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Ma
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^ Economic
Issil Review
F E D E R A L R E S E R V E B A N K O F ATLANTA
J U L Y / A U G U S T 1988
Economic
Review
President
Robert P. Forrestal
Senior Vice President and
Director of Research
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Vice President and
Associate Director of Research
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Financial
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I S S N 0732-1813
V O L U M E LXXI11, N O . 4, J U L Y / A U G U S T 1988, E C O N O M I C
REVIEW
2
The U.S. Dollar
and the "Delayed J-Curve"
Jeffrey A Rosensweig a n d Paul D. Koch
16
Past and Current Trends
in Retirement: American Men
from 1860 to 1980
Jon R. Moen
Surprisingly, downturns in the dollar's
value affect the U.S. balance of foreign
trade only after a delay, a finding at
odds with the standard I-curve that
depicts projected trade balance response to currency depreciation.
During the 1980s, a greater percentage
of men over 65 are retiring than at any
previous time in U.S. history; this article
explores the causes and consequences
of this phenomenon.
28
F.Y.I.
Larry D. Wall
Commercial Bank Profitability:
Still Weak in 1987
43
Book Review
Hard Heads, Soft Hearts
Mary Susan Rosenbaum
by Alan S. Blinder
48
Statistical Pages
Finance, Employment, Construction, General
I FEDERAL R E S E R V E BANK O F ATLANTA 3
The U.S. Dollar and
the "Delayed J-Curve"
Jeffrey A. Rosensweig and Paul D. Koch
Downward movements in the dollar affect the four basic elements of the trade balance—import
import volume, and export volume—but
prices, export prices,
import prices and volumes respond more slowly than portrayed in
standard
J-curve theory. The authors analyze this departure from expectations and suggest that the United States presents
a unique case of delayed trade balance response to currency
In February 1985, after more than four years of
gains, the dollar exchange rate reached a peak
against major indexes of foreign currencies. The
dollar's subsequent steady fall since early 1985
bred optimism that the U.S. balance of trade
deficit, which to the concern of many had risen
to record levels, would begin to shrink. Most
analysts of the international economy anticipated that the turn would not come immediately, however. Past experience had shown that
The authors
nance,
are, respectively,
Emory
Professor
University
of Finance,
project
began
Reserve
Bank
while
University
Professor
School,
worked
as international
visiting scholar, respectively.
Reserve
System.
wish to thank B. Frank King, Vice President
contributions
Reserve
to this
of Fi-
Associate
on this
Federal
economist
These views are the
Director of Research at the Federal
2
at the
reflect those of the Federal
Bank of Atlanta or the Federal
for his substantial
and
of Kansas. Research
the authors
of Atlanta
and do not necessarily
Assistant
Business
and
authors'
Reserve
The authors
and
Associate
Bank of Atlanta,
article.
depreciation.
exchange rate depreciation was linked to an
improved balance of trade only after a lag.
Indeed, evidence from past episodes indicates
that currency depreciation is typically followed
immediately by deterioration
in the trade
balance; only after a time does the trade balance improve.
Though a lag between the dollar's peak and
improvement in the trade deficit is generally
expected, the extent of this lag in the period
since 1985 has surprised most analysts. The
dollar's highest level in early 1985 preceded the
largest subsequent monthly (and quarterly)
balance of trade deficit by more than two-and-ahalf years, and the deficit has yet to retreat to its
smaller levels of early 1985. As Chart 1 shows,
the quarterly nominal trade balance as measured by net merchandise exports in the GNP
accounts reached its most recent nadir (that is,
the trade deficit peaked) in the fourth quarter of
1987. The monthly nominal merchandise trade
deficit reached its highest level most recently in
ECONOMIC REVIEW. JULY/AUGUST 1988 J
October 1987 and has since been improving
sporadically.
This surprisingly belated downturn in the
nominal U.S. trade deficit after the dollar's
massive, persistent decline from its February
1985 peak has sparked renewed interest in the
individual response to exchange rate movements of the components of the balance of
trade: import and export prices and volumes.
In an attempt to explain the long lag, analysts
have been reviewing two related strands of
economic thought The primary line of thinkingtermed here the ¡-curve strand—focuses on the
overall response of nominal trade balances to
the dollar.1 The other line of thinking concentrates on the "pass-through" of exchange rate
movements into import prices. This pass-through
refers to the channels through which currency
valuation changes progress to be reflected in
import prices.
The delayed nominal trade balance response
can be understood more fully by uniting these
FEDERAL R E S E R V E BANK OF ATLANTA
two strands of economic thought and specifying
the dynamic links running from the dollar to the
prices and volumes of U.S. imports and exports.
In pursuit of such an understanding, this article
presents a simple framework that relates the
overall effect of the dollar on the U.S. trade
balance to four specific exchange rate relationships and their respective time paths. This focus
allows tests of how well, in the flexible exchange rate era since March 1973, U.S. experience supports a J-curve explanation. This
approach also allows a pinpointing of the specific links where the J-curve pattern breaks
down, if it does.
An analysis of the post-1973 experience shows
a slow and weak pass-through of dollar movements into U.S. import prices. This pass-through
weakness helps to explain the belated turnaround in the trade balance of the United States
since 1985. Reasons for this weakness are discussed later in this article.2 First, though, the trade
balance and the J-curve should be studied.
3
Chart 1.
The Dollar and Nominal Net Merchandise Exports
Federal Reserve
Dollar Index
(March 1973 = 100)
(Quarterly Data, 1982-88)
Nominal Net
Merchandise Exports
(Billions of U.S. Dollars)
Nominal Net Merchandise Exports
tr
C
O
C
O
Q
><
•
E
C
O
3
o
30o-
®
-30-60 -90-120
-150
-180
1982
1983
1984
1985
1986
1987
Sources: The Board of Governors of the Federal Reserve System and the U.S. Department of Commerce.
A Framework for Analyzing
How the Trade Balance Evolves
The J-curve is a stylized way of sketching the
evolution of the nominal trade balance after a
depreciation or devaluation of a currency. As its
name implies, the J-curve represents a balance
that initially falls sharply, remains temporarily
low, gradually begins to improve, and ultimately
rises above its previous level as time passes. To
identify the time path of changes underlying the
J-curve, this research divides the trade balance
into four parts, which are related in the following
equation:
NX ~ {Px * X) - {Pm * M)
where NX is net merchandise exports (that is,
the balance of trade) in current prices; Px and
4
Pm are, respectively, the average price indexes
of exports and imports; and X and Mare, respectively, the total volume of exports and imports.
The term enclosed in the equation's first parenthesis (Px * X) represents nominal exports; the
term in the second parenthesis (Pm * M) is
nominal
imports.
W h e n NX is negative, the
balance of trade in the United States is at a
deficit.
In standard J-curve theory, each of the four
elements of the balance of trade responds over
its own time path to exchange rate fluctuations.
Together these changes produce the overall
trade balance's reaction to the exchange rate.
The standard J-curve explanation argues that—
initially—only Pm, import prices, will change
early as lower dollar exchange rates directly
increase import prices; hence, in the absence of
changes in import and export volumes, total
ECONOMIC REVIEW, )ULY/AUGUST 1988
payout for imports will increase and the trade
balance will deteriorate. Export prices in dollar
terms would not b e expected to change in the
short run but might rise slightly in the longer run
either as U.S. producers pass on the increased
costs of imported intermediate inputs by raising their prices or as rising export d e m a n d
pushes U.S. producers toward capacity constraints. Generally, however, dollar export prices
are expected to remain more or less stable.
Changes in import and exportvolumes.Mand
X, are expected to occur later, as purchasers
react to the dollar's depreciation by eventually
finding new sources of products. In response to
rising import prices, import volumes, M, would
be expected to decline eventually. This reaction
would help to counteract the early impact of
import price increases and push the balance of
trade toward improvement Export volumes, X,
would be expected to increase as foreigners
face lower prices in their own currencies for
dollar-priced goods from t h e United States.
This effect, too, would tend to improve the U.S.
balance of trade.
Combined, these four sets of reactions suggest the J-curve shape for the reaction over time
of the balance of trade to a currency depreciation (see Chart 2). The trade balance's short-run
decline is accounted for by a quick rise in import
prices but with little other change. The trade
balance's later improvement occurs when falling import volume and rising export volume
offset higher import prices. If the responses of
trade volumes are sufficient, the rising section
of the J-curve will move above its level at the
time of the currency depreciation. That is, the
trade balance will recover and surpass its level
when the currency began depreciating.
While seemingly a reasonable series of events,
these reactions represent only one of many
possible scenarios. Each element of the expected relationship imposes some strict assumptions about the level, pattern, and time path of
balance-of-trade reactions. The failure to appear of one or more of the four basic patterns
could lead to many different time patterns of
trade balance response to the exchange rate.
Importantly, the pricing behavior consistent
with the J-curve is seemingly based on somewhat extreme assumptions. Export prices will
remain flat in dollar terms only if U.S. supply is
perfectly elastic or foreign demand perfectly
I FEDERAL
Digitized for R E S E R V E BANK OF ATLANTA
FRASER
7
Merchandise
Trade
Balance
Dollars
Chart 2.
The Standard J-Curve
r
t=0
t=1
•-time
t=0 time of initial currency depreciation.
t=1 time at which net export balance begins to
improve.
inelastic. The J-curve volume assumptions imply
that demand is ultimately not inelastic; therefore, export supply must be totally elastic.
The same elasticity assumptions implicitly
underlie the import side of a J-curve theory.
However, the recent literature on the market
structure of traded goods industries casts doubt
on any notion of perfectly elastic supply. 3 Thus,
each of the expected individual elements could
fail to develop for a variety of reasons, suggesting a multitude of alternative patterns of trade
balance evolution, each with its own issues and
problems. Only one of these patterns renders
the classic J-curve.
Tests of the
Basic Trade Balance Elements
T h e four e l e m e n t s of t h e trade b a l a n c e import prices, export prices, import volume,
and export volume—provide the focus for this
paper. Using a statistical technique called time
series analysis, this research identifies the
nature and extent of the dynamic relationships
between changes over time in the dollar's value
and elements of the nominal balance of trade.
Rather than studying the values of coefficients
of a prespecified dynamic structure, this research concentrates on the precise timing and
direction of the relationships, because recent
economic developments suggest that some of
the generally expected relationships consistent
with the standard J-curve may have broken
down. The results of the research should cause
economists to reconsider some particular assumptions implicit in J-curve-type behavior.
The following assumptions about the time
path of reactions to a dollar depreciation underlie the standard J-curve: When the dollar falls,
•
Import prices rise immediately. Their strongest rise occurs early, and they continue to rise
with successively less strength for several
months. Standard theory argues that the
relationship is strong and negative, running
only from the exchange rate to import prices.
•
Export prices remain stable. Any response
that might appear will be late, weak, and perhaps negative.
•
•
Import volumes begin to decline some months,
perhaps a year, after the exchange rate
change and continue to decline for many
months thereafter. The relationship is expected to be strong and positive, and to run
only from the exchange rate to import volumes.
Export volumes begin to increase some
months, perhaps a year, after the exchange
rate decline and continue to increase for
several months thereafter. The relationship
is expected to be strong and negative, and to
run only from the exchange rate to export volumes.
This research examines the four relationships
between the dollar and the different components involved in trade balance adjustments.
To acknowledge possible relationships in the
opposite direction to those expected, models
that link the dollar to current and past changes
in each of the four components of the trade
balance are also tested.
Since the tests allow focusing on the exchange rate-trade balance component relationships, this study can analyze monthly data.
Quarterly data, such as GNP statistics, are not
6
needed. The data are not seasonally-adjusted,
since seasonal adjustment effectively takes
place within the time series models. The use of
monthly data provides a double advantage:
having both a large number of observations and
data drawn solely from the floating exchange
rate regime.
The sample period chosen spans April 1973
through December 1986. The period was cut off
after 1986 so that only revised data would be
included. The April 1973 starting date coincides
with the beginning of the floating rate era. Previous studies, though, have mixed quarterly
data from both fixed and floating rate eras.4
The time series techniques employed here
are discussed in the accompanying box as well'
as in Paul D. Koch, Jeffrey A Rosensweig, and
Joseph A. Whitt, Jr.'s (1986,1988) studies, and are
explained in detail in Koch and Rosensweig
(1988). In essence, these present techniques
allow analysis of two aspects of the exchange
rate's relationship with the balance of trade
elements: (1) whether the exchange rate and
each trade balance element are independent
over time and (2) the direction and nature of
their temporal relationship, if any.
'
t
5
Empirical Results
Cross-Correlation Functions. The temporal
relationships between the dollar exchange rate
and the four balance-of-trade elements are
depicted graphically in Charts 3 through 6.
(Results of formal tests of independence | KochYang tests] are found in Table 1 in the box.) Each
chart shows a cross-correlation function (CCF).
These CCFs summarize the timing, size, and
direction of the dollar's relationship with a trade
balance component. Each chart shows a time
line of months running horizontally. Vertical
bars measure the relationship between the
exchange rate and a component of the trade
balance at a time before or after an exchange
rate change. The 0 month in the center of the
chart shows a contemporaneous relationship.
Positive months—to the right of the 0 monthshow lags of the component behind the exchange rate movement. Negative months—to
the left of the 0 month—show leads of the components before the dollar. The lagged relationECONOMIC REVIEW. JULY/AUGUST 1988
V
jj
J
ships are computed for 48 months before and
after the dollar change. Dotted lines parallel to
the horizontal axis show 95 percent confidence
intervals. Vertical bars that extend beyond
these dotted lines represent statistically significant relationships. Shaded areas suggest, in a
rough manner, the relationships implied by
standard J-curve theory.
Contrary to typical J-curve expectations but
consistent with arguments in some earlier research, the cross-correlation graph in Chart 3
shows little relationship between the dollar and
import prices. The coefficients for each month
are generally quite small and display no distinct
pattern, appearing to be randomly distributed
about zero. No evidence is available to indicate
an immediate rise in import prices after a dollar
decline. A few coefficients approach the 95 percent confidence interval about zero. Coefficients representing lags of 13 and 18 months
after the dollar change are the only notably large
coefficients in the entire function. As expected,
these coefficients are negative, perhaps suggesting that a decline in the dollar is followed by
a rise in import prices that is delayed between
12 and 18 months.
The picture in Chart 4 is roughly consistent
with the export price pattern of response implied by standard J-curve theory. Little evidence
of a dynamic relationship between the dollar
and export prices is present. A few large coefficients show export prices leading the dollar,
but the lack of a distinct pattern suggests no
substantive relationship. In the other direction,
the coefficients are extremely small in magnitude, although a pattern is weakly suggested as
they are mostly negative.
The cross-correlation results in Chart 5 display at best a very weak and delayed response
of import volumes to dollar movement. Research performed by the authors could not
reject the hypothesis that the dollar and import
volumes move independently. The CCF shows a
series of rather weak shrinking import volume
effects beginning some 20 months after a dollar
decline. These results are consistent with the
above finding of a weak and delayed response
of import prices.
The cross-correlation function picturing the
relationship between the dollar and export
volume appears in Chart 6 and produces strong
evidence of the expected negative relationship
I FEDERAL R E S E R V E
BANK OF ATLANTA
between the dollar and export volume. At lags of
12 through 24 months after an exchange rate
change, a string of several large (negative) coefficients appears, indicating that a decline in the
dollar strengthens export volume from a year to
up to 24 months later. Two large positive coefficients linking dollar movements to previous
export volumes appear after a long delay (at lags
-23 and -39 months). These may be spurious, or
may reflect modest support for a weak relationship from export volume to the dollar after two
or more years.
Granger Test Results. Statistical tests introduced by C.W.J. Granger (1969) were performed
to investigate further the "direction" of the
lead/lag relationship suggested by the time
series independence tests and cross-correlation
functions. These tests determine whether each
variable in a bivariate relationship—such as the
dollar exchange rate and import prices—can be
more accurately predicted using past values of
both variables rather than using only past values
of each variable by itself. Granger tests are more
powerful under certain conditions which are sufficiently met at times in this analysis; test results
for the four elemental relationships appear in
Table 2 in the box at the end of this article.
In contrast to the tests of independence associated with the CCFs, Granger tests suggest that
the dollar leads to subsequent movements in
import prices, but that import prices do not lead
the dollar. This finding may appear inconsistent
with the failure of the independence test to reject
the hypothesis of no relationship between these
two variables. However, while the cross-correlation
function in Chart 3 comprises mostly small coefficients following no distinct pattern, the two large
coefficients at lags of 13 and 18 months suggest
that a decline in the dollar is followed by an
increase in import prices between one to oneand-a-half years later. For dynamic relationships characterized by one or two large distributed lag coefficients, regression tests such
as Granger's have been shown to be more
powerful than time series tests (John Geweke,
1981; Koch and S.S. Yang, 1986), lending more
credence to the relationship suggested by the
Granger tests in this case. Of particular interest here, however, is the delay before import
prices are substantively impacted, which is a crucial departure from the standard J-curve's assumed pattern of quick pass-through response.
7
Chart 3.
Cross-Correlation Function between the Dollar's Value and Import Prices
| |I I IM Ii I| II II Ii Ii II I| II II II II II I| II II II II II I| II II I I II II I| II II II II II I| II II II II II I| II II II II II | II !I II II II I| M M I II I| I I I I I || Ii |[ II IM || II II II M I || II II I I II II || II II II II II || II Ii ! !i
M I
I
I
|
I
!
48
-42
-36
-30
-24
-18
-12
-6
0
6
12
18
24
30
36
42
i |
48
Chart 4.
Cross-Correlation Function between the Dollar's Value and Export Prices
I
1111111 111 M l 111 M | i 11 111111111 1111 11111 i 1111
48
-42
-36
-30
-24
-18
-12
-6
I
I I I
[ i l l I I | I I I I I | I I
0
6
12
l l I
| M
18
l l
l | i
24
l l I I
| i M
30
i i | i i i i
36
i | i i i
42
i i |
48
Chart 5.
Cross-Correlation Function between the Dollar's Value and Import Volume
48
-42
-36
-30
24
30
Chart 6.
Cross-Correlation Function between the Dollar's Value and Export Volume
36
42
48
The Granger tests, like the earlier independence tests, produce no solid evidence supporting a substantive relationship between the dollar
and export prices. These results are consistent
with a standard J-curve scenario.
For the relationship between the dollar and
import volume, Granger test results suggest
only that import volume leads the dollar. These
results support the information provided by the
independence test in Table 1 in the box and the
cross-correlation function in Chart 5, indicating
that an increase in import volume is followed by
small declines in the dollar over a long distributed lag. Any impact of the dollar on import
volumes appears to b e weak and quite delayed,
perhaps reflecting the findings of weak and
delayed import price pass-through.
Finally, the Granger tests indicate that the
dollar leads export volumes, but export volumes
do not lead the dollar. This finding corresponds
with the independence test in Table 1 in the box
and the pattern in the cross-correlation function
in Chart 6, indicating that a decline in the dollar
is followed by a rise in export volume beginning
after a lag of about 8 months and then distributed over the following 16 or so months. This
powerful response, though delayed and distributed, fits the conventional J-curve pattern.
Price Pass-Through Issues
Although the results on the export side of the
balance of trade are consistent with the typical
J-curve story, import prices and volumes do not
show patterns consistent with standard J-curve
theory. Rather, both of these elements move
more slowly and weakly after the dollar change
than most analysts expected. T h e standard
explanation of the J-curve d e p e n d s crucially on
the rapid pass-through of dollar changes to
import prices, thence to import volumes. Previous discussion indicated that certain economists have questioned the quick pass-through
of dollar changes. Since the results of this research point to this weakness in the J-curve
explanation, a more thorough discussion of passthrough issues is indicated.
Analyses of balance of trade responses for
developed countries usually rely on an empirical
10
regularity now known as Grassman's rule (S. Grassman, 1973), which states that trade prices are likely
to be invoiced, and thus initially fixed, in terms of
the exporter's currency. S. Magee (1973) demonstrated that a standard J-curve pattern, such
as that observed after the British devaluation
in 1967, could be explained by such invoicing
practices (also s e e J. Bilson, 1983). If U.S. imports are invoiced in foreign currencies and
trade volumes do not change immediately, a
dollar decline would initially result only in
higher import prices measured in dollars, leading
to the "perverse" initial trade balance deterioration defining a J-curve.
Bilson, however, points out that "trade in primary
products and capital assets is typically denominated in major vehicle currencies, particularly the
U.S. dollar."5 Consequently, the type of price passthrough consistent with Grassman's rule and
underlying the J-curve may not extend to the
imports of the United States because of the
dollar's role as a global vehicle currency.
Indeed, the United States may b e a special
case. Several recent studies point to the unusually slow or weak rise in U.S. import prices
following the dollar's plunge from 1985 onwards. These studies emphasize that foreign
exporters may cut profit margins to maintain
market share. 6 In addition, invoicing and contracting practices themselves may delay an
initially perverse J-curve response in the U.S.
case. The International Monetary Fund (IMF)
reports that about 70 percent of U.S. imports
are invoiced in the U.S. dollar. If this figure is
correct, then some countries exporting to the
United States do not invoice all of their exports in their own currencies. For example, in
1986 fully 64 percent of Japanese exports were
not denominated in yen (International Monetary Fund, 1987).
Further, U.S. imports are often p u r c h a s e d
under contracts that fix prices in dollar terms
for an extended period. Bilson (1983, p. 386)
states that: " T h e major part of true international trade is contractual
" and these
contracts could b e lengthy.
If U.S. import prices often are contractually
fixed in dollar terms, and if contracts are at
least implicitly set for long periods, then most
of the pass-through of dollar declines into the
import price index will b e d e l a y e d . Thus, the
J-curve's initial t r a d e b a l a n c e deterioration
ECONOMIC REVIEW. JULY/AUGUST 1988 J
would be delayed, as would the subsequent
improvement based on the reaction of import
volumes to higher import prices.
Implications: An Alternative View
Evidence on the dynamic relationships between the dollar and the four critical components of the trade balance suggests a new
view of the U.S. trade balance response to
dollar depreciation. The two import-side elements of dollar influence display patterns
that are both weaker and more delayed than
the assumed patterns implied by conventional J-curve theory. These results, combined
with an analysis of import price reactions, suggest an alternative to the standard j-curve model
of trade balance evolution.
Evidence that import price pass-through occurs most clearly only after a lag of at least one year
and that import volume responds with an even
longer lag implies a new view of U.S. trade balance
evolution following dollar depreciation. In this
view the nominal balance of trade traces out a
"delayed J-curve" primarily because a dollar
change is not significantly reflected in import
prices for some months and then only weakly.
This pattern may be peculiar to the United
States because, unlike any other country's, the
U.S. currency is an international numeraire, that
is, the international unit of exchange; other
currencies are defined relative to the U.S. dollar.
The dollar is also the primary reserve currencyso widely held that all other currencies can be
easily exchanged for it. U.S. markets may also be
large enough to induce market share competition and less than perfectly elastic supplies.
Consequently, U.S. import prices would not
jump in dollar terms immediately after a dollar
decline. The initial deterioration of a trade
balance following depreciation that marks a
standard J-curve, caused by import prices rising
before volumes can respond, is delayed for at
least a year in the U.S. case. Further, the weak
and delayed import price pass-through hinders
the substitution of domestic products for imported goods, restraining the import volume
contraction.
The result of the delays on the crucial import
side is a delay in both the initial downturn and
subsequent improvement of the trade balance,
I FEDERAL R E S E R V E BANK O F ATLANTA
an effect that is particularly important for the
United States, where the import side recently
far outweighed the export side. In the implied
trade pattern, the trade balance is fairly flat for
about a year, then it deteriorates when import
prices increase (unless the export volume response at that time is very strong). Only after a
further lag do import volumes respond to this
delayed price pass-through and shrink, finally
generating the long-awaited trade balance
improvement.
The "delayed J-curve" pattern proposed in
this article can help to explain the belated
improvement in U.S. nominal trade balances
following the dollar's decline from its 1985 peak.
However, the delay or long lags identified in this
article stem from estimates computed over the
entire floating rate era since March 1973. Rather
than the period since early 1985 being a special
case in U.S. balance of trade history, the overall
U.S. trade balance response to depreciation
itself apparently represents a special case that
does not conform to the conventional J-curve
model.
This article suggests that import prices have
reacted slowly because many U.S. imports are
priced in dollars and subject to long-term contracts. As noted above, however, other plausible
explanations are available for the delay in the
reaction of the U.S. nominal balance of trade to the
dollar's decline since 1985. The delayed J-curve
is generally consistent with and complementary
to these explanations, and each may have
relevance to the continuing episode of delayed
trade balance response.
The standard J-curve was originally developed
to explain responses to one-time devaluations
rather than long gradual declines such as that
recently experienced by the dollar. A gradual
decline can be seen as a series of small depreciations generating a series of J-curves
played out in an overlapping sequence that
traces a balance-of-trade time path similar to a
delayed J-curve (see Chart 7). The tardy declines
of the exchange rates of important U.S. trading
partners, seen especially in the behavior of the
Asia-excluding-Japan as well as the Canadian
subindex of the Atlanta Fed dollar index, may
also have weakened or postponed the response
of the trade balance to the dollar's decline. 7
Several other factors subsumed under the
currently popular rubric of hysteresis are blamed
13
Chart 7.
A Comparison of the Standard
and Delayed J-Curves
Merchandise
Trade
Balance
Dollars
— — Standard J-Curve
Delayed J-Curve
such as the sharp and persistent rise of the
dollar between 1981 and 1985. There are several
strands of this argument: First, uncertainty
about the permanence of the low dollar level
may delay reactions by exporters and importers
and result in a delayed J-curve. Second, in order
to maintain U.S. market share or simply to continue to cover their variable costs of producing
and marketing, foreign producers of U.S. imports may be willing to cut prices in their own
currency after the dollar depreciates. Third,
domestic producers, already burned by import
competition, may hesitate to add capacity to
produce goods that substitute for imports until
exchange rate changes begin to appear permanent.
Conclusion
t=0
t=1
t=2
t=0 time of initial currency depreciation.
t=1 time at which net export balance is expected to begin
to improve ("standard J-curve").
t=2 time at which actual improvement begins.
(t= 1) - (t=0): standard response time
(t=2) - (t=0): actual response time
(t=2) - (t=1): additional delay
for import prices' slow response. 8 The hysteresis argument is based on the occurrence of
irreversible change in the face of large shocks
12
This study has focused attention on nominal
imports in trying to explain the slow turnaround
in the U.S. trade balance following the dollar's
1985 peak. This laggardly response is rooted in
the slow or partial pass-through of the dollar's
movement into import prices, as well as the consequently slow and weak import volume response to the dollar through import prices.
Therefore, both the initial deterioration and
the subsequent upturn reflected in a J-curve
pattern are delayed, leading to a proposal of
an alternative v i e w - t h e " d e l a y e d J-curve."
Further, our empirical results find that this
delay in the U.S. data applies not just to the
period since 1985, but to the entire floating
exchange rate era.
ECONOMIC REVIEW. JULY/AUGUST 1988 J
Data and Time Series Models Used in this Research
The import and export price indexes used in
this article are the unit value indexes found in the
International Monetary Fund's International Financial StatisticsImport
and export volume
indexes are created by deflating the nominal
values reported in International Financial Statistics by these price indexes. The dollar's value is
given by the Federal Reserve Board's multilateral
trade-weighted dollar index comprising ten major
foreign currencies.2 Dollar depreciation is signified by declines in the index.
The time series models used in this research
are explored in some detail by the authors in
several other places. Koch and Rosensweig (1988)
present a detailed explanation and set of references on the models. The models are also explained in Koch, Rosensweig, and Whitt's 1986
and 1988 research and in Ira G. Kawalier, Koch, and
Timothy W. Koch (1988).
Time series models such as these can be interpreted loosely as reduced form models, except
that the noise model (error term) in each replaces
other "exogenous" variables that would appear in
a typical multivariate theoretical structural model.
This noise model is an unrestricted moving average (MA) process that incorporates information
explaining inertia in the variation of the dependent variable that is not explained by the other
included right-hand-side variables. As A. Zellner
and F. Palm (1974) show, a simultaneous system
that incorporates dynamic structural equations
implies reduced form relationships that may be
expressed explicitly as time series models of
this nature.
Time series models are particularly useful for
identifying the existence, direction, and extent of
dynamic relationships between variables. Koch
and Yang (1986) provide a test that encompasses
both a comparison of each coefficient in the crosscorrelation functions computed here to their standard errors, and a scrutiny of these functions for a
possible pattern in the successive distributed lag
coefficients. This statistic is used here to test for
the independence of individual trade balance
elements from the exchange rate. A summary of
I FEDERAL R E S E R V E BANK O F ATLANTA
the results from the Koch-Yang tests is shown in
Table I.
Time series independence tests can indicate
that a relationship exists, and can distinguish between a short distributed lag with large coefficients and a long distributed lag pattern with
small coefficients. However, once the independence hypothesis is rejected, the nature of the
dynamic relationships should be examined further. The research statistically examines the direction of Granger causality, testing whether each
variable can be predicted more accurately using
past values of both variables, rather than using
past values of each variable alone.
In order to estimate the model and compute the
standard F tests, a finite lag parameterization
must first be chosen. While longer lag lengths
lessen the chance of misspecification, they also
result in the loss of more degrees of freedom.
Hence it is desirable to choose the minimum lag
length that specifies the relationships accurately.
In this analysis, the lag length was set at 48 months
for the dependent variable in each equation and
36 months for theright-hand-sidevariable.
Table 2 summarizes the results of these Granger
tests of causal priority or predictive ability.
Notes
' Related studies invariably use unit value indexes, after
pointing out their weaknesses compared to true price
series, because unit values are the only data consistently available for a long sample period. Particularly
given this model's ability to use monthly data, the
availability of unit value data becomes the compelling
factor in data choice. Further, the absence of a long
monthly series on "non-oil import prices" precludes
removing oil imports and their prices from this study.
2 This choice was motivated by comparability to earlier
studies, but tests show that this paper's results are
fairly robust The Atlanta Fed Dollar Index, which uses
bilateral trade weights and has a broader 18-currency
coverage, was also employed with results similar to
those reported in this paper.
13
Table 1.
Time Series Independence:
Do Koch-Yang Tests Reject Independence?
Significance Level
Series
5 percent
10 percent
Exchange rate and Import prices
no
no
Exchange rate and Export prices
no
yes
Exchange rate and Import volumes
yes
yes
Exchange rate and Export volumes
yes
yes
Table 2.
Granger Tests of Causality:
Do Lags of Variable 1 Help Predict Variable 2?
Significance Level
5 percent
10 percent
Import prices
yes
yes
Exchange rate
Export prices
no
no
Exchange rate
Import volumes
no
no
Exchange rate
Export volumes
no
yes
Import prices
Exchange rate
no
no
Export prices
Exchange rate
no
no
Import volumes
Exchange rate
yes
yes
Export volumes
Exchange rate
no
no
Variable 1
Variable 2
Exchange rate
14
ECONOMIC REVIEW. JULY/AUGUST 1988 J
Notes
1 See,
for instance, Krugman and Baldwin (1987), Hooper and
Mann (1987), and Rose and Yellen (1987).
4 See,
2 For
6See
3 See,
% e e Baldwin (1988), Baldwin and Krugman (1986), and Foster and Baldwin (1986).
other recent views on delayed pass-through, see Mann
(1986), Giovannini (1988), and Baldwin (1988), among
others.
for example, Dornbusch (1987), Mann (1986), and Krugman (1986).
for instance, Rose and Yellen (1987).
(1983): 384.
5 Bilson
the studies cited in footnotes 1, 2, and 3, particularly
Mann (1986) and Krugman and Baldwin (1987).
7 S e e Rosensweig (1986).
References
Baldwin, Richard. "Some Empirical Evidence on Hysteresis
in Aggregate U.S. import Prices." National Bureau of
Economic Research Working Paper no. 2483 (January
1988).
Kawaller, Ira G„ Paul D. Koch, and Timothy W. Koch. "The
Relationship between the S & P 500 Index and S & P 500
Index Futures Prices." Federal Reserve Bank of Atlanta
Economic Review 73 (May/)une 1988): 2-10.
and Paul Krugman. "Persistent Trade Effects of
Exchange Rate Shocks." Massachusetts Institute of
Technology, 1986.
Koch, Paul D., and ).F. Ragan, )r. "Investigating the Causal
Relationship Between Quits and Wages: An Exercise in
Comparative Dynamics." Economic Inquiry 24 (lanuary
1986): 61-84.
Bilson, J. "The Choice of an Invoice Currency in International
Transactions." In Economic Interdependence and Flexible Exchange Rates, edited by ). Bhandari and B. Putnam, 384-401. Massachusetts Institute of Technology
Press, 1983.
Box, G.E.P., and C.M. Jenkins. Time Series Analysis, Forecasting and Control. San Francisco: Holden Day, 1976.
Caves, R., and R. (ones. World Trade and Payments. 4th ed.
Boston: Little, Brown, 1985.
Dornbusch, Rudiger. "Exchange Rates and Prices." American Economic Review 77 (March 1987): 93-106.
Foster, Harry, and Richard Baldwin. "Marketing Bottlenecks
and the Relationship between Exchange Rates and
Prices." Unpublished paper, Massachusetts Institute of
Technology, 1986.
Geweke, )ohn. "Testing the Exogeneity Specification in the
Complete Dynamic Simultaneous Equation Model."
Journal of Econometrics 7 (April 1978): 163-85.
"Comparison of Tests of the Independence of
Two Covariance-Stationary Time Series." lournal of the
American Statistical Association 76 (June 1981): 363-73.
Koch, Paul D., and Jeffrey A. Rosensweig. "The U.S. Dollar
and the Delayed J-Curve.' " Federal Reserve Bank of
Atlanta Working Paper 88-4 (forthcoming, 1988).
Koch, Paul D„ Jeffrey A. Rosensweig, and Joseph A. Whitt, Jr.
"The Dynamic Relationship Between the Dollar and U. S.
Prices: An Intensive Empirical Investigation." Journal of
International Money and Finance 7 (June 1988): 181-204.
Koch, Paul D., and S.S. Yang. "A Method for Testing the
Independence of Two Time Series that Accounts for a
Potential Pattern in the Cross-Correlation Function."
Journal of the American Statistical Association 81 (June
1986): 533-44.
Krugman, Paul. "Pricing to Market When the Exchange Rate
Changes." National Bureau of Economic Research Working Paper no. 1926 (May 1986).
. and Richard Baldwin. "The Persistence of the
U.S. Trade Deficit." Brookings Papers on Economic
Activity 1 (1987): 1-56.
Ljung, G.M., and G.E.P. Box. "On a Measure of Lack of Fit in
Time Series Models." Biometrika 65 (1978): 297-303.
Giovannini, Alberto. "Exchange Rates and Traded Goods
Prices." lournal of International Economics 24 (1988):
45-68.
Magee, S. "Currency Contracts, Pass-Through, and Devaluation." Brookings Papers on Economic Activity I (1973):
303-25.
Granger, C.W.). "Investigating Causal Relations by Econometric Models and Cross-spectral Methods." Econometrica 37 (July 1969): 424-38.
Mann, Catherine. "Prices, Profit Margins and Exchange
Rates." Federal Reserve Bulletin 72 (June 1986): 366-79.
Grassman, S. "A Fundamental Symmetry in International
Payment Patterns." Journal of International Economics 3
(1973): 105-16.
Haugh, Larry D. "Checking the I n d e p e n d e n c e of Two
Covariance Stationary Time Series: A Univariate Residual
Cross-Correlation Approach." journal of the American
Statistical Association 71 (June 1976): 378-85.
Hooper, Peter, and Catherine Mann. " T h e U.S. External
Deficit: Causes and Persistence." International Finance
Discussion Paper no. 316 (November 1987).
International Monetary Fund. IMF Survey. (September 28,
1987): 280-81.
I FEDERAL R E S E R V E BANK O F ATLANTA
Rose, A. and J. Yellen. "Is there a J-Curve?" University of
California at Berkeley (May 1987).
Rosensweig, Jeffrey. "A New Dollar Index: Capturing a More
Global Perspective." Federal Reserve Bank of Atlanta
Economic Review 71 (June/July 1986): 12-22.
Whitt, Joseph A., Jr., Paul D. Koch, and Jeffrey A. Rosensweig.
"The Dollar and Prices: An Empirical Analysis." Federal
Reserve Bank of Atlanta Economic Review 71 (October
1986): 4-18.
Zellner, A., and F. Palm. "Time Series Analysis and Simultaneous Equation Econometric Models." Journal of
Econometrics 2 (January 1974): 17-54.
15
Past and Current Trends
in Retirement:
American Men from 1860 to 1980
Jon R. Moen
In comparison to earlier periods in U.S. history, a much smaller percentage of men aged 65 and over is now in
the work force. This study examines the reasons for the shift in labor force participation
effects on the nation's
Most men in the United States will retire by
age 65. Earlier this century, though, men as a
group remained active in the work force past
this age. In 1985 only 16 percent of men aged 65
and older were "officially" working, or working
outside the home. In contrast 58 percent of men
aged 65 and older were in the labor force in
1930, while even as late as 1950,47 percent were
in the labor force. Social Security, private pensions, a changing mix of occupations, and a large
supply of younger workers from the baby boom
have made it easier for older men to leave the
labor force. The choice for the average male
worker today is not if he should retire but rather
how soon he should retire.
Concurrent with the decreased participation
in the labor force among older males is the aging
of the American population. The baby boom
generation is just entering its years of peak pro-
The author is an economist
Atlanta
Fed's Research
16
and considers its possible
economy.
in the regional
Department.
section
of the
ductivity, but the supply of young, entry-level
workers is the smallest it has been in years.1 In
20 to 25 years, when the baby boom generation
begins reaching retirement age, people over
age 65 will make up a greater percentage of the
population than at any time in the nation's history. The labor force participation rates of these
people will have important implications for
labor force size and growth, and consequently
for growth in the economy's capacity to produce.
The presence of older workers in the labor force
thus has important macroeconomic ramifications.
The fall in the labor force participation rate of
men aged 65 and older has been one of the most
dramatic changes in our labor markets. The percentage decline since 1900 has been greater
than the percentage increase in female labor
force participation. Since our understanding of
retirement and the role of older persons in our
society has been influenced by the continued
withdrawal of older men from the labor force,
they are the focus of this research.
ECONOMIC REVIEW. JULY/AUGUST 1988 J
The tendency for older men to retire earlier
and earlier has not been constant and is a fairly
recent event. Over the long run, periods of sustained decline in participation have been followed by periods of relative stability. Furthermore, the periods of decline coincide with
changes in federal policy and private attitudes
towards retirement, aging, and work itself. The
historical record also suggests possible solutions for some of the future problems presented
by an aging population and the continued
withdrawal of older men from the labor force.
Changing Patterns in Labor Force
Participation, 1860 to 1980
Three changes in the labor force between
1860 and 1980 allowed—and in some cases
forced—older men to leave work. First, in 1860
most people lived in rural areas and worked at
jobs related to agriculture. Being self-employed
I FEDERAL R E S E R V E BANK OF ATLANTA
and working in or near one's home was not
unusual, and a worker in this situation could
generally set his own pace. Since 1860 the home
and workplace have become increasingly separated, and most jobs are now in or near urban
areas. Farm households have always provided a
wide range of jobs with varying degrees of physical difficulty. Older men had little reason to
retire completely because repair and maintenance work was always needed on a farm, in
addition to more strenuous work like planting or
plowing. Rural employment and retirement patterns contrast greatly to retirement from factory
work, in which withdrawal from the labor force is
quite distinct and abrupt.
Second, in the 1860s few private pensions or
government-sponsored assistance plans aided
older workers; family support was the main
source of help for the few who stopped working.
By the late 1930s Social Security was in place,
and businesses were starting to offer pensions
to employees. Pensions became widespread
after 1950.
17
Chart 1.
Labor Force Participation Rates of Men Aged 65 and Older: 1860 to 1980
LFPR
(percent)
Source: J o n Moen, "From Gainful Employment to Labor Force: Definitions and a New Estimate of Work Rates of American Males, 1860 to
1980," Historical Methods, forthcoming, fall 1988, tables 1 and 2.
A third change in the labor force was the
change in methods of compensation and production, with hourly wages and factories becoming more prevalent than piece rates and working
at home. Hourly wages and assembly lines
placed a premium on the ability to do continuous and repetitive tasks, and employers
would want to replace older workers who could
not keep pace. Piece rates were suitable for
more intermittent and individualized work
where the worker set his own pace. With piece
rates, employers would be willing to let older
workers work less intensively than younger
workers, thus allowing older workers to avoid
retirement. The argument assumes that older
workers would not impede the work of others or
tie up machines that more productive workers
could use.
18
Labor force data definitions and sources have
also changed considerably since 1860. To overcome problems caused by definitional changes,
this research pieces together a series of labor
force participation rates that are defined consistently from 1860 through 1980 for men aged 65
and older. The series is based on an alternative
measure of the labor force, which allows examination of labor force participation rates over a
longer period than had b e e n possible before.
Details on the construction of the series are presented in the box on page 26.
Chart 1 contains the 1860-1980 participation
rates for men aged 65 and older, estimated with
both the current and alternative measures of
labor force participation. 2 The figures in Chart I
show that between 1860 and 1980 the labor
force participation rate of men aged 65 and
ECONOMIC REVIEW. JULY/AUGUST 1988 J
Table 1.
Civil War Pensioners and Their Benefits: 1880 to 1930
Year
Pensioners
(thousands)
1880
250
1890
Average Payment
($/veteran)
520
U.S.
Per Capita Income
—
—
162
210
740
142
231
560
189
349
1920
240
460
755
1930
50
941
857
1900
1910
The Potential Effect of Civil War Pensions on Labor Force Participation:
1880 to 1920
(thousands)
Population
Pensioners
Change in
Labor Force
Change in
Pensioners
Year
Labor Force
1880
—
—
250
—
—
1890
888
1,200
520
—
+270
1900
975
1,500
740
+87
+220
1910
1,160
2,000
560
+185
-180
1920
1,500
2,500
240
+350
-320
White Male Labor Force Participation Rates: 1900
North
Age
Farm
South
Nonfarm
Farm
Nonfarm
65-69
.87
.72
.97
.84
70-74
.79
.49
.86
.71
.56
75-79
.64
.38
.88
80+
.42
.15
.62
65+
.72
.54
.88
.72
N
627
89
69
1,071
.25
Source: J o n Moen, Essays on the Labor Force and Labor Force Participation Rates. The United States from 1860 through 1950,
unpublished Ph.D. dissertation, University of Chicago, 1987.
older fell by two-thirds. Labor force participation held steady at about 75 percent until 1890,
when the first period of decline began. The
causes of this decline are not certain, but two
events seem likely to have contributed to it. Between 1900 and 1910 over 700,000 Civil War
I FEDERAL RESERVE BANK OF ATLANTA
veterans became eligible for pensions. Although
it is impossible to determine at present how
many of the veterans used their pension benefit
to retire, the overall number of pensioners
affected was certainly more than enough to
account for the decline in labor force participa19
Table 16.
Coverage of Public and Private Pensions: 1950 to 1979
(thousands of persons
covered)
Labor Force
Private
Federal
1950
62,208
9,800
1960
69,628
18,700
3,118
1970
82,715
26,100
1979
102,908
35,200
State/Local
Social Security
2,600
36,500
3,077
4,500
55,300
3,320
7,300
69,200
3,034
11,400
87,600
Source: Laurence Kotlikoff and Daniel E. Smith, Pensions in the American Economy (Chicago: University of Chicago Press,1983): 28; and
Social Security Administration, Social Security Bulletin, Annual Statistical Supplement, 1983,61.
tion (see Table l). The fact that the labor force
participation rate of older men in 1900 was higher
in the South than in the North lends further support to this view since veterans of the Confederate
army were not eligible for federal pensions.
Related to the increase in coverage of Civil
War pensions, the growing perception of old age
itself as a distinct medical condition, regardless
of one's state of health, also may have contributed to earlier retirement by older men. Old
age was increasingly being viewed by employers and the federal government as a debilitating
state. For example, for many years veterans were
eligible for pensions only if they had b e e n
wounded or disabled during the Civil War. By
1907 "old age" was included among the conditions that would qualify a veteran for a pen-
Table 3.
Increase in IRS Qualified Pension
Plans: 1939 to 1980
(number of plans)
1939
659
1949
12,154
1960
63,698
1970
225,899
1980
616,642
Source: Laurence Kotlikoff and Daniel E. Smith, Pensions in the
American Economy (Chicago: University of Chicago
Press, 1983): 165
20
sion, regardless of any other medical conditions
or handicaps. 3 It is also true that around this
time employers began to offer pensions as a
means of enticing older workers to retire, thus
making room for younger workers who may have
been more productive in the increasingly mechanized factory. Nonetheless, the coverage of
private pensions at the turn of the century was
small and cannot account for much of the decline to that time in labor force participation.
Around 1910 the decline in labor force participation was interrupted. Labor force participation remained constant at about 58 percent before declining again during the 1930s.
Although labor force participation d i d not
change much, the workplace was undergoing
further changes. Private pension plans were
beginning to take hold in several industries.
Most of these plans were intended to maintain a
stable work force by reducing turnover among
skilled workers. 4 At this time, though, workers
had no guarantee that they would actually
receive their pension upon retirement. A company could withdraw the pension benefit at any
time if the employee acted in a way that the
company perceived not to be in its best interest.
Such behavior might entail, for example, going
on strike, taking a second job, or even marrying.
Furthermore, the coverage that these pensions
provided was small when compared to today's,
and many pensions were wiped out during the
Great Depression.
Aside from the incipient growth of private
pension plans, the creation of Social Security in
1935 also may have spurred changes in labor
ECONOMIC REVIEW, JULY/AUGUST 1988
Table 4.
Age Distributions of Men Aged 65 and Older: 1860 to 1980
(in percent)
1860
1900
Age
Bateman-Foust
Older Males
1980
Average
65-69
1950
42
46
43
43
43
38
70-74
28
32
29
29
26
28
75-79
17
14
16
16
18
18
13
8
12
12
13
16
1,662
1,209
—
1.995
879
10,311
80+
N
Note: The Bateman-Foust
and Older Males
age distributions
were given weights of 85 and 15 percent,
respectively.
Source: Jon Moen, Essays on the Labor Force and Labor Force Participation Rates: The United States from 1860 through 1950,ure-
published Ph.D. dissertation, University of Chicago, 1987.
force participation, although the first payments
were not made until 1942. The Social Security
Act established a system that was part welfare
payments based on need (Title I of the Social
Security Act) and part retirement payments
based on one's previous work history (Title II of
the Act). The Title II provisions were created in
part to draw older workers out of the labor force
and allow younger workers to obtain work during the Depression. 5
Labor force participation rates began their
most recent decline after 1950. By 1980 rates
had fallen from 47 to 26 percent when measured
with the alternative measure and from 41 to 19
percent when measured with the Labor Department's labor force definition. The number of
private pension plans expanded rapidly during
this period, and by I960 Social Security had
become almost universal, covering nearly 84
percent of the work force (see Tables 2 and 3).
Intuitively, it might seem that the rise in life
expectancy since 1860 and the increasing share
of men 65 and older in the population should
account for some of the decline in participation
as is the case for the participation rate of men
aged 16 and older. But, the aging of the work
force is only beginning to have an impact on the
participation of men aged 65 and older, because the age distribution of this group has
changed little since I860 even though its members are a larger share of the population. The
I FEDERAL RESERVE BANK OF ATLANTA
relative stability of the age distribution of men
at older ages suggests that participation above
age 65 declined because of changes in agespecific participation rates, rather than a shift in
the age structure of the population towards a
larger share of older workers (see Table 4); since
1950 retirement has become a standard part of
one's work career.
Economic Reasons for the Decline
in Labor Force Participation
T h e growth of private pension plans and
Social Security has made retirement from the
labor force a more viable option for aging male
workers in the twentieth century. Rising real
income, wages, and unearned income would
also seem to have played some role in the
decline of labor force participation among men
aged 65 and older. Not until the 1950s, however,
did income's effect on retirement become substantial. Leisure is thought to b e an incomenormal good; that is, the higher one's income,
the more leisure time one demands. Economists refer to the relationship between income
and the quantity of a good demanded—in this
case, leisure—as the "income effect." On the
other hand, higher wages increase the value of
time and, hence, the price of leisure, making
21
individuals reluctant to forgo opportunities to
earn more money. The relationship between the
price of a good and the quantity demanded—in
this case, the wage rate and leisure time—is
called the "substitution effect." Higher unearned income—such as interest, dividend, or
trust fund income that is independent of one's
wage or salary—would tend to lower labor force
participation if leisure is an income-normal
good. Whether or not the income effect dominates the substitution effect is an empirical
question, and the evidence is mixed.6
Economists have also recognized other factors as influential in the decision to enter or stay
in the work force. These factors range from
marriage and education to self-employment
and rising wage levels.
In the past, marriage has tended to prolong a
man's stay in the labor force. The reasoning is
that since he and his spouse would have to live
on his pension and Social Security income, the
man would tend to work longer to increase the
value of these income sources. The increasing
tendency of wives to work outside the home may
diminish the importance of a husband's continued participation in the labor force.
Education also extends a worker's stay in the
labor force. More educated persons typically
have access to higher-paying and perhaps more
pleasant jobs, which increases the opportunity
cost of retirement. Self-employed workers tend
to stay in the labor force longer, often because
they are not subject to any mandatory retirement rules. Because many self-employed workers are doctors, lawyers, or members of other
professions, higher educational attainment is
again a factor in their higher participation
rate.
Research Findings. Though items such as an
increase in pensions, a man's marital status, or
the extent of a man's formal education affect the
overall level of labor force participation among
aging male workers, until about 1950 much of
the decline in the labor force participation rate
of older men was attributable to a change in the
mix of occupations.7
In 1860, 65 percent of men aged 65 and older
lived on farms, while today less than 3 percent
do. Labor force participation among older men
living on farms fell 25 percent between 1860 and
1980 (from 88 to 66 percent), while participation
in the labor force fell 66 percent overall. Most of
22
the decline came within nonfarm households.
The increasing weight of nonfarm households in
the overall average labor force participation rate
also contributed to the decl ine. Had the share of
older men living on farms remained constant
between 1860 and 1980, the labor force participation rate of men 65 and older would have
been 48 percent rather than 26 percent in 1980,
when participation is defined using the alternative measure.
The movement out of agricultural jobs was
part of the larger shift in the mix of occupations,
in which manufacturing jobs became more
important. In the nineteenth century older men
tended to retire earlier from some jobs than
from others (see Table 5). Men in farm-households and in the households headed by unskilled laborers tended to stay at work longer
than those in the households headed by skilled
craftsmen. As the economy moved away from
unskilled jobs and agricultural employment,
the labor force participation rate of men aged 65
and older started to fall. Unskilled workers in
1900 worked on average at least as long as in
1860, as did farmers, skilled workers, and professionals. However, unskilled workers and
farmers were becoming a smaller share of the
work force. Also, the share of older men living in
households where the head had no occupation
went from 10 to 20 percent, which accounts for
most of the decline in participation between
1860 and 1900. Retired Civil War veterans may
have been a major element in this particular
decline.
Around 1950 the rate of retirement from all
types of jobs increased, and the shift in the mix
of jobs began to have less effect on the overall
labor force participation rate of older men. An
increase in the share of households headed by
older men who had no occupation accompanied
this general tendency to retire. In 1860 about 10
percent of men aged 65 and older lived in
households where the head had no occupation.
Today over 55 percent live in such households
and 90 percent are also the household h e a d even though they have no occupation. The rise
of private pensions and Social Security has
made this a fairly typical phenomenon in the
United States.
Measuring the relative importance of the
income versus the substitution effect back to
1860 is difficult because of a lack of income and
ECONOMIC REVIEW. JULY/AUGUST 1988 J
Table 13.
Labor Force Participation Rates by Household Type:
1860 to 1980
(alternative
All
Professionals
.76
1860
Farm
.88
.73
.86
Service/Clerks
.86
.71
.08
(-01)
(.10)
(.08)
.86
(.13)
.83
.90
(-12)
.85
(-12)
(-04)
.75
.47
(.11)
.26
.82
.67
(-09)
(•14)
.66
—
.53
.43
(•03)
—
None
(.11)
(•05)
(•39)
—
1980
Laborers
.85
.70
1950
Skilled
(.65)
—
1900
definition)
(-09)
.86
.78
(-12)
(.06)
.53
(.14)
.08
(-20)
.16
(-50)
.58
.01
(-16)
(-04)
(.56)
Note: Figures in parentheses are percentage of men 65 and older living in each household type.
Source: J o n Moen, "The Shifting Structure of Occupations and the Effect on the Labor Force Participation Rate of American Males, 1860to
1980," Fédéral Reserve Bank of Atlanta Working Paper 88-3, May 1988.
Table 6.
Labor Force Participation Rates by Month: 1980 to 1987
(current
J
1980
1985
1987
19.6
F
definition)
M
A
M
J
J
A
S
O
19.1
19.0
18.9
18.7
15.6
15.6
15.2
19.2
15.7
18.6
18.5
16.3
16.7
16.0
16.0
16.3
16.8
16.2
15.9
16.1
16.5
16.7
17.0
15.7
19.9
19.2
15.8
16.2
15.6
15.7
15.9
15.8
16.0
N
D
18.6
18.5
Note: Labor force participation rates are seasonally adjusted.
Source: U.S. Department of Labor, Bureau of Labor Statistics, Employment and Earnings, February 1985, p. 134, and February
1988, p. 131.
wage data. Still, assuming that wealth in the
form of real estate and personal property is a
reasonable proxy for unearned income, wealth
information from the 1860 census demonstrates
that the level of one's wealth had little effect on
the probability of being in the labor force.8 In
contrast, the 1950 census contains income and
wage data which imply that higher unearned
income, such as that available from pensions,
FEDERAL RESERVE BANK OF ATLANTA
resulted in lower labor force participation
among men aged 65 and older. Preliminary
results from 1980 census data are similar. While
these results are not intended to b e precise
estimates of the labor supply's sensitivity or responsiveness to changes in income, they indicate that the elasticity of labor force participation with respect to income increased greatly
between I860 and 1980.
23
Recent Tïends în Labor Force
Participation Rates
The increasing share of household heads having no occupation and the rapid decline in labor
force participation since 1950 are unique events
in American economic history. Although differences in labor force participation rates across
households classified by occupation have always been important, their magnitudes are
small in comparison to the decline in the overall
rate between 1860 and 1980. However, research
suggests that the sharp overall decline will not
continue and may not have been as large as was
first thought.
If the current definition of the labor force is
used, participation among older males fell from
41 percent in 1950 to 19 percent in 1980. Current
measurements indicate that this trend has
stopped and that participation in this cohort
maybe starting to increase (see Table 6). In mid1985 labor force participation was close to ¡5
percent. Over the next two years it rose slowly
until, by the end of 1987, labor force participation was at 17 percent. While not dramatic, the
increase suggests that labor force participation
can move up as well as down, as it did briefly
during World War 1 . The increase of 2 percent1
age points also means that about 230,000 more
older men are at work than would have been had
the participation rate remained at 15 percent.
The alternative measure of labor force participation indicates that more older men may
have been working than the current measure
indicates. William G. Bowen and T. Aldrich
Finegan (1969) show that withdrawal from the
labor force by men between ages 64 and 67
tends to be in terms of fewer weeks of work per
year rather than shorter work weeks or fewer
hours per day. 9 If some men were not at work
during the census reference week, they would
not be counted as part of the labor force under
the current definition, even though at some
other point in the year they happened to be
at work.
The influence of government pol icy seems to
have been strongest during the most recent
period of declining labor force participation
since the drop is closely associated with the
spread of Social Security. Research shows that a
negative correlation existed between participa24
tion and unearned income—including Social
Security and pension income—in 1950 and 1980.
Furthermore, Bowen and Finegan demonstrate
the extent to which Social Security provides a
disincentive to continue working after age 65.10
They show that participation in I960 declined
for men aged 65 and 71, after which it increased
for several years before declining again. They
attributed this reversal to the Social Security
earnings test, which at that time reduced Social
Security payments for persons earning more
than $1,200 a year. After age 71, however, this
restriction ceased to apply. Consequently, many
older men returned to the labor force in spite of
increasing age, and their participation rate rose
by 3 to 4 percentage points.
Summary and Outlook
Starting during the New Deal, government
policies toward older workers contributed to
the decline in labor force participation, although they do not explain ail of the decline
Official recognition of old age as a reason to
retire regardless of physical ability, combined
with the expanding coverage of Social Security,
has made retirement an accepted, if not expected, practice. Recent revisions to the Social
Security Act, however, will alter some of these
perceptions. The age at which one can retire and
receive full benefits is currently increasing
depending on when one was born. For individuals born after 1960 the retirement age will rise
to 67. Early retirement is still possible, but
individuals who retire early will be eligible for
only 70 percent of benefits rather than the
current 80 percent. In addition, mandatory
retirement for some workers has been eliminated. In particular, the 1978 amendments to
the Age Discrimination in Employment Act
raised the age of mandatory retirement in
private industry to 70 from 65 and eliminated it
for federal workers.
Research presented here shows that the
labor force participation rate of older men has
stopped declining and may be starting to increase. The increase will be gradual until workers
of the baby boom cohort begin reaching the
traditional retirement age of 65. At that time, a
potential squeeze on Social Security benefits
ECONOMIC REVIEW. JULY/AUGUST 1988 J
may also make retirement less attractive, but
adequate funding for retiring baby boomers
should exist if the trust fund is managed properly. Much of the response to the changing labor
market, however, will have to come from individuals acting in their own financial and
economic interest, regardless of government
policy changes. A smaller share of individuals
may choose complete retirement because the
smaller supply of workers to replace them will
maintain pressure on wages and salaries, de-
I FEDERAL R E S E R V E BANK OF ATLANTA
creasing the incentive to retire. 11 Furthermore,
the changing mix of jobs away from manufacturing toward services will make it physically easier
for older men to remain in the labor force. Like
laborers who worked for piece rates, older
workers in service jobs will have some flexibility
to set their own pace. The widespread decline
of labor force participation among older male
workers during the middle of the twentieth century may eventually emerge as a unique event in
our economic history.
25
Labor Force Participation: An Alternative Measure
As with many time series, the definition of what
one is measuring changes—sometimes substantially; this is the case with labor statistics and the
definition of labor force participation. Most of this
article's information about the labor force comes
from samples drawn from the manuscript schedules of the 1860 through 1980 decennial censuses.1 Manuscript schedules are the forms on
which the census enumerators record household
information.
Between 1930 and 1940 the Census Bureau
replaced its definition of "gainful employment"
with the current definition of labor force activities.
Gainful employment formerly consisted of those
tasks or pursuits through which a person usually
earned money or goods to support himself. To be
part of the labor force under gainful employment,
one simply had to report an occupation when the
census enumerator came around. The enumerator
did not record when the occupation was pursued
or how much time was spent at it. From 1860
through 1930 the labor force participation rate for
older men was thus defined as the proportion of
men aged 65 and over reporting an occupation to
the census enumerator. Individuals who described themselves as retired or reported nonoccupations like "student" were not included in
the labor force.
Currently to be part of the labor force a person
must either have a job or be looking for one during
a specific week of the census year. The job activity
in which one engages to support oneself is less
important. Individuals not working or looking for
work during the specified week would not be
counted as part of the labor force even if they had
been at work a few weeks earlier.2 Gainful employment is not as restrictive a category and is more
likely to cover people with seasonal or part-time
jobs.
To overcome the inconsistencies between gainful employment and the current definition of the
labor force, this research utilized an alternative
measure to that currently used by the Census
Bureau and the Bureau of Labor Statistics.3 Under
the alternative measure of labor force participation, rates are defined as the proportion of individuals in an age group reporting one or more
weeks of work in the year prior to the census.4
Unlike the current definition, the alternative
measure covers any work a person may have done
in the year prior to the census and is closer to the
definition of gainful employment. Table 7 presents labor force participation rates estimated
with the current definition and the alternative
measure for 1950 and 1980.
Table 7.
A Comparison of Labor Force
Participation Rates Measured
by Current and Alternative Methods
Age
1950
1980
14-19
46
16-19
—
(34)
20-24
86
(82)
93
(92)
94
93
—
_
65
(52)
91
(83)
93
(92)
86
(93)
(83)
76
65+
47
14+
80
(41)
26
(71)
(79)
—
16+
—
25-34
35-54
55-64
—
—
79
(93)
(19)
—
(75)
Note: The numbers in parentheses are the participation
rates estimated with the current measure.
Source: Jon Moen, "From Gainful Employment to Labor Force:
Definitions and a New Estimate of Work Rates of
American Males, 1860 to 1980," Historical Methods,
forthcoming, fall 1988.
Notes
1 For
1860 the samples are the Bateman-Foust sample of
rural, northern households and a sample of men aged
65 and older in large cities. The 1900, 1950, and 1980
figures were estimated from public use samples. All
samples except the older males sample are available
from the Interuniversity Consortium for Political and
Social Research (ICPSR) in Ann Arbor, Michigan, or the
Bureau of the Census. Contact the author of this article
about the older males sample.
26
2See
Avery (1986) for a discussion of two current measures of the labor force.
3 The
Bureau of Labor Statistics currently uses a definition that asks about one's activities in the labor force
over the previous four weeks instead of one week.
Otherwise its definition is the same as that used by the
Census Bureau.
4Moen
detail.
(1988b) explains the alternative measure in
ECONOMIC REVIEW. JULY/AUGUST 1988 J
Notes
'The baby boom generation is usually defined as those
people born between 1946 and 1964.
E s t i m a t e s of labor force participation for 1940 and after do
not include persons in institutions like hospitals or
asylums. Except for 1880, the estimates before 1940 may
include some institutionalized individuals, because under
the definition of gainful employment in use at the time, an
institutionalized individual could be in the labor force if
he did some work for pay. The sample used to estimate
.
the 1880 rate was designed to cover only the noninstitutional population, which may account in part for the
fact that the 1880 estimate was 2.5 percent higher than the
1860 estimate.
3 Haber
(1983): 111, and Achenbaum (1978): 50.
(1983): 115-16.
5 Graebner (1980), Haber (1983).
4 Haber
^ e e Clark and Spengler (1980) for a review of this point.
7 Moen (1988a).
8 Moen (1987), chapter II.
9 Bowen and Finegan (1969): 281.
I0 lbid., 285.
1
'Levine and Mitchell (1988).
References
Achenbaum, W. Andrew. Old Age in a New Land. Baltimore:
The )ohns Hopkins University Press, 1978.
Avery, David. "Employment: Two Different Measures."
Federal Reserve Bank of Atlanta Economic Review 71
(August/September 1986): 32-39.
Bowen, William G., and T. Aldrich Finegan. The Economics of
Labor Force Participation. Princeton: Princeton University Press, 1969.
Clark, Robert, and Joseph Spengler. The Economics of
Individual and Population Aging. Cambridge: Cambridge
University Press, 1980.
Graebner, William. A History of Retirement: The Meaning
and Function of an American Institution, 1885-1978. New
Haven, Conn., and London: Yale University Press, 1980.
Haber, Carol. Beyond Sixty-Five: The Dilemma of Old Age in
America's Past. New York and London: Cambridge
University Press, 1983.
Kotlikoff, Laurence. "Intergenerational Transfersand Savings."
journal of Economic Perspectives 2 (Spring 1988): 41-58.
, and Daniel E. Smith. Pensions in the American
Economy Chicago: University of Chicago Press, 1983.
I
FEDERAL RESERVE BANK OF ATLANTA
Levine, Phillip, and Olivia Mitchell. " T h e Baby Boom's
Legacy: Relative Wages in the Twenty-First Century."
American Economic Review 78 (May 1988): 66-69.
Modigliani, Franco. "The Role of Intergenerational Transfers
and Life Cycle Saving in the Accumulation of Wealth."
Journal of Economic Perspectives 2 (Spring 1988): 15-40.
Moen, Jon R. Essays on the Labor Force and Labor Force Participation Rates: The United States from I860 through
1950. Unpublished Ph.D. dissertation, University of
Chicago, 1987.
. "The Shifting Structure of Occupations and the
Effect on the Labor Force Participation Rate of American
Males, 1860 to 1980." Federal Reserve Bank of Atlanta
Working Paper 88-3, May 1988a.
. "From Gainful Employment to Labor Force:
Definitions and a New Estimate of Work Rates of American
Males, 1860-1980." Historical Methods (forthcoming,
Fall 1988b).
U.S. Department of Labor. Bureau of Labor Statistics.
Employment and Earnings, February 1985: 134; and February 1988: 131.
27
Commercial Bank Profitability:
Still Weak in 1987
Larry D. Wall
Aggregate bank profit ratios in the United
States were very weak in 1987. Many major
banks anticipated loan losses to troubled foreign borrowers and substantially increased loan
loss provisions. This reduced reported profitability. In 1987, banks' average return on assets
was 0.11 percent and average return on equity
was 1.87 percent. If banks with assets in excess
of $1 billion are excluded, 1987 profitability
ratios increased from the historically weak
levels of 1986, with the return on assets (ROA)
ratio rising from 0.59 percent in 1986 to 0.65 percent in 1987.
Bank profits in six southeastern states have
slipped in recent years, from 0.96 percent ROA
in 1983 to 0.79 percent in 1987.1 Nevertheless,
banks in the Southeast generally outperformed
their peers in the rest of the country again in
1987. Southeastern banks typically had fewer
loans outstanding to Latin American and other
The author is a senior economist
the Atlanta Fed's Research
Wilson for research
28
in the financial section of
Department.
assistance.
He thanks
Sherley
troubled borrowers than the national average,
and hence did not need to make large loan
loss provisions.
Georgia and Alabama banks continue to have
the highest profitability ratios of the six southeastern states examined in this report. Louisiana banks showed improved performance in
1987, but in aggregate they still had negative
returns in terms of two basic profitability measures.
This study examines bank profitability ratios
for U.S. banks in six size categories. The profitability of southeastern banks is also examined
by size category and by state. Finally, the return
on assets by profitability quartiles is examined
for each of the six size categories.
Profitability Measures
Three different profitability measures provide information on bank performance: adjusted net interest margins, return on assets, and
return on equity. 2 Adjusted net interest margin
ECONOMIC REVIEW. JULY/AUGUST 1988 J
measures the difference between the bank's
interest income and interest expense, and is
roughly similar to a business's gross profit
margin. The adjusted net interest margin is
calculated by subtracting a bank's interest
expense from its interest revenue (net of loan
loss provisions) and dividing that result by its
net interest-earning assets. For this calculation, interest revenue from tax-exempt securities is a d j u s t e d upward by t h e bank's
marginal tax rate to avoid penalizing institutions
that hold substantial state and local securities
portfolios, which reduce their tax burdens. Loan
loss expenses are subtracted from interest revenue to place banks that make low-risk loans at
low interest rates on a more equal footing with
those that make high-risk loans which generate
greater interest income.3
The ROA ratio, obtained by dividing a bank's
net income by its assets, gauges how well a bank's
management is using the company's assets. The
return on equity (ROE) figure tells a bank's
shareholders how much the institution is earning on their investments. R O E is calculated by
dividing a bank's net income by its total equity.
The ratio of ROA to R O E d e p e n d s on the bank's
equity capital-to-assets ratio, which tends to
fall as bank size increases. Analysts who want
to compare profitability while ignoring differences in equity capital ratios tend to focus
on ROA. Analysts wishing to focus on returns to
shareholders look at ROE.
The differences in these three ratios are illustrated by comparing the performance of Tennessee banks with those in Florida and Mississippi. The adjusted net interest of banks in
Florida exceeded that of banks in Tennessee in
1987, yet Tennessee banks had a higher return
on assets than banks in Florida (see Tables 13
and 17). The differences between the two ratios
may reflect changes in the banks' non-interest revenues and non-interest expenses, and changes
in their securities' gains or losses. Tennessee
banks lagged slightly behind Mississippi banks
in returns on assets but had higher returns on
equity, suggesting that Tennessee banks had a
lower equity capital-to-assets ratio than banks
in Mississippi (Table 18).
Adjusted Net Interest Margins. Adjusted net
interest margins fell nationwide in 1987, but the
drop is attributable largely to a sharp decline
among large banks (see Table 1). Adjusted net
interest margins at banks with assets in excess
o f $ l billion fell from 3.05 percent in 1986 to 2.00
percent last year. However, adjusted margins
improved at banks with assets below$500 million,
and banks in the $500 million to $ 1 billion range
experienced only a small drop in the ratio.
The key to the 1987 changes in adjusted net
interest margins is a change in banks' loan loss
provisions (Table 3). The large increase in provisions for Latin American debt sent loan loss
expense at large banks soaring to 1.82 percent
of interest-earning assets. Meanwhile, at banks
Table 1.
Adjusted Net Interest Margin as a Percentage of Interest-Earning Assets
(Insured commercial banks by consolidated
Year
All
Banks
0-$25
million
$25-$50
million
$50-$100
million
4.89
assets)
$100-$500 $500 millionmillion
$1 billion $1 billion +
4.74
4.74
3.34
3.62
4.31
4.73
4.65
1984
4.30
4.48
4.46
4.38
3.16
1985
3.63
4.00
4.15
4.26
4.31
4.22
1986
3.32
3.56
3.75
4.17
4.13
3.94
1983
1987
3.89
2.64
3.72
3.87
3.97
3.86
3.99
3.30
3.05
2.00
Source: Figures in all tables have been computed by the Federal Reserve Bank of Atlanta from data in "Consolidated Reports of Condition
for Insured Commercial Banks," and "Consolidated Reports of Income for Insured Commercial Banks," 1982-87, filed with each
bank's respective regulator.
I
FEDERAL RESERVE BANK OF ATLANTA
29
Table 16.
Tax-Equivalent Interest Revenue as a Percentage of Interest-Earning Assets
(Insured commercial banks by consolidated
Year
All
Banks
0-$25
million
1983
12.75
12.84
1984
1985
1986
1987
12.77
11.47
10.16
9.83
12.80
12.03
10.77
9.84
$25-$50
million
$50-$100
million
assets)
$100-$500 $500 millionmillion
S i billion
$1 billion +
12.66
12.55
12.69
12.47
12.62
12.66
12.55
12.55
12.87
11.61
11.33
11.94
11.83
11.59
10.74
10.71
9.89
10.47
9.96
10.75
9.95
9.99
12.86
9.92
9.78
Table 3.
Loan Loss Expense as a Percentage of Interest-Earning Assets
(Insured commercial banks by consolidated
Year
All
Banks
0-$25
million
1983
.62
1984
.68
.69
.91
1985
.79
1986
.91
1987
1.47
1.24
1.31
.93
$25-$50
million
$50-$ 100
million
assets)
$100-$500 $500 millionmillion
$1 billion $1 billion +
.60
.58
.75
.59
.52
.55
.65
1.00
.53
.57
.88
.72
.80
.73
.91
1.03
.66
.83
1.08
.79
.91
.60
.76
.87
1.82
Table 4.
Interest Expense as a Percentage of Interest-Earning Assets
(Insured commercial banks by consolidated
Year
All
Banks
0-$25
million
$25-$50
million
1983
8.24
7.27
7.32
1984
1985
1986
1987
30
8.46
7.05
5.92
5.72
7.58
6.79
5.90
5.19
7.63
6.80
5.90
5.22
$50-$ 100
million
assets)
$100-$500 $500 millionmillion
$1 billion
$1 billion +
7.23
7.30
7.55
7.37
8.87
7.56
7.61
8.98
6.69
5.83
5.18
6.56
5.70
5.16
6.59
5.73
5.22
7.26
5.99
5.96
ECONOMIC REVIEW, JULY/AUGUST 1988
Table 5.
Percentage Return on Assets
(Insured commercial banks by consolidated
Year
1983
1984
All
Banks
0-$25
million
.67
.85
.64
.60
$25-$50
million
.96
.79
$50-$ 100
million
$100-$500 $500 millionmillion
Si billion
$1 billion +
.96
.87
1985
.70
.63
.12
.11
.48
.23
.68
.50
.77
1987
.36
.70
.81
.77
.54
.88
.92
1986
assets)
.86
.54
.71
.67
.85
.65
.75
.62
.65
.60
-.12
Table 6.
Percentage Return on Equity
(Insured commercial banks by consolidated
Year
1983
1984
1985
1986
1987
All
Banks
0-$25
million
$25-$50
million
$50-$100
million
11.25
8.77
11.17
10.70
6.21
11.34
9.11
3.69
8.10
9.97
1.26
5.54
8.41
2.48
5.85
9.29
10.20
1.87
with assets below $1 billion, provisions in 1987
fell from high levels in 1986. The level of loan
loss provisions at banks with assets below $50
million and between $500 million and $ 1 billion
remains unusually high. The overall improvement in loan loss provisions may be caused in
part by some improvements in the agricultural
sector and by a bottoming out of the economies
of the energy-producing states.
Both interest revenues and interest expenses
as a percentage of interest-earning assets fell in
1987. Banks with assets below $ 1 bill ion showed
a drop in interest expense as a percentage of
interest-earning assets of over 50 basis points
(0.50 percent). However, the interest expense
ratio fell a mere 3 basis points at banks with
assets in excess of $1 billion.
Banks' Returns on Assets and Equity. The
return ratios for banks with assets in excess of $ 1
I FEDERAL RESERVE BANK OF ATLANTA
11.86
11.49
assets)
$100-$500 $500 millionmillion
Si billion
$1 billion +
12.05
12.27
11.73
9.06
10.01
11.46
11.11
12.66
10.51
10.54
12.53
9.18
11.92
8.91
-2.35
billion are negative, which caused the average
return ratios for all banks in the nation to b e
extremely weak. T h e biggest banks experienced an ROA of -0.12 percent and an R O E of
-2.35 percent. Profitability ratios at banks with
more than $ 1 billion in assets are unlikely to b e
this weak in 1988 unless they are forced into
another round of increasing loan loss allowances on troubled foreign debt.
Returns on assets and equity improved in
each of the four size categories of assets under
$500 million. The improved profitability at banks
with assets below $50 million is especially
significant since profitability at these banks had
deteriorated to very low levels. Unfortunately,
profit ratios are still weak for banks with less
than $50 million in assets, especially for banks
with assets below $25 million. The 2.48 percent
return on equity at banks with assets below $25
31
Table 16.
Adjusted Net Interest Margin as a Percentage of Interest-Earning Assets
(Insured commercial banks in the Southeast by consolidated
assets)
Year
All SE
Banks
0-$25
million
$25-$50
million
1983
5.11
4.87
4.79
4.92
4.94
4.77
4.65
4.64
5.00
5.37
4.53
4.81
4.67
4.82
4.64
4.23
4.19
4.21
4.52
4.68
4.11
4.31
4.20
3.79
4.16
4.47
4.29
3.78
4.21
1984
1985
1986
1987
4.24
$50-$ 100
million
4.44
$100-$500 $500 millionmillion
$1 billion $1 billion +
3,91
5.29
4.89
4.56
Table 8.
Tax-Equivalent Interest Revenue as a Percentage of Interest-Earning Assets
(Insured commercial banks in the Southeast by consolidated
AHSE
Banks
Year
0-$25
million
$25-$50
million
$50-$100
million
assets)
$100-$500 $500 millionmillion
$1 billion $1 billion +
1983
13.01
12.98
12.74
1984
12.81
12.61
13.08
13.51
12.98
12.98
12.87
12.80
12.79
12.76
13.22
10.71
11.15
11.11
12.32
12.18
11.90
11.90
11.62
10.23
10.21
11.10
10.85
10.30
10.24
10.86
10.47
10.28
1985
11.85
1986
1987
12.37
10.12
10.22
Table 9.
Loan Loss Expense as a Percentage of Interest-Earning Assets
(Insured commercial banks in the Southeast by consolidated
Year
1983
1984
1985
1986
1987
32
All SE
Banks
0-$25
million
.56
.88
.54
.75
.76
.90
.85
1.13
.79
.94
$25-$50
million
$50-$100
million
.62
.72
.66
.60
.87
.94
1.00
.90
.87
.63
assets)
$100-$500 $500 millionmillion
$1 billion $1 billion +
.53
.55
.48
.45
.69
.46
1.16
.60
.74
1.02
1.24
.70
.70
1.13
.80
ECONOMIC REVIEW, JULY/AUGUST 1988
Table 10.
Interest Expense as a Percentage of Interest-Earning Assets
(Insured commercial banks in the Southeast by consolidated
Year
1983
1984
1985
1986
1987
All SE
Banks
7.34
7.65
6.56
5.62
5.19
0-$25
million
7.24
7.45
6.66
5.82
5.16
$25-$50
million
7.19
7.56
6.79
5.90
5.25
$50-$100
million
7.15
7.55
6.73
5.89
5.23
assets)
$100-$500 $500 millionmillion
Si billion
$1 billion +
7.08
7.49
6.47
5.64
5.06
7.16
7.77
7.43
7.87
6.83
6.45
5.83
5.22
5.48
5.22
Table 11.
Percentage Return on Assets
(Insured commercial banks in the Southeast by consolidated
Year
All SE
Banks
1983
.96
1984
1985
1986
1987
.94
.91
.81
.79
0-$25
million
.67
.76
.74
$25-$50
million
.99
.92
.33
.90
.64
.38
.54
million is clearly inadequate for the long-run
survival of many of these banks, given the numerous alternative investment opportunities
available to their shareholders.
Southeastern Banks' Performance
Southeastern banks in every size category
except the $500 million to $l billion range outperformed their peers across the nation in
adjusted net interest margins, returns on assets,
and returns on equity (Tables 7, 11, and 12, respectively). In direct contrast to the national
figures, banks with more than $ 1 billion in assets
posted the highest ROA and R O E ratios in the
region; institutions with assets below $25 million recorded the lowest return ratios.
FEDERAL R E S E R V E BANK O F ATLANTA
$50-$ 100
million
.97
.96
.85
.78
.83
assets)
$100-$500 $500 millionmillion
$1 billion
$1 billion +
.96
.94
.98
.83
.96
.50
.78
.49
.70
.56
.98
.96
.99
.94
.86
The largest southeastern banks outperformed the rest of the nation by a substantial
margin with a regional ROA ratio of 0.86 percent
and R O E of 14.01. The superior performance in
the Southeast resulted largely from more limited
exposure to Latin American borrowers. However, loan losses as a percentage of interestearning assets increased for southeastern banks
with more than $ 1 billion in assets, whereas the
loan loss expense ratio fell in all other size
categories in the Southeast.
While southeastern banks with assets below
$50 million outperformed their peers across the
nation and showed improved profitability ratios
in 1987, returns on assets and equity remained
weak. The R O E of 3.38 percent for banks with
less than $25 million in assets is an inadequate
return to investors, and even the R O E of 5.95
percentat banks in the $25 million to $50 million
33
Table 12.
Percentage Return on Equity
(Insured commercial banks in the Southeast by consolidated
Year
All SE
Banks
0-$25
million
$25-$50
million
$50-$100
million
1983
13.37
6.85
11.16
12.03
13.11
1984
13.48
7.57
10.32
11.96
13.40
1985
13.11
7.18
10.01
10.29
13.05
1986
11.88
3.17
7.09
9.28
9.49
1987
11.35
3.38
5.95
9.69
10.21
category is, compared with other investment
alternatives, inadequate compensation for bank
stockholders. Both figures must improve if
banks in these categories are to continue to
operate independently.
A State-by-State Breakdown. Each of the six
southeastern states except Louisiana posted
ROA and R O E figures that exceed the national
averages. Again, the generally superior performance is due in large part to the absence of
significant Latin American and energy loan problems in five of the six states.
Georgia banks had the highest adjusted net
interest margins, ROA ratios, and R O E ratios in
the region. The highest adjusted margins occurred in spite of a moderately high loan loss
expense ratio and resulted primarily from a very
strong tax-equivalent interest revenue to interest-earning asset ratio. Georgia was the only
southeastern state to have increased its interest
revenue ratio.
Alabama banks turned in the second-best
adjusted net interest margins, ROA ratios, and
R O E ratios, though all three ratios were down
from 1986. This strong performance was due
partially to Alabama's having the lowest loan
loss ratio among the six southeastern states.
Profitability ratios fell in 1987 in part because
the interest revenue to interest-earning assets
ratio dropped more than the interest expense
ratio.
Banks in Mississippi reduced their ratio of
loan loss expense to interest-earning assets
and maintained the second lowest loan loss
34
assets)
$100-$500 $500 millionmillion
$1 billion
$1 billion +
13.87
16.57
11.48
16.59
7.64
16.74
8.79
15.78
7.52
14.01
expense ratio in the six southeastern states.
Their interest expense to interest-earning assets ratio also fell faster than their interest
revenue ratio, helping to boost their 1987 adjusted net interest margins. However, Mississippi banks showed lower returns on assets
and returns on equity despite their higher
adjusted margins.
The loan loss ratio also dropped for banks in
Tennessee. However, the interest revenue ratio
for the state dropped by more than the interest
expense ratio, which together produced a drop
in adjusted net interest margins. ROA and R O E
ratios of Tennessee banks also d r o p p e d in
1987.
Florida bankers reported a higher loan loss to
interest-earning assets ratio; banks in this state
had the second highest loan loss expense ratio
of the six southeastern states. Interest revenue
as a percentage of interest-earning assets fell by
more than the interest expense ratio, contributing to a fall in adjusted net interest margins. The
drop in adjusted net interest margins helped to
reduce Florida banks' ROA and R O E in 1987,
producing the second lowest levels in the six
Southeastern states.
Louisiana banks performed somewhat better
than in 1986 due largely to a significant decrease
in the loan loss provision to interest-earning
asset ratio. However, loan losses in Louisiana
remain at an extremely high level— l .57 percent
of interest-earning assets. Furthermore, Louisiana banks on average continued to have negative values for their ROA and R O E ratios.
ECONOMIC REVIEW. JULY/AUGUST 1988 J
Table 13.
Adjusted Net Interest Margin as a Percentage of Interest-Earning Assets
(Insured commercial banks in the Southeast by state)
Year
All SE
Banks
Alabama
5.11
4.96
1984
4.79
4.65
1985
4.53
4.92
4.23
4.24
1983
1986
1987
Florida
5.61
5.04
4.67
Georgia
Louisiana
Mississippi
Tennessee
5.62
4.88
4.14
4.35
5.30
4.33
4.12
4.60
3.57
4.73
4.67
2.43
4.13
4.44
4.31
4.89
3.01
4.23
4.40
4.57
4.38
5.20
4.36
4.18
Table 14.
Tax-Equivalent Interest Revenue as a Percentage of Interest-Earning Assets
(Insured commercial banks in the Southeast by state)
Year
All SE
Banks
1983
1987
Louisiana
13.38
13.36
12.55
13.10
13.35
12.65
12.00
11.85
1986
Georgia
12.82
12.98
1985
Florida
12.52
13.01
1984
Alabama
11.87
12.28
11.60
Mississippi
Tennessee
12.32
12.87
12.51
13.25
11.67
11.53
10.71
10.82
10.79
10.89
10.32
10.47
10.69
10.23
10.03
10.13
10.96
9.90
10.30
10.00
Table 15.
Loan Loss Expense as a Percentage of Interest-Earning Assets
(Insured commercial banks in the Southeast by state)
Year
All SE
Banks
Alabama
Florida
Georgia
1983
.56
.47
.42
.44
1984
.54
.39
.47
.45
1985
.76
.66
.56
.44
.67
.67
2.11
.44
.76
.72
1.57
1986
1987
.85
.79
FEDERAL R E S E R V E BANK OF ATLANTA
.60
Louisiana
.73
.83
1.38
Mississippi
Tennessee
.69
.79
.55
.62
.65
.59
.58
.72
.66
.64
35
Table 16.
Interest Expense as a Percentage of Interest-Earning Assets
(Insured commercial banks in the Southeast by state)
Year
All SE
Banks
Alabama
1983
7.34
7.39
7.48
1984
7.65
1985
6.56
6.47
5.19
Florida
7.35
7.59
5.15
1986
1987
5.62
5.65
6.54
5.55
5.06
Georgia
7.30
7.59
6.52
5.55
5.36
Mississippi
Louisiana
7.49
6.93
7.85
7.49
Tennessee
7.72
8.07
6.58
6.66
6.65
5.32
5.34
5.18
Mississippi
Tennessee
5.68
5.77
5.67
Table 17.
Percentage Return on Assets
(Insured commercial banks in the Southeast by state)
Year
All SE
Banks
Alabama
Rorida
1983
.96
1.12
.96
.94
1.11
.91
1.14
.91
1.20
.87
1.07
.76
1.13
1984
1985
1986
1987
.81
.79
1.22
1.08
.87
Distribution of Bank Profitability
Banks in the Southeast and across the United
States have clearly become less profitable in
the past few years, with smaller banks experiencing the greatest decline in profitability.
However, these statistics do not provide information on profitability gains and losses within
the size categories. For example, perhaps only
the most profitable banks were unable to sustain their earnings, while the majority of banks
were unaffected by the changing environment.
Although slumping earnings would generally
displease owners and managers of highly profitable banks, moderately reduced profitability at
these banks should pose no public policy problems. On the other hand, if the least profitable
36
Georgia
Louisiana
1.11
1.01
1.20
.78
.37
-.20
-.02
.83
.90
1.01
1.01
.90
.66
.84
.94
.97
.89
banks have suffered most of the decline in profitability, the drop could spell a potential increase in the number of problem and failed
banks. A growing incidence of troubled banks
not only raises concern about the safety and
soundness of the banking system but also
places continuing stress on the Federal Deposit
Insurance Corporation.
One way of analyzing the distribution of bank
profitability is to study the ROA figures at
various profitability percentiles. This study
focuses on the profitability of banks across the
nation at the 75th, 50th, and 25th percentiles in
ROA. Banks in the 75th percentile were more
profitable than three-fourths of the institutions
analyzed. Banks in the 50th percentile had profitability higher than half the banks. Banks in the
25th percentile were least profitable, with ROAs
ECONOMIC REVIEW, JULY/AUGUST 1988
Table 18.
Percentage Return on Equity
(Insured commercial banks in the Southeast by state)
Year
1983
1984
Ail SE
Banks
Alabama
13.37
13.48
1985
13.11
1986
11.88
1987
11.35
13.73
13.84
14.97
15.19
13.29
Florida
14.56
14.50
13.93
14.20
12.25
higher than only the bottom 25 percent of the
banks studied. The ranking was done separately
for each year, and so some banks shifted to different profitability ranges over the five-year
period analyzed.
Profitability at the weakest banks (in the 25th
percentile) improved from 1986 to 1987 in every
size category below$500 million. However, profits at the 25th percentile remain very weak for
banks with less than $50 million in assets. Onequarter of the banks with assets below $25 million earned an ROA of 0.01 percent or less. This
weak performance suggests continued consolidation of the banks in this size category in
the future.
ROA ratios at the 25th percentile fell for banks
with assets above $500 million. The sharp drop
in the 25th percentile ROA for banks with more
than $l billion in assets was not accompanied
by a substantial drop in the ROA figures at the
50th or 75th percentile. This statistic further
underscores the fact that only a small number of
banks posted large increases in loan loss expenses associated with Latin American debt.
However, the amount of loan loss additions at
these banks was so large that they skewed the
entire industry's average returns for 1987.
T h e m e d i a n (50th percentile) ROA ratio
showed little change last year—a maximum of
three basis points—for banks in all size categories. The median profitability ratios remained
at historically low levels for banks with assets
below $50 million but are in a much stronger
position for banks with more than $100 million
in assets.
I FEDERAL R E S E R V E BANK OF ATLANTA
Georgia
Louisiana
Mississippi
Tennessee
16.16
12.64
17.19
11.22
9.57
9.63
12.23
12.44
16.50
4.60
13.92
13.71
-2.66
13.59
13.67
11.81
12.38
18.45
16.23
-.27
The ROA ratios for banks in the 75th percentile are generally down from 1986. However, no
drop in the ROA ratio exceeds the 0.06 percent
drop recorded for institutions with assets between $25 million and $50 million.
Conclusion
Bank profitability ratios, excluding those of
the biggest banks, generally improved by a
small margin from 1986 to 1987. However, 1987
profitability ratios remain weak for several
categories of banks, especially banks with
under $50 million in assets. Banks with less than
$25 million in assets earned an average ROA of
0.23 percent, and the 25 percent of the banks in
this size category with the lowest ROA had an
ROA of 0.01 percent.
One category showing a significant drop in
1987 profitability ratios is the large banks, which
substantially increased their provisions for troubled loans to certain foreign borrowers. The
number of banks that increased their provisions
appears to be small, but the magnitude of the
increase in their loan loss allowances was so
large that the return on assets of banks with
assets in excess of $1 billion fell from 0.65 percent in 1986 to -0.12 percent in 1987.
Banks in the Southeast continue to outperform their peers across the nation, but Louisiana banks still experience problems, increasing
profitability ratios in 1987 but still posting
losses for the year.
37
Table 19.
Percentage Return on Assets
Table 20.
Percentage Return on Assets
(Insured commercial banks with assets
below $25 million)
(Insured commercial banks with assets
of $25 million to $50 million)
Percentile According to Profitability
Percentile According to Profitability
Year
75%
50%
25%
Year
75%
50%
25%
1983
1.50
1.06
.55
1983
1.46
1.10
.72
1984
1.36
1985
1.29
1986
1.13
1987
1.10
.93
.82
.66
.69
.35
.06
-.25
.01
Table 21.
Percentage Return on Assets
(Insured commercial banks with assets
of $50 million to $100 million)
1984
1985
1986
1987
75%
1983
1.40
1984
1985
1986
1987
1.32
1.35
1.29
1.26
1.34
1.24
1.18
1.00
.97
.84
.85
.60
.50
.29
.39
Table 22.
Percentage Return on Assets
(Insured commercial banks with assets
of $100 million to $500 million)
Percentile According to Profitability
Year
1.34
Percentile According to Profitability
50%
25%
Year
75%
50%
25%
1.08
.74
1983
1.27
.97
.66
.63
1985
1.29
1.02
.56
1987
1.24
.96
1.02
1.04
.95
.95
.70
.50
1984
1986
1.26
1.27
.99
.96
.71
.69
.54
.56
Table 23.
Percentage Return on Assets
Table 24.
Percentage Return on Assets
(Insured commercial banks with assets
of $500 million to $1 billion)
(Insured commercial banks with assets
over$1 billion)
Percentile According to Profitability
Percentile According to Profitability
Year
75%
50%
25%
Year
1983
1.10
.88
.60
1983
1984
1985
1986
1987
38
1.19
1.19
1.19
1.20
.91
.91
.93
.94
.62
.64
.57
.48
1984
1985
1986
1987
75%
.98
1.05
1.10
1.10
1.08
50%
25%
.75
.46
.86
.54
.88
.59
.90
.60
.87
.30
ECONOMIC REVIEW, JULY/AUGUST 1988
Accounting for Troubled Foreign Loans
The increase in loan loss provisions at major
banks had a pronounced effect on reported 1987
bank profitability. Banks with more than $1 billion
in assets accounted for 82 percent of the assets
and 78 percent of the loan losses of the banks in
the 1986 sample. These very large banks accounted for 83 percent of the assets and 92 percent of
the loan losses in 1987. Another way of gauging the
effect of loan loss provisions is to examine the
ratio of net income before loan loss provisions,
extraordinary items, and taxes to the banks' total
assets in 1986 and 1987.1 This ratio improved from
1986's 1.52 percent for the largest banks to 1.55
percent in 1987. However, loan loss expense as a
percentage of total assets also more than doubled,
from 0.71 percent in 1986 to 1.53 percent, in 1987.
As a consequence, net income before taxes and
extraordinary items fell from 0.81 percent in 1986
to 0.02 percent in 1987.
This box seeks to address two issues: why did
the large banks not provide substantial increases
in their loan loss allowances prior to 1987, and
what is the effect of the increase in allowances? An
understanding of how banks account for loan
losses would be helpful before addressing these
questions.
Accounting Procedures
After every period a bank examines its existing
loan portfolio and estimates the expected losses
on outstanding loans. The loan loss allowance (on
the bank's balance sheet) is then increased to
match expected losses, with the amount of the
increase charged against income as a provision for
possible loan losses. Losses on individual loans
during the next accounting period are charged
against the loan loss allowance but are not immediately reflected in the bank's income accounts.
Similarly, if the bank recovers more than expected
on loans that were previously charged off, the
bank's accountants add the amount of the recovery back to the loan loss allowance. At the end
of the period, the amount in the loan loss allowance is equal to its beginning-of-period value, less
any charge-offs and plus any recoveries. The bank
then begins the cycle again by determining expected losses on loans and comparing that with its
loan loss allowance.
This procedure may seem needlessly complicated; a far simpler approach would be to
recognize loan losses when the loan is written off.2
One reason for following the more complicated
I FEDERAL R E S E R V E BANK O F ATLANTA
procedure, though, is that it accords with the
important accounting principal of conservatism,
that when "reasonable support exists for alternative methods . . . the accountant should select the
accounting option with the least favorable effect
on net income and financial position in the current
period." 3 Recognizing expected loan losses before they occur is more conservative than waiting
until the loan is written off. The more complicated
procedure is also required to meet the needs of
the accrual method of accounting, which is used by
all large banks. Banks following the accrual method recognize revenue in the period when the payment is earned, regardless of when it is received.4
The accrual method also requires that after revenue associated with a period is determined, the
costs associated with that income must also be
recognized. For institutions in the business of
making loans, one of the expenses stems from the
fact that some of their loans will not be fully repaid.
Therefore, accrual accounting requires that the
bank anticipate suffering some losses in the
loan portfolio.
The responsibility for a bank's loan loss allowances rests with its management. The managers of
an organization are in the best position to evaluate its financial condition, which is typically communicated to existing and potential shareholders
in its annual financial statements. A bank's auditors may suggest increases in the allowance, but
they cannot force management to follow such suggestions. Bank regulators may compel managers
to increase their loan loss allowances if, in the
regulators' opinion, the allowance is inadequate.
Thus far, federal bank regulators have encouraged
banks to review careful ly their allowance for losses
but have not ordered large increases in loan loss
allowances.
Why Are the 1987 Writeoffs So Large?
The problems that at least some Latin American
countries would have in repaying their debt have
been obvious since the problems with Mexican
debt emerged in August 1982. Yet until 1987, most
major banks did not significantly increase their
loan loss allowances to account for their exposure
to Latin American debt. Why did many large banks
take so long to increase their loan loss allowances?
The banks' reluctance to increase their allowances could be justified on the grounds that the
losses might not occur. The troubled foreign
39
borrowers were seeking to extend the term of their
repayments but none had repudiated its outstanding debt. Thus, the banks could still receive
repayment in full. The problem with this explanation for the failure to increase allowances is that it
mistakes the purpose of the loan loss allowance.
The loan loss allowance exists to account for
losses that may be reasonably expected on a bank's
existing loan portfolio; those portions of loans
that have incurred actual losses should be written off.
The expected amount of losses is open to some
question, but the market clearly expected banks
to absorb some losses on their Latin American
debt. The secondary market in Latin American
debt has priced the debt of individual countries at
a discount to their face values. In some cases these
discounts have been substantial. The secondary
market may be criticized as being too thin to provide reliable prices, but the general conclusion
that some losses are expected on loans to some
Latin American countries is supported by the
bank equity markets. Informal examination of bank
stock prices suggests that banks with substantial
exposure to Latin American countries have traded
at a large discount to their book values for several
years. On a more formal level, Robert F. Brunerand
)ohn M. Simms, )r. (1987) show that within six days
of the 1982 announcement that Mexico would suspend principal repayments, the market was discounting bank stock prices based on each bank's
loans to Mexico.
Another explanation for the delay in increasing
allowances is that many banks could not afford to
increase their provisions because their exposure
to Latin American debt exceeded their capital.
Some banks would have been left with no capital
had they increased their loan loss allowances. One
response to this explanation is that banks need
not and should not have increased their provisions to cover all of their troubled Latin American
debt. The financial markets have not been indicating that the troubled loans were worthless, merely
that the face value of the loans overstated their
economic value. Most banks could have afforded
some increase in their allowances.
Perhaps the best justification for the delay is
that increasing provisions may have had an adverse effect on the negotiations with troubled
Latin American borrowers. An increase in loan loss
allowances may have encouraged some countries
to seek better terms than the banks were prepared to offer. An increase in allowances may also
have discouraged certain banks from participating
in the restructuring of outstanding debt. Some
40
banks with relatively small exposure may have
been unwilling to provide additional loans at a
time when they were increasing their allowances
on existing loans. This justification raises a troubling question: is the purpose of accounting statements to provide an unbiased "scorecard," or is it
one more tool to be manipulated?
What fs the Significance
of the Increased Allowance?
The increase in loan loss allowances has very little direct effect on banks or borrowers, in some
sense this increase was merely a set of accounting
entries, but these entries potentially have significant indirect effects. The market clearly attached
significance to the action. James J. Musumeci &nd
loseph F.Sinkey.Jr. (1988) report significant abnormal returns to a portfolio of ten money-center
banks the day after Citicorp announced its increased loan loss allowance.
Loan loss allowances are sometimes referred to
as loan loss reserves. Unfortunately the term loan
loss reserves may create the mistaken impression
that a bank sets aside funds (cash) in reserve to
cover its loan losses. An increase in the loan loss
account, however, does not directly cause any
change in the allocation of a bank's assets. Loan
loss allowances merely reduce the netvalue of the
bank's loans on its accounting records.
An increase in the loan loss allowance may
indirectly cause a bank to reduce its dividends or
seek additional equity. The federal government
and many state governments restrict bank dividends based on the bank's current earnings and
recent retained earnings as reported on their
financial statements.5 An increase in loan loss provisions reduces a bank's income and hence its
ability to pay a dividend. Large increases in
allowances will also decrease a bank's equity capital as reported in its accounting records and possibly trigger regulatory demands for additional
equity. However, the regulators can already demand additional equity for organizations with a
substantial volume of troubled loans, regardless
of the reported value of the bank's equity.
The increase in banks' loan loss allowances has
no direct effect on the Latin American debtors.
The banks did not waive their right to repayment
on any loans, and they still hope to be repaid in
full. Bank managers may be psychologically more
prepared to make concessions on the loans since
the losses were acknowledged in an earlier period
(in part because additional concessions would
have less of an impact on their bonuses). However,
ECONOMIC REVIEW. JULY/AUGUST 1988
J
the provisions could have the opposite effect if
they made the banks feel less financially vulnerable
to pressure from the Latin American borrowers.
Though they increased their loan loss provisions, banks were not able to deduct from taxable income an amount equivalent to the increased provision. The Tax Reform Act of 1986
changed the rules on the accounting for loan
losses. Banks with assets in excess of $500 million
may reduce their taxable income only by the
amount of loan losses they actually incur in a year.
Thus, a large bank can recognize losses on Latin
American debt for tax purposes only when it either
writes off part of the loans or sells some of its loans
at a loss.
In summary, many U.S. banks, particularly larger
banks outside the Southeast, waited until last year
to increase substantially their loan loss allowances on foreign, especially Latin American, loans.
Though this increase is primarily an accounting
adjustment with little direct effect on banks or
borrowers, indirect effects may result. The impact
of these adjustments on bank profitability will
likely be lessened in 1988, unless the country's
larger banks continue increasing loan loss allowances on troubled foreign debt.
Notes
'A before-tax ratio is used to avoid potential differences
in the tax treatment of loan loss provisions at different banks.
2 The
new tax law requires the simpler treatment of
losses for tax purposes.
3 See Meigs, Mosich, Johnson, and Keller (1974): 22.
4 For example, suppose a bank makes a three-month
loan on November I, 1987, with no interest payment
due until February J, 1988. The bank would recognize
two months of interest revenue (from November I
through December 31) in its 1987 income and one
month of interest revenue in its 1988 income.
National banks are prohibited from making dividend
payments in excess of the current year's income plus
the sum of the prior two years' retained earnings. State
chartered banks face limitations imposed by state law
and may also be limited by the actions of their federal
bank supervisor.
Appendix
The data in this article were taken from reports
of condition and income filed with federal bank
regulators by insured commercial banks. The sample consisted of all banks that had the same identification number at the beginning and end of each
year. The number of banks in the 1987 sample
was 12,390.
The three profitability measures used in this
study are defined as follows:
Adjusted Net Interest Margin =
Expected Interest Revenues - Interest Expense
Average Interest-Earning Assets
Return on Assets =
Net Income
Average Consolidated Assets
I FEDERAL RESERVE BANK O F ATLANTA 43
Return on Equity =
Net Income
Average Equity Capital
Average interest-earning assets and average
equity capital are derived by averaging beginning-,
middle-, and end-of-the-year balance sheet figures. The expected interest income component to
net interest margin incorporates two significant
adjustments from ordinary interest income. The
lesser of revenue from state and local securities
exempt from federal tax and the bank's net income
is divided by I minus the bank's marginal federal
tax rate, and loan loss expenses are subtracted
from interest income.
Notes
'in this study the Southeast refers to the six states that are
entirely or partially within the Sixth Federal Reserve District: Alabama, Florida, Georgia, Louisiana, Mississippi,
and Tennessee.
2 The revenue, expense, and profitability figures presented
are generally similar to those presented in prior bank profitability studies published in this Economic Review (see
Wall 119871 for the most recent study). The figures are not
identical because reporting errors by banks are continually
being found and corrected. In addition, the interest rev-
enue as a percentage of interest-earning assets ratio and
adjusted net interest margins may differ from prior years
owing to the correction of errors in the treatment of taxexempt interest revenue.
3 For
example, the interest rates on credit cards have been
substantially higher than the rates on prime commercial
loans, but the loan losses on credit cards have also been
larger. Loan losses on credit cards were 1.25 percent of the
credit card volume in 1985, according to Weinstein (1985).
References
Bruner, Robert F., and |ohn M. Simms, )r. "The International
Debt Crisis and Bank Security Returns in 1982."Journal of
Money, Credit and Banking 19 (February 1987): 46-55.
Meigs, Walter B., A.N. Mosich, Charles E. Johnson, and
Thomas F. Keller. Intermediate Accounting. 3d ed. New
York: McGraw-Hill, 1974.
Musumeci, lames J., and Joseph F. Sinkey, Jr. "The International Debt Crisis and Bank Security Returns Surrounding Citicorp's Loan-Loss-Reserve Decision of May 19,1987."
42
Federal Reserve Bank of Chicago, Conference on Bank
Structure and Competition, 1988, forthcoming.
Wall, Larry D. "Commercial Bank Profitability: Some Disturbing Trends." Federal Reserve Bank of Atlanta Economic
Review 72 (March/April 1987): 24-36.
Weinstein, Michael. "Another Good Year is Expected for
Bank Credit Cards, Although Prices Are Under Pressure
and Losses Are Up." American Banker, December 31,
1985, 3.
ECONOMIC REVIEW, JULY/AUGUST 1988
Book Review
Hard Heads, Soft Hearts
by A l a n S. B l i n d e r
R e a d i n g , M A : A d d i s o n - W e s l e y P u b l i s h i n g , 1987
236 p a g e s . $17.95.
Alan Blinder introduces Hard Heads, Soft
Hearts, his extensive discussion of economic
policymaking, with an extremely discouraging
generalization about the "remarkably systematic perversity in the way economic advice is
used in policymaking." However, his "Murphy's
Law of Economic Policy" appears to be well supported in a review of recent economic history.
The "law" reads, "Economists have the least
influence on policy where they know the most
and are most agreed; they have the most influence on policy where they know the least and
disagree most vehemently" (p. I), and is accompanied by O'Connor's Corollary: "When confl icting economic advice is offered, only the worst
will be taken" (p. 2). Recent events provide no
shortage of examples illustrating these principles, and Professor Blinder, the Gordon S.
Rentschler Memorial Professor of Economics at
Princeton University, gives lively, lucid descriptions of these economic policy debacles. Still,
the book is optimistic, on balance, about the
prospects for improving both economic policymaking and, subsequently, economic conditions.
Hard Heads, Soft Hearts should find wide support in the economics community.
The body of this book is a series of persuasive
arguments that show how profoundly flawed
FEDERAL R E S E R V E BANK O F ATLANTA
policy came to be, and how it could be changed
to yield greatly improved results. As Professor
Blinder sees it, the greatest obstacles to better
economic policy are "ignorance, ideology, and
interest groups" (p. 197). Some combination of
the three, he claims, is responsible for the
federal budget deficit crisis, the recent increase
in protectionist legislation, and the disappointing results of the environmental pollution
abatement legislation of the 1970s, among other
societal ills. The ravages of ignorance receive
the most attention; Blinder feels that ignorance
may be the one obstacle on which economists
can have the greatest constructive impact,
because increased public knowledge about
economic policy will lessen the influence of
ideology and interest groups.
Few economists or public policy analysts will
disagree with Professor Blinder on these points.
In fact, despair over the public's general contempt for the facts unites otherwise contentious
parties. Consider that James David Barber, a
Duke University political scientist typically supportive of liberal policy initiatives, and Paul
Craig Roberts, a promulgator of supply-side economics, seem of one mind on this issue. Barber
comments, "We've had a lot of anti-empiricism
in national discourse. Political discourse has
43
been reduced to a balance of sentiments." 1 In
the same vein, Roberts states, "Economic policymaking is hopeless if facts cannot penetrate
public discourse." 2
Blinder faults economists, among others, for
this pervasive ignorance. He argues that while
bad policy is based on "gross misunderstanding
of elementary economics, utter disregard for the
facts, or both," economists have failed to convince the public, and so the policymakers, that
good policy tends to be "too complex to be
emblazoned on a T-shirt," and that good policy
is, in fact, "|I|ess crisply defined and full of
qualifications" (p. 9).
Not only have economists been ineffective
educators, they are also guilty of embracing
ideology. Professor Blinders own position is
clear. In this book, the best policy rejects the
extreme prescriptions of monetarism, rational
expectations, and especially supply-side economics, in favor of a broadly based and proven
Keynesian approach. Unfortunately, Professor
Blinder trivializes and dismisses the contributions of these other models. However, the
practical Keynesian view he takes has benefited
in no small way from the broadening forced
upon it by these competing approaches. In fact,
the Keynesianism he describes does not much
resemble the original animal. It is an eclectic
mix, having been forced to acknowledge the
critical importance of monetary policy, expectations formation, and the incentive structure
built into tax rates.
The cold-blooded discussion of policy failures and limitations at the outset of the book
gives way to a rigorous defense of economics as
a discipline able to promote the general welfare
of all U.S. citizens. That is, economics is an ivory
tower discipline, but one that operates in the
real world. This discipline can be most valuable
when the high road of theory meets the low road
of extensive practical experience.
The author's strategy in Hard Heads, Soft
Hearts is to introduce the reader to two of the
most fundamental concepts of economic analysis: efficiency and equity, both of which are
generally acceptable as reasonable goals for
public policy. Efficiency requires that resources
(for example, labor, capital, clean air, and oil) not
be wasted. Equity requires that resources be
distributed fairly. Taken in turn, each principle
is uncontroversial. Clearly, however, a policy
44
that advances one of these goals often hinders
the other. The obvious example is tax policy, in
that the distortionary or disincentive influences
of tax policies which redistribute income may
discourage the most efficient use of resources.
Professor Blinder also shows why the free
market system, which he rigorously supports,
tends to produce inequities. He does not compare the degree of inequality in a free market
economy with that of a command economy because he asserts, without argument, that the
free market is superior. Although the system of
rewards and incentives that produces the most
efficient outcome "shows no mercy," Blinder
considers this an asset.
Next comes a sly tactical maneuver. B y discussing policy changes that increase both equity
and efficiency, Professor Blinder avoids some of
the uglier problems of the trade-off between
"T/ie cold-blooded discussion of policy failures and limitations ... gives way
to a rigorous defense of economics as
a discipline able to promote the general welfare of all U.S. citizens. "
these two concepts that bedevil so much of the
economic policy debate. Surprisingly, many
important policies are not eliminated by these
narrow criteria.
Professor Blinder's preferences and biases
are very much on the side of weighting inequity
over inefficiency as Bad Things, and he admits
this forthrightly. The waste associated with unemployment is much more passionately condemned than the costs of inflation. This assessment is clearly reflected in the author's
willingness to accept more inflation for less
unemployment. By extension, he argues that
the cost of the anti-inflation policies of the early
1980s was unconscionably (although not unnecessarily) high. This section of the book
(chapters 2 and 3) is high-minded and compassionate, but gives little attention to the distinction between stable and rising inflation
rates, a distinction that played a major role in
ECONOMIC REVIEW. JULY/AUGUST 1988 J
deciding upon the tough policies earlier in
this decade.
In his discussion of the cost of low, stable
inflation Blinder suggests that with indexation
even these moderate costs could be reduced
considerably. However, in the current institutional and cultural setting in the United States,
inflation tends to accelerate, not remain constant, once it is widely recognized. Rising moderate inflation soon becomes decidedly immoderate, and the attendant costs and distortions are immensely destructive. The distinction between low inflation and rising inflation is
at once important in theory and fleeting in practice. The former soon becomes the latter. Thus,
much of Professor Blinders argument about the
minimal costs of inflation, and the attendant
condemnation of the anti-inflation policies of
the early 1980s, seems to rest on a narrow prece-
"T/ie discussion of environmental policy
is almost heartbreaking in its description of opportunities lost "
dent not supported by recent history.
The discussion of the inequities and inefficiencies of recent anti-inflation policy is probably the most controversial part of the book.
Surprisingly, Professor Blinder uses a clearly
contentious issue to illustrate the economics
profession's consensus on the equity/efficiency
principle. Equally surprising is that this illustration does not materially weaken the remainder
of his work, possibly because his other examples involve issues where strong professional
solidarity exists. Blinder also takes on protectionism, pollution control, and tax reform. In
each case he shows how the principles of
efficiency and equity and the prescriptions of
the overwhelming majority of the economics
profession have often been ignored in policymaking to the detriment of the common good.
In the best part of the book, Blinder discusses
the principles of free trade and the mindless,
FEDERAL R E S E R V E BANK OF ATLANTA
needless waste of protectionism. The clear
exposition of the idea of comparative advantage
is sophisticated enough to allow Professor
Blinder to debunk a series of protectionist arguments without preaching on the costs of protectionism. But then he does so, with a flurry of
statistics illustrating the colossal waste of such
policies.
For example, Professor Blinder describes
how the "voluntary" export restraints imposed
on the Japanese automobile industry in 1981
saved a number of jobs in the U.S. auto industry
and increased profits for auto industry shareholders. A reasonable estimate of the bill for
this relief is $ 13 billion; about $8 billion went to
domestic producers and roughly $5 billion went
to the Japanese auto industry. This $13 billion
represents the additional cost to U.S. consumers of cars purchased in the United States in
1984 and 1985 only. The cost per job saved is
variously estimated between $105,000 and
$ 160,000. Did any individual auto worker benefit
to the tune of $ 160,000? The case of the voluntary export constraints is an example of the
general rule that the benefits and costs of protectionism are distributed very differently:
"trade protection typically imposes heavy costs
on consumers in order to secure smaller benefits for producers" (p. 118).
The discussion of environmental policy is
almost heartbreaking in its description of
opportunities lost. Professor Blinder shows how
the imposition of property rights on otherwise
free resources (clean air and water) would make
society recognize how valuable and scarce they
are. Currently, most pollution abatement laws
are one of two types: ambient air and water
standards that set the minimum acceptable
quality of air or water after a plant has finished
using it, and effluent or emission standards that
specify the amounts of a pollutant that may be
discharged from a particular source. Apparently,
many of the standards now on the books are not
being met because companies find it cheaper
to "invest in litigation than in pollution abatement equipment" (p. 144). Professor Blinder
contends that if the rights to use air and water
resources were licensed, or auctioned, these
precious resources would be used more rationally and with fewer harmful results. Without
using economist's jargon, he shows that by forcing industry to internalize the costs that are
45
currently externalized (all of society-not just
industry—pays for and suffers from dirty air and
water), much less pollution would occur. Additionally, companies would have an incentive to
minimize pollution, since pollution control
costs would become an element of production
costs. Conservative estimates of the economic
gain from a switch to a system of fees or pollution permits from the current labyrinth of regulations are huge, on the order of $23 billion per
year. Have any experiments with pollution permits ever been tried? Yes, but only a few.
Limited evidence indicates that the potential
gains are indeed as substantial as the estimates suggest.
The disheartening rejection of economic
principles seen in protectionism and environmental policy is not universal. In chapter 6 of
Hard Heads, Soft Hearts, Professor Blinder
recounts the triumph of equity and efficiency in
the "improbable saga of tax reform." Readers
are shown how a system that in the past served
as an example of the power of the few (special
interests) over the many was used to affect tax
reform, enhancing both equity and efficiency.
Unfortunately, economic principles prevail in
only this one chapter; in many, many unwritten
chapters, they do not.
The book ends with a prescription to reverse
this situation. Professor Blinder calls for pragmatism to fight the ideology that harbors untruths, for the support of forces to counter the
influence of special interests, and for education.
Economists can realistically address only the
last of these remedies. Unfortunately, they have
46
failed to do their best to educate the electorate
and the elected on the benefits of good economics as much as the public has failed to use
the advice economists have offered. Economists know that economics is an extremely
powerful tool that can be used in almost all
areas of public policy. However, this discipline
is not very accessible to the public, let alone the
policymakers. As Blinder writes, "economic
illiteracy is widespread."
Hard Heads, Soft Hearts stands as an example of the sort of book that will help raise the
level of economic discussion among noneconomists. Blinders work can be part of the
solution; his book is gracefully written and
clearly reasoned, with its mild ideology worn on
its sleeve. It is cold-bloodedly realistic but
also optimistic, two traits that economists will
have to adopt to revoke "Murphy's Law of Economic Policy."
Mary Susan Rosenbaum
The reviewer is the Research Officer in charge of the mac-
ropolicy group of the Atlanta Fed's Research
Department.
Notes
1
Peter Kilburn, "The S u d d e n Wilting of Reagan's Rosy
Economy," The New York Times, Sunday, July 27, 1986,
sec. 3.
2 Paul
Craig Roberts, "Beneath the Twin Towers of Debt,"
Wall Street journal, October 28, 1986.
ECONOMIC REVIEW. JULY/AUGUST 1988 J
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47
FINANCE
iri
1988
JUNp
$ nil lions
UNITED STATES
Commercial Bank Deposits
Demand
NOW
Savings
Time
1988
MAY
1988
APR
1,809,388 1,779,243 1,792,663
372,660
358,816
357,752
173,790
170,359
170,782
522,868
513,614
520,361
787,504
780,451
779,940
1987
JUN
1987
MAY
ANN.
I
CHG.(*)
1987
APR
1,678,133 1,660,331 1,677,942
359,026
351,237
358,994
155,818
152,850
159,216
511,724
509,119
517,511
687,310
678,900
676,670
+ 4
+12
+15
SOUTHEAST
Commercial Bank Deposits
Demand
NOW
Savings
Time
218,949
42,668
24,251
58,560
98,453
215,993
41,032
23,722
57,959
97,547
217,791
41,866
24,197
58,891
97,066
201,102
40,994
22,025
57,745
84,135
199,060
40 , 350
21,759
57,643
83,016
201,584
41,491
22,633
58,813
82,588
ALABAMA
Commercial Bank Deposits
Demand
NOW
Savings
Time
22,372
4,245
2,587
4,895
11,228
21,914
3,999
2,523
4,813
11,057
22,255
4,193
2,499
4,906
11,154
20,352
4,102
2,148
4,623
9,885
19,954
4,025
2,102
4,579
9,700
20,265
4,092
2,158
4,658
9,738
+10
+ 3
+20
+ 6
+14
FLORIDA
Commercial Bank Deposits
Demand
NOW
Savings
Time
86,648
16,506
10,946
27,413
33,581
85,312
16,081
10,728
27,137
33,055
86,201
16,366
10,974
27,612
32,867
78,387
16,009
10,015
27,061
26,900
77,652
15,825
9,917
26,908
26,523
79,043
16,420
10,364
27,476
26,552
+11
+ 3
+ 9
+ 1
+25
GEORGIA
Commercial Bank Deposits
Demand
NOW
Savings
Time
35,884
9,194
3,407
9,328
15,689
35 , 254
8,655
3,310
9,189
15,584
35,191
8,865
3,377
9,341
15,165
32,265
8,545
3,097
8,972
13,040
LOUISIANA
Commercial Bank Deposits
Demand
NOW
Savings
Time
28,145
5,123
2,403
8,033
13,069
28,089
5,002
2,392
8,032
13,069
28,366
4,987
2,434
8,146
13,144
27,309
4,963
2,250
7,955
12,488
27,404
4,931
2,221
7,980
12,626
27,758
5,035
2,299
8,116
12,663
+
+
+
+
+
MISSISSIPPI
Commercial Bank Deposits
Demand
NOW
Savings
Time
15,200
2,433
1,546
2,991
8,571
15,054
2,350
1,536
2,972
8,472
15,124
2,393
1,585
2,992
8,454
14,145
2,357
1,398
3,066
7,507
14,034
2,338
1,400
3,102
7,416
14,188
2,473
1,466
3,161
7,350
+ 7
+ 3
+11
- 2
+14
TENNESSEE
Commercial Bank Deposits
Demand
NOW
Savings
Time
30,700
5,167
3,362
5,900
16,315
30,370
4,945
3,233
5,816
16,310
30,654
5,062
3,328
5,894
16,282
28,644
5,018
3,117
6,068
14,315
28,189
4,928
3,042
6,039
14,021
28,488
5,011
3,164
6,177
13,964
+ 7
+ 3
+ 8
- 3
+14
BHB
:
31,827
8,303
3,077
8,963
12,730
+ 4
+10
+ 1
+17
#
t%ÊÊÊ
31,842
8,460
3,182
9,225
12,321
WÊÊÊKÊÊÊBtKÊKBÊHÊSKÊSSÊÊ
+11
+ 8
+10
+ 4
+20
3
3
7
1
5
NOTES:
d
3 3 r e e x t r a
i t ? d f r P m t h e F e d e r a 1 Reserve Report of Transaction Accounts, other Deposits and Vault Cash
fr^SKf" f
(FRZ900), and are reported for the average of the week ending the 1st M o n d a y of the month. Most recent data, reported
institutions with over $30 million in deposits and $3.2 million of reserve requirements as of D e c e m b e r 1987, represents 95 %
of deposits in the six state area. The major differences between this report and the "call report" are size, the treatm ent of
interbank deposits, and the treatment of float. The total deposit data generated from the Report of Transaction Accounts
eliminates interbank.deposits by reporting the net of deposits "due to" and "due from" other depository institutions. The
Report of Transaction Accounts subtracts cash in process of collection from d e m a n d deposits, while the call report does
n
£ | \ ™ e Southeast data represent the total of the six states. Subcategories were chosen on a selective basis and do not
add to total,
p - preliminary
* - Most recent month vs. year-ago month
48
ECONOMIC R E V I E W , JULY/AUGUST 1988
EMPLOYMENT
APR
1988
MAR
1988
APR
1987
ANN.
%
CHG
120,264
113,905
6,359
119,957
112,867
7,090
119,335
111,041
7,306
+ 1
+ 3
-13
Unemployment Rate - % SA
5.4
5.6
6.3
M f g . Avg. W k l y . Hours
M f g . A v g . W k l y . Earn. - $
41.0
415
40.7
413
40.4
399
+ 1
+ 4
16,374
15,356
1,018
16,400
15,333
1,063
16,119
14,889
1,142
+ 2
+ 3
-11
UNITED STATES
Civilian Labor Force - thous.
Total Employed - thous.
Total Unemployed - thous.
SOUTHEAST
Civilian Labor Force - thous.
Total Employed - thous.
Total Unemployed - thous.
Unemployment Rate - % SA
6.4
6.3
7.2
M f g . Avg. W k l y . Hours
M f g . Avg. W k l y . Earn. - $
41.2
342
41.0
342
40.5
356
+ 2
- 4
1,845
1,720
125
1,851
1,714
137
1,879
1,697
143
- 2
+ 1
-13
Civilian Labor Force - thous.
Total Employed - thous.
Total Unemployed - thous.
Unemployment Rate - % SA
M f g . A v g . W k l y . Hours
Mfg. Avg. W k l y . Earn. - $
Civilian Labor Force - thous.
Total Employed - thous.
Total Unemployed - thous.
Unemployment Rate - % SA
M f g . Avg. W k l y . Hours
Mfg. Avg. Wkly. Earn. - $
Civilian Labor Force - thous.
Total Employed - thous.
Total Unemployed - thous.
Unemployment Rate - t SA
7.2
6.9
8.0
40.6
335
40.6
336
40.5
330
+ 0
+ 2
6,035
5,731
304
6,045
5,758
287
5,768
5,469
299
+ 5
+ 5
+ 2
5.3
4.9
5.5
40.6
335
40.6
336
40.8
330
3,085
2,906
180
3,074
3,024
2,857
167
2,S
+ 0
+ 2
+ 2
2
5.9
5.8
5.6
41.2
356
41.4
356
40.3
341
+ 4
1,886
1,686
200
1,894
1,671
223
1,975
1,717
258
- 5
- 2
-22
Unemployment Rate - t SA
10.4
11.4
12.9
M f g . Avg. W k l y . Hours
Mfg. Avg. Wkly. Earn. - $
42.5
466
42.6
462
41.3
454
+ 3
+ 3
1,149
1,065
84
1,158
1,058
100
1,152
1,034
118
- 0
+ 3
-29
M f g . A v g . W k l y . Hours
M f g . A v g . W k l y . Earn. - $
Civilian Labor Force - t h o u s .
Total Employed - thous.
Total Unemployed - thous.
Civilian Labor Force - thous.
Total Employed - thous.
Total Unemployed - thous.
"
+ 0
Unemployment Rate - % SA
7.6
8.2
10.6
M f g . A v g . W k l y . Hours
Mfg. A v g . W k l y . Earn. - $
39.8
311
40.1
311
39.4
297
+ 1
+ 5
2,373
2,248
125
2,378
2,238
136
2,321
2,115
157
+ 2
+ 4
-20
Civilian Labor Force - thous.
Total Employed - thous.
Total Unemployed - thous.
Unemployment Rate - % SA
5.4
5.5
6.9
M f g . A v g . Wkly. Hours
Mfg. Avg. W k l y . Earn. - $
41.8
370
41.8
369
40.6
361
NOTES:
+ 3
+ 2
APR
1988
MAR
1988
APR
1987
ANN.
%
CHG
Nonfarm Employment - thous.
Manufacturing
Construction
Trade
Government
Services
F i n . , Ins. 8 Real Est.
Trans., Com. 8 Pub. U t i l .
104,608
19,391
5,078
24,269
17,709
25,069
6,689
5,510
103,754
19,334
4,812
24,164
17,694
24,865
6,651
5,473
101,381
18,926
4,843
23,745
17,351
23,950
6,530
5,314
+ 3
+19
+ 5
+ 2
+ 2
+ 5
+ 2
+ 4
Nonfarm Employment - thous.
Manufacturing
Construction
Trade
Government
Services
F i n . , Ins. 8 Real Est.
Trans., Com. 8 Pub. U t i l .
13,843
2,382
784
3,448
2,426
3,124
822
762
13,825
2,384
778
3,441
2,433
3,114
820
759
13,404
2,336
754
3,335
2,359
2¿970
796
743
Nonfarm Employment - thous.
Manufacturing
Construction
Trade
Government
Services
F i n . , Ins. 8 Real Est.
Trans., C o m . 8 Pub. Util.
1,519
372
73
334
304
282
70
72
1,514
372
73
332
304
281
70
72
1,498
364
73
330
302
274
70
72
+ 1
+ 2
0
+ 1
+ 1
+ 3
0
0
Nonfarm Employment - thous.
Manufacturing
Construction
Trade
Government
Services
F i n . , Ins. 8 Real Est.
T r a n s . , Com. 8 Pub. U t i l .
5,099
542
347
1,393
779
1,399
370
262
5,108
542
348
1,397
785
1,398
370
260
4,826
526
333
1,309
738
1,301
356
254
+
+
+
+
+
+
+
+
Nonfarm Employment - thous.
Manufacturing
Construction
Trade
Government
Services
F i n . , Ins. 8 Real Est.
T r a n s . , C o m . 8 Pub. Util,
2,787
570
549
156
176
2,784
572
148
688
490
547
155
175
2,744
567
147
1685
478
532
153
173
Nonfarm Employment - thous.
Manufacturing
Construction
Trade
Government
Services
F i n . , Ins. 8 Real Est.
Trans., Com. 8 Pub. U t i l .
1,496
168
81
361
314
328
85
104
1,494
167
79
361
315
329
85
104
1,478
162
81
358
316
318
84
104
+ 1
+ 4
0
+ 0
- 1
- 1
+ 1
0
Nonfarm Employment - thous.
Manufacturing
Construction
Trade
Government
Services
F i n . , Ins. 8 Real Est.
T r a n s . , C o m . 8 Pub. Util.
886
233
33
187
200
143
39
43
880
233
33
186
199
141
39
43
860
226
33
184
194
138
38
42
+ 3
+ 3
0
+ 2
+ 3
+ 4
+ 3
+ 2
Nonfarm Employment - thous.
Manufacturing
Construction
Trade
Government
Services
F i n . , Ins. 8 Real Est.
Trans., Com. 8 Pub. U t i l .
2,056
497
100
481
341
422
102
106
" 2,043
498
97
477
340
418
101
105
"1,998
494
97
468
330
408
94
98
All labor force data are from Bureau of Labor Statistics reports supplied by state agencies.
Only the unemployment rate data are seasonally a d j u s t e d .
The Southeast data represent the total of the six states.
I
F E D E R A L R E S E R V E B A N K O F ATLANTA
49
3
2
4
3
3
5
3
3
+
+
+
+
+
+
+
+
6
3
4
6
6
8
4
3
+
+
+
+
+
+ 3
2
1
1
1
2
+ 2
+ 2
+
+
+
+
+
+
+
+
3
1
3
3
3
4
9
9
CONSTRUCTION
APR
1987
APR
1988
ANN.
%
CHG.
APR
1987
1988
ANN.
%
CHG.
(12-month cumulative rate)
Mil.
Nonresidential Building Permits 50,200
Total Nonresidential
7,232
Industrial B l d g s .
12,985
Offices
13,363
Stores
2,229
Hospitals
.,092
Schools
Residential Building Permits
Value - $ M i l .
Residential Permits - Thous.
Single-family units
Multifamily units
Total Building Permits
Value - $ M i l .
50,596
7,275
13,357
13,169
2,266
1,131
93,196
93,642
96,859
- 4
1,007.2
462.0
1,010.7
467.9
1,082.6
610.0
- 7
-25
140,102
140,944
144,160
- 3
15,557
15,677
15,797
- 2
202.4
100.9
205.5
102.0
206.2
123.8
- 2
-18
23,336
23,411
23,512
- 1
601
619
678
-11
10.0
3.3
10.0
3.9
11.2
6.7
-10
-51
1,112
1,130
1,238
-10
8,944
9,029
8,733
+ 2
115.4
70.9
110.3
71.5
108.0
80.0
+ 7
-11
12,647
12,751
12,585
+ 0
3,610
3,599
3,682
- 2
46.8
18.3
47.0
17.6
50.7
20.6
- 8
-21
5,560
5,490
5,434
+ 2
396
402
493
-20
6.4
0.5
6.6
0.5
7.5
17.9
-15
-97
764
787
941
-19
286
288
323
-11
4.8
1.1
4.9
0.8
5.4
1.6
510
503
563
1,719
1,740
1,889
22.0
6.8
22.1
7.7
23.4
13.1
2,743
2,778
2,901
Nonresidential Building
Total Nonresidential
Industrial B l d g s .
Offices
Stores
Hospitals
Schools
7,780
814
1,911
2,417
495
264
7,763
867
1,852
2,522
482
263
7,866
1,124
1,883
2,445
445
152
- 1
-28
+ 1
- 1
+11
+74
Residential Building Permits
Value - $ M i l .
Residential Permits - Thous.
Single-family units
Multifamily units
Total Building Permits
Value - $ Mil.
Nonresidential
Total Nonresidential
Industrial B l d g s .
Offices
Stores
Hospitals
Schcols
511
22
161
189
16
22
511
29
158
186
16
19
561
72
164
174
17
21
-10
-69
- 2
+ 9
- 6
+ 5
Residential Building Permits
Value - $ M i l .
Residential Permits - T h o u s .
Single-family units
Multifamily units
Total Building Permits
Value - $ M i l .
Total Nonresidential
Industrial B l d g s .
Offices
Stores
Hospitals
Schools
3,702
3,690
821
1,057
182
96
3,722
3,872
808
1,098
174
95
3,852
4,073
890
1,162
314
32
- 4
-10
- 8
-10
-42
+200
Residential Building Permits
Value - $ M i l .
Residential Permits - Thous.
Single-family units
Multifamily units
Total Building Permits
Value - $ M i l .
Total Nonresidential
Industrial B l d g s .
Offices
Stores
Hospitals
Schools
1,950
1,891
1,752
+11
245
264
350
-30
580
526
411
+41
578
565
532
+ y
123
124
21
103
104
42
+486
+4b
368
16
62
162
106
12
386
12
63
163
106
14
448
39
91
130
36
41
-18
-59
-32
+2b
+194
$ Mil.
223
28
56
63
16
12
215
27
51
61
16
13
240
21
59
81
24
8
- 8
+33
- 5
-22
-33
+50
Residential Building Permits
Value - $ Mil.
Residential Permits - T h o u s .
Single-family units
Multifamily units
Total Building Permits
Value - $ M i l .
T b i
Nonresidential Building Permits - $ Mil.
Total Nonresidential
1.024
Industrial Bldgs.
133
Offices
231
Stores
368
5 2
Hospitals
Schools
19
1,038
146
246
347
47
18
1,012
234
267
317
33
8
+ 1
-43
-10
+21
+58
+138
Residential Building Permits
Value - $ M i l .
Residential Permits - T h o u s .
Single-family units
Multifamily units
Total Building Permits
Value - $ M i l .
Total Nonresidential
Industrial Bldgs.
Offices
Stores
Hospitals
Schools
Total Nonresidential
Industrial Bldgs.
Offices
Stores
Hospitals
Schools
-n
Residential Building Permits
Value - $ M i l .
Residential Permits - Thous.
Single-family units
Multifamily units
Total Building Permits
Value - $ M i l .
Residential Building Permits
Value - $ M i l .
Residential Permits - Thous.
Single-family units
Multifamily units
Total Building Permits
Value - $ M i l .
- 9
-
6
-48
- 5
o f the six states.
50
E C O N O M I C R E V I E W , JULY/AUGUST 1988
GENERAL
LATEST CU RR.
DATA PERIOD
united
msm
Personal Income
($ b i l . Plane Pass. A r r . (thous.]
Petroleum Prod, (thous.)
Consumer Price Index
1967=100
Kilowatt Hours - m i l s .
Personal Income
($ b i l . - SAAR)
Plane Pass. Arr. (thous.]
Petroleum Prod, (thous.)
Consumer Price Index
1967=100
Kilowatt Hours - m i l s .
Personal Income
($ b i l . - SAAR)
Plane Pass. A r r . (thous.)
Petroleum Prod, (thous.)
Consumer Price Index
1967=100
Kilowatt Hours - m i l s .
Personal Income
($ bil. - SAAR)
Plane Pass. Arr. (thous.)
Petroleum Prod, (thous.)
Consumer Price Index
1977=100
MIAMI
Kilowatt Hours - m i l s .
Personal Income
($ b i l . - SAAR)
Plane Pass. Arr. (thous.)
Petroleum Prod, (thous.)
Consumer Price Index
1967=100
Kilowatt Hours - m i l s .
PREV.
PERIOD
YEAR
AGO
ANN.
%
CHG.
Q4
3 ,844.8
3,749.3
3,589.2
+ 7
APR
N.A.
8 ,172.0
N.A.
8,283.0
N.A.
8,413.3
- 3
APR
APR
350.8
214.4
349.0
225.1
337.7
198.2
+ 4
+ 8
Q4
468.1
465.7
439.0
+ 7
APR
APR
6,083.4
1,319.0
6,703.6
1,324.0
6,438.0
1,423.5
- 6
- 7
FEB
N.A.
34.0
N.A.
34.0
N.A.
31.0
+10
Q4
49.2
48.6
46.4
+ 6
APR
APR
158.9
56.0
181.3
57.0
170.8
56.0
- 7
0
FEB
N.A.
4.6
N.A.
4.9
N.A.
4.2
+ 10
189.7
185.1
174.3
+ 9
3,113.7
22.0
MAY
187.2
10.3
3,669.8
22.0
MAR
185.5
10.0
3,263.5
21.0
MAY
179.1
9.0
- 5
+ 5
88.6
90.4
Q4
APR
APR
FEB
Q4
APR
+14
+ 5
Plane Pass. Arr. (thous.]
Petroleum Prod, (thous.)
Consumer Price Index
1967=100
Kilowatt Hours - m i l s .
Personal Income
($ b i l . - SAAR)
Plane Pass. Arr. (thous.)
Petroleum Prod, (thous.)
Consumer Price Index
1967=100
Kilowatt Hours - m i l s .
Personal Income
($ b i l . - SAAR)
Petroleum Prod, (thous.;
Consumer Price Index
1967=100
Kilowatt Hours - m i l s .
2,119.6
N. A.
2,190.5
N.A.
FEB
N. A.
5.6
N.A.
6.0
N.A.
5.1
+10
Q4
51.4
50.7
49.8
+ 3
APR
APR
340.9
1,166.0
329.4
1,171.0
372.2
1,267.5
- 8
- 8
FEB
N.A.
4.5
N.A.
4.9
N.A.
4.4
+ 2
Q4
26.9
27.2
25.5
+ 5
APR
APR
39.1
75.0
45.3
74.0
46.1
79.0
-15
- 6
FEB
N.A.
2.3
N.A.
2.4
N.A.
2.1
+10
Q4
62.3
63.7
58.9
+ 6
APR
Personal Income
($ bil. - SAAR)
2,095.9
N. A.
334.9
N.A.
358.2
N.A.
394.9
N.A.
-15
N.A.
6.7
N.A.
6.8
N.A.
6.2
FEB
- 4
+ 8
ANN.
MAY
%
1987 CHG.
MAY
1988
APR(R)
1988
Agriculture
Prices Rec'd by Farmers
Index (1977=100)
134
Broiler Placements (thous.)
94,235
Calf Prices ($ per cwt.)
91.90
Broiler Prices (t per lb.)
33.50
Soybean Prices ($ per bu.)
6.98
Broiler Feed Cost ($ per ton) (Q2)181
130
94,214
95.20
28.00
6.36
(01)195
128
91,712
77.60
30.00
5.33
(Q2)189
+ 5
+ 3
+18
+12
+31
- 4
Agriculture
Prices Rec'd by Farmers
Index (1977=100)
123
Broiler Placements (thous.)
40,132
Calf Prices ($ per cwt.)
91.00
Broiler Prices (i per lb.)
-32.33
Soybean Prices ($ per bu.)
7.20
Broiler Feed Cost ($ per ton) (Ql)163
121
40,041
96.33
26.30
6.61
(Q1)190
113
37,944
75.23
28.76
5.37
(Q2)l73
+ 9
+ 6
+21
+12
+34
- 6
Agriculture
Farm Cash Receipts - $ m i l .
Dates: JAN., M A R .
564
Broiler Placements (thous.)
14,451
Calf Prices ($ per cwt.)
90.80
Broiler Prices (< per lb.)
32.50
Soybean Prices ($ per bu.)
7.29
Broiler Feed Cost ($ per ton)
158
14,517
100.00
26.00
6.51
194
421
13,292
76.80
29.00
5.43
177
+34
+ 9
+18
+12
+34
-11
Agriculture
Farm Cash Receipts - $ m i l .
Dates: J A N . , MAR
Broiler Placements (thous.)
Calf Prices ($ per c w t .
Broiler Prices (i per lb.)
Soybean Prices ($ per bu.)
Broiler Feed Cost ($ per ton)
1,862
2,452
95.00
32.50
7.29
158
2,405
105.00
26.60
6.51
194
1,634
2,401
81.10
28.90
5.43
177
+14
+ ?
+17
+12
+34
-11
Agriculture
Farm Cash Receipts - $ m i l .
Dates: JAN., M A R .
613
Broiler Placements (thous.)
15,831
Calf Prices ($ per cwt.)
88.90
Broiler Prices (i per lb.)
31.50
Soybean Prices ($ per bu.)
7.33
Broiler Feed Cost ($ per ton)
158
15,491
93.00
25.50
6.61
194
581
15,178
72.80
28.00
5.31
177
+ 5
+ 4
+22
+13
+38
-11
Agriculture
Farm Cash Receipts - $ mil.
Dates: JAN., M A R .
314
Broiler Placements (thous.)
N.A.
Calf Prices ($ per cwt.)
91.00
Broiler Prices {t per lb.)
N.A.
Soybean Prices {$ per bu.)
7.14
Broiler Feed Cost ($ per ton)
185
N,
.A.
93.
.00
N. A.
,
6.
,6b
N.
.A.
269
N.A.
73.50
N.A.
5.32
159
+34
+16
Agriculture
Farm Cash Receipts - $ m i l .
Dates: JAN., M A R .
Broiler Placements (thous.)
Calf Prices ($ per cwt.)
Broiler Prices (t per lb.)
Soybean Prices ($ per bu.)
Broiler Feed Cost ($ per ton)
482
7,343
94.20
33.60
7.15
185
7,259
93.70
28.20
6.63
175
321
7,073
74.00
29.80
5.38
159
+50
+ 4
+27
+13
+33
+16
Agriculture
Farm Cash Receipts - $ m i l .
Dates: JAN., M A R .
438
Broiler Placements (thous.)
N.A.
Calf Prices ($ per cwt.)
87.20
Broiler Prices (< per lb.)
N.A.
Soybean Prices ($ per bu.)
7.18
Broiler Feed Cost ($ per ton)
197
389
N.A.
71.80
N.A.
5.41
205
+13
N.A.
90.70
N.A.
6.60
N.A.
+16
+24
+21
+33
- 4
NOTES:
Personal Income data supplied by U. S. Department of Commerce. Taxable Sales are reported as a 12-month cumulative total. Plane
Passenger Arrivals are collected from 26 airports. Petroleum Production data supplied by U. S. Bureau o f M i n e s . Consumer Price Index data
supplied by Bureau o f Labor Statistics. Agriculture data supplied by U . S . Department o f Agriculture. Farm Cash Receipts data are reported
as cumulative for the calendar year through the month shown. Broiler placements are an average weekly r a t e . The Southeast data represent
the total o f the six states. N. A. = not available. The annual percent change calculation is based on most recent data over prior year
R = revised.
I F E D E R A L R E S E R V E B A N K O F ATLANTA
51
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Economic
Review
Federal Reserve Bank of Atlanta
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