in the money stock. Adopting total re­
serves as an operating target would simplify
the operating procedure.

I.

Length of the Settlement Period

There are theoretical grounds for making the
length of the reserve-settlement period coinci­
dent with the average payment cycle. Consider
one household that is paid biweekly, with income

32

Economic Review □ Spring 1982

deposited in a transactions account on the first
day of the payment period. Suppose the demanddeposit balance falls in a random way through­
out the period until it reaches zero on the last
day. For this example, also assume that there is
no currency. If the economy were made up of
households identical to this one, where all firms
had sophisticated cash-management programs
but households did not, then a one-week aggre­
gate measuring of the money stock generally
would overstate the average money stock in the
first week and understate it in the second. If the
central bank were to set weekly targets for the
money supply, seasonal adjustment would be
necessary to supply a target amount of total
reserves in a biweekly cycle that duplicated the
average payment cycle.
If the weekly seasonal factors were predicta­
ble, there would be no problem. But, if the sea­
sonal factors changed in an unpredictable way,
then institutions would be induced to interme­
diate the repeated discrepancies between the
demand for reserves, derived from the deposit
cycle, and the supply of reserves, implied by the
“targeting” procedures. If this intermediation is
not costless, then whether the central bank
should adopt weekly reserve maintenance when
the average payment cycle is longer than a week
depends on how accurately the weekly seasonaladjustment factors can be predicted.
As this simple example suggests, it is impor­
tant for short-frequency seasonal-adjustment
factors to be predictable when the reserveaccounting period is shorter than the average
payment cycle and total reserve targeting is
practiced. If the seasonal factors are in error, the
Federal Reserve would force markets to adjust
to an incorrect supply of reserves. One way to
avoid the possibility of “targeting” errors is to
lengthen the reserve-accounting period to the
minimum predictable average payment cycle.
How long is the minimum predictable average
payment cycle? Cox and Leach (1964) and the
Morgan Guaranty proposal suggest four weeks.
The pattern of the seasonal factors for 1981
indicates that payment cycles are interwoven at
all measured frequencies—weekly, monthly,
quarterly, and annually. Recent evidence sug­



gests that the cycle in the weekly interval is
much more difficult to predict than the cycles in
monthly or longer intervals.5 Pierce (1981) dis­
cusses the problems posed by the weekly moneysupply data. The problems are reflected in the
relative absence of weekly money-market mod­
els. Carlson (1982) discusses the importance of
using models to predict movements in the money
supply. He concludes that there is a good chance
that existing models of monthly seasonal factors
may be improved in the near future. However,
our confidence in weekly models is still quite
limited. In a letter to Senators Jake Garn and
William Proxmire, Federal Reserve Chairman
Paul Volcker (1981) wrote:
There is nearly unanimous agreement by all
observers that weekly money statistics are ex­
tremely erratic and therefore poor indicators of
underlying trends. While monthly data can often
deviate considerably from such trends, the weekly
observations are particularly “noisy.” Week-toweek changes are quite large and recent esti­
mates indicate that the “noise” element—attrib­
utable to the random nature of money flows and
difficulties in seasonal adjustment—accounts for
plus or minus $3.3 billion in weekly change twothirds of the time. Such a large erratic element
appears intrinsic to money behavior, rather than
implying poor underlying statistics.

This uncertainty in the weekly data generates
uncertainty in the reserve-target paths, because
they are based on weekly seasonal factors for the
money supply.
The dollar size of unexpected variation in the
money supply is about the same for monthly as
for weekly data. If one assumes that the adjust­
ment costs to the banking system are propor­
tional to the unexpected variation in the money
supply over the settlement period and to the
number of settlement days, then the Morgan
Guaranty plan would reduce these adjustment
costs by 75 percent.
5. See also Seasonal A djustm ent o f the Monetary Aggregates,
Report of the Committee of Experts on Seasonal Adjustment
Techniques (Board of Governors of the Federal Reserve Sys­
tem, 1981).

Federal Reserve Bank of Cleveland

Another consideration is relevant to choos­
ing the appropriate length of the accounting
period. The period chosen should be consistent
with the timeframe appropriate for close mone­
tary control. A wide range of research within
the Federal Reserve System clearly suggests
that money control w ithin very short periods
of time, such as one week, is pointless for both
operational and theoretical reasons.6 There
are many issues involved in selecting an ap­
propriate temporal framework for monetary
control. Nevertheless, there is neither support
nor sentiment for close control of the money
supply w ithin a period shorter than one
month.7 While there still would be a chance
of “targeting” errors if reserves were con­
trolled on a monthly basis, the errors probably
would be much smaller than with a weekly
control period; empirical evidence gives us
more confidence in the stability of monthly
seasonal factors than weekly factors.
Two obstacles stand in the way of moving to a
monthly reserve-accounting period. One is the
desire to update information weekly. Yet, there
is no reason why weekly reporting could not be
maintained with monthly reserve accounting.
The other is a concern that the banking system
as a whole would accumulate larger aggregate
errors if the reserve-accounting period were
lengthened. This may be true, because markets
process and disseminate information when they
clear. In a sense, the reserve market clears only
on settlement day. Between settlement days the
federal funds rate is determined by expectations
about future interest rates, especially expecta­
tions about the federal funds rate on the next
settlement day. The individual bank learns
about aggregate behavior on settlement day.
6. For example, see Axilrod and Lindsey (1981), p. 248, and
the papers by Lindsey et al. and by Pierce in New Monetary
Control Procedures—Volume II. Karl Brunner (1973) argues
that the appropriate timeframe for targeting the money
supply exceeds one month (pp. 530-31).
7. There are exceptions, of course. First, some are willing
to make radical institutional changes such as suggested by
Laurent (1981). Second, others, such as Balbach (1981), see
the need for close week-to-week control as a method of get­
ting longer-run control.




33

Larger errors associated with a longer time
between settlement days would require larger
interest-rate variations to correct the errors
and/or less precise control over total reserves.
Staggering reserve-maintenance periods as
suggested in the Morgan Guaranty proposal
would mitigate these problems, because onefourth of all banks would settle each week. All
banks would learn of accumulating aggregate
errors on settlement days. Nonsettling banks
would have time to adjust their reserve positions
before their own settlement days.

II.

Simplifying the Operating Procedures

Under the current operating procedures, the
discount window is an important and necessary
link in the transmission of monetary policy from
nonborrowed-reserve operating targets to the
money-supply targets. The discount window is
necessary because required reserves today are
held against deposits of two weeks earlier. The
short-run path of the money supply is deter­
mined by the public’s demand for currency and
deposits. The money supply is controlled indi­
rectly by controlling nonborrowed reserves.
Reserves to support deviations of the money
supply from target must be borrowed at the
discount window. Because the Federal Reserve
district banks use administrative pressure to
prevent banks from borrowing too frequently,
short-term interest rates tend to rise when
borrowing rises and to fall when borrowing
falls. One implication of this procedure is that
nonborrowed reserves normally should be main­
tained below required reserves. Otherwise, bor­
rowing and the federal funds rate could fall to
zero when the money supply goes below the
target path, as it did briefly in 1980 and for a
longer period in 1981.
One source of slippage in this procedure is the
uncertain relationship between the amount of
borrowing today and the change in the money
supply in the future. If the money supply goes
above the target path, borrowing and interest
rates will rise, but there is considerable shortrun variation in the reaction of the public to the
higher interest rates. The money supply usually

34

Economic Review □ Spring 1982

comes down in the weeks following the higher
interest rates, but the response is delayed and
variable. These deviations of the money supply
from target are viewed as a problem by some
market participants today. Since the mid-1970s
many deviations were above target and were not
readily corrected; when they occurred at the end
of a targeting period, they were incorporated
into the level of the money supply from which
succeeding targets were calculated.8
To prevent this upward drift in the money
supply, many observers have called for a change
in operating targets from nonborrowed reserves
to total reserves. If total reserves were con­
trolled at a target level, then the money supply
could not drift off target over time. The Federal
Reserve has proposed a change in reserveaccounting rules that would permit more con­
trol of total reserves.9 Jones (1981) suggests
that targeting total reserves under this pro­
posal might increase the volatility of interest
rates and uncertainty in short-term financial
markets. This increased volatility in short­
term markets might not be too high a price to
pay for closer control of total reserves. How­
ever, proponents of staggered-reserve account­
ing argue that it is an unnecessary price to pay.
W ith staggered-reserve accounting the Federal
Reserve could use total reserves as its operat­
ing target without requiring perfectly contem­
poraneous reserve-maintenance periods.
To analyze the effect that staggering reserve
periods would have on the impact of monetary
policy, it is important to identify which impacts
are desired and which are not. It is likely that the
short-term securities market would not be as
responsive to monetary policy as it is in a non­
staggered regime; yet, the reaction to policy in
the short-term securities market today may not
be optimal, given the high cost to banks of
adjusting assets other than short-term securi­
ties on short notice. The impact of monetary

8. Poole (1976) predicted the inflationary consequences of
incorporating this “base drift” in setting annual targets.
9.

For a description of this proposal, see Federal Reserve

Bulletin, November 1981, pp. 856-57.



policy on bank lending would not necessarily be
delayed under a staggered-reserve regime.
To understand why this is so, imagine that
each bank seeks a fairly stable ratio of short­
term securities to loans and that it is more costly
for a bank to change its lending plans within a
few days than for it to change its holdings of
securities. Today, with small carryover privi­
leges and limited access to the discount window,
a shortage of reserves in the aggregate encour­
ages banks to sell short-term securities to the
nonbank public. This causes yields on securities
to rise, inducing nonbanks to shift from money
to securities and inducing banks to increase
their use of the discount window. In following
periods, banks reduce loans and buy back some
of the securities. Staggered settlement days
would allow banks to adjust a wider range of
assets, reducing the need for some of the trading
in short-term securities. Persistent excess de­
mand for reserves over a few weeks would cause
interest rates to rise, but yields on securities
would not have to rise relative to yields on loans.
Achieving immediate control of total reserves
could be associated with reduced turnover in
securities markets and associated interest-rate
movements. As this simple example suggests,
the impact of monetary policy on loan markets
and the money stock could be achieved with less
“churning” by banks in security markets if
reserve-maintenance periods were staggered
among banks.
Staggering reserve-maintenance periods would
perform much the same role that the discount
window serves today in moderating short-run
volatility of interest rates in securities markets.
But, staggered settlement days would allow the
Federal Reserve to end most adjustment lending
at the discount window and gain more precise
control of total reserves. Only if a bank had
special problems that prevented access to the
inter-bank market would the Federal Reserve
still have to be the source of reserve-adjustment
credit. Seasonal and extended credit facilities
would not have to change in any way. With
staggered reserves, however, the reserve-target­
ing process would no longer be complicated by
an erratic short-run linkage between changes in

Federal Reserve Bank of Cleveland
borrowed reserves, money market interest rates,
and money growth. Removing the discount win­
dow from the control mechanism would still
allow the Federal Reserve to set attainable
targets for total reserves. Attaining perfect con­
trol over total reserves under staggered-reserve
accounting would not give perfect control over
money-supply growth. But, deviations of the
money supply from target automatically would
cause interest rates to adjust in a way that
would encourage banks to supply and the public
to demand the targeted amount of money.

III.
Dynamic Stability and
Staggered-Reserve Accounting
Laufenberg (1975) first noted that the insti­
tutional structure of the staggered-reserveaccounting regime implied the possibility of dy­
namic instabilities. Lindsey (1981) suggests that
such instabilities are a property of staggered
accounting per se. Trepeta and Lindsey (1979)
present a model in which a disturbance to de­
posits with no change in total reserves sets in
motion an undamped cycle in which deposits
oscillate above and below the equilibrium level
implied by the total reserve target. This seems
improbable, however; a cycle in deposits would
tend to induce a cycle in the federal-funds rate
and imply a profit opportunity that banks could
easily exploit. Moreover, Bagshaw and Gavin
(1982) show that, even if banks ignored this
profit opportunity, the dynamic instability de­
scribed in the Laufenberg and the TrepetaLindsey papers is peculiar to a model with just
two banking groups. When the model is extended
to include more than two groups, the dynamic
instability disappears, although damped cycles
are still present.

IV.

Conclusion

The Morgan Guaranty proposal would lengthen
the reserve-accounting period to four weeks and
stagger settlement days among four groups of
banks. Lengthening the reserve-settlement
period would make it more consistent with a
timeframe that is considered appropriate for
measuring and controlling the money supply.



35

The adoption of a reserve-targeting operating
procedure in October 1979 created a new envi­
ronment for the financial community. Weekly
variations in the money stock and the demand
for reserves impose costs in financial markets
that did not exist under the old operating proce­
dure. Staggering settlement days provides a new
way of handling these short-run variations in
money demand. Lengthening the reserve-maintenance period to four weeks alleviates some of
the costs associated with these variations by
reducing the frequency of reserve adjustment
for each bank.
Adoption of staggered-reserve accounting
would allow the Federal Reserve to set operating
targets for total reserves. The operating proce­
dure would be simplified. This institutional
structure has the advantage of allowing market
participants to determine the short-run path for
the money supply and interest rates. At the
same time, the Federal Reserve could maintain
total reserves on a path consistent with its longrun monetary objectives.

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36

Economic Review □ Spring 1982

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