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Federal Reserve Bank of Philadelphia
SEPTEMBER • OCTOBER 1988
SEPTEMBER/OCTOBER 1988
The BUSINESS REVIEW is published by the
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CAN STOCK PRICES RELIABLY
PREDICT RECESSIONS?
Leonard Mills
One year after the stock market crash of
October 1987, analysts are still puzzled by
its seemingly small impact on the econ
omy. The recession that had been expected
to follow Black Monday never material
ized, thus calling into question the relia
bility of stock prices as a leading indicator
of recessions. To quantify the stock mar
ket's performance as a recession predictor,
the author applies the "Neftci technique"
to estimate the probability that the econ
omy has turned down. The results suggest
that stock prices can provide some infor
mation about the economy, but that this
information should be combined with
other data to obtain a more reliable
indicator.
PRIVATE-SECTOR DECISIONS AND
THE U.S. TRADE DEFICIT
Behzad Diba
The U.S. trade deficit has resulted from
many public- and private-sector decisions:
an investment boom during the early 1980s
and the emergence of large U.S. budget
deficits, followed by a plunge in the U.S.
personal savings rate. The investment
boom could benefit future generations,
despite the accompanying trade deficit,
even though the resulting international
debt will be theirs to repay. But there may
be a way to ease the debt burden. Evidence
suggests that returning the personal sav
ings rate to its historical average level
would be as effective as eliminating the
budget deficit in reducing the trade
deficit.
Can Stock Prices
Reliably Predict Recessions?
Leonard Mills*
The stock market crash of October 19, 1987,
has had its impacts on Wall Street—including
congressional calls for more regulation of the
financial markets, the New York Stock Ex
change's proposals for limits on trading, and
reduced volume and liquidity in the financial
markets. The expected impact on Main Street,
however, never seemed to materialize. Imme
diately following the crash, predictions of
‘ Leonard Mills is an Economist in the Macroeconomics
Section of the Research Department of the Federal Reserve
Bank of Philadelphia. The author extends special thanks to
Tom Stark and Henry Min for valuable research assistance.
recession—or, reminiscent of 1929, depres
sion—were rampant. But overall the economy
remained strong in the fourth quarter of 1987
and the first half of 1988, and fears of recession
soon dissipated.
The economy's resilience in the wake of the
crash has surprised many observers. Some have
argued that the time between a decline in stock
prices and a recession is so long that we have yet
to see the upcoming recession. But others claim
to be not surprised, arguing that stock prices
have never been a reliable indicator of impend
ing recessions. This view is summarized in the
3
BUSINESS REVIEW
often-quoted quip by Paul Samuelson: "The
stock market has predicted nine of the last five
recessions!"1
To be fair, however, no indicator of future
economic activity is infallible, and the October
crash may be just one of those rare occasions
when the stock market made an incorrect pre
diction. In short, the issue that the crash has
resurrected is whether stock prices, by them
selves, are a reliable leading indicator of reces
sions. Theory alone cannot provide the answer;
it is an empirical issue. But analysts looking at
the same set of numbers do not always reach the
same conclusions. So we should first try to
quantify objectively the stock market's per
formance as a leading indicator. One statistical
technique, recently developed by Salih Neftci
and one that has been applied to other economic
indicators, can provide a helpful perspective
when applied to stock prices. The results of the
Neftci technique suggest that though stock prices
alone offer some indication of the economy's
future, broader indicators, such as the Index of
Leading Indicators, are more reliable.
DECLINING STOCK PRICES
COULD SIGNAL RECESSIONS
There are sound economic reasons for think
ing that a fall in stock prices would be a good
leading indicator of recessions. One reason is
that declining stock prices may have direct effects
on consumer spending because falling stock
prices lower the financial wealth of stockholders.
This decline in wealth may induce them to
decrease their spending on goods and services.
Consumers who do not own stock also could be
affected by falling stock prices because they may
lose confidence in the economy and feel their
own income prospects are dimmer. Hence, they
may become more cautious in their current
spending. For businesses, lower stock prices
raise the cost of acquiring equity funds to pur-
iPaul A. Samuelson, "Science and Stocks," Newsweek,
September 19,1966.
4
SEPTEM BER/OCTOBER 1988
chase new plant and equipment, so investment
spending could be reduced when stock prices
fall. And as investment and consumer spending
decrease because of declining stock prices, the
economy could grow at a slower rate and per
haps slip into a recession.
The 1987 stock crash, however, seemed to
have only modest effects on consumer spending
and investment. After slowing in the fourth
quarter of 1987, consumption and business in
vestment came back in the first half of 1988. In a
recent study, Alan Garner concludes that "this
relatively small effect is consistent with empirical
studies showing that the stock market has only a
modest impact on consumer spending."2 Like
wise, in an earlier study, Douglas Pearce finds
that most empirical studies have concluded that
decreases in stock prices lead to decreases in
investment, but that the size of the effect is un
certain.3*
Even if the direct impact of stock price declines
is small, stock prices may still be a good leading
indicator. The conventional view is that stock
prices reflect firms' expected future earnings.
According to this view, a general decline in stock
prices means that market participants have
lowered their expectations of firms' future earn
ings, presumably because they foresee a down
turn in the economy. If the expected downturn
actually occurs, the decline in stock prices will
have preceded it. So to the extent that an eco
nomic downturn, whatever its cause, can be
foreseen, its onset should be forewarned by the
stock market.
An alternative view is that stock prices some
times fluctuate for reasons unrelated to the
economic fundamentals. In particular, the stock
market may be subject to speculative bubbles. In
a bubble, speculators bid up the current prices
2C. Alan Gamer, "Has the Stock Market Crash Reduced
Consumer Spending?" Federal Reserve Bank of Kansas City
Economic Review (April 1988) pp. 3-16.
3Douglas K. Pearce, "Stock Prices and the Economy,"
Federal Reserve Bank of Kansas City Economic Review
(November 1983) pp. 7-22.
FEDERAL RESERVE BANK OF PHILADELPHIA
Can Stock Prices Reliably Predict Recessions?
of stocks simply because they expect to sell the
stocks at still higher prices in the future, even
though expectations of future earnings remain
unchanged. For a while, the expectations of
higher prices are self-fulfilling. A second group
of buyers is willing to pay more than the first
because it expects to get even higher prices from
a third group, and so on. But at some point in
time, people lose faith that prices will go any
higher—an expectation that is likewise selffulfilling. The bubble then bursts and stock prices
come tumbling down. In this circumstance, a
decline in stock prices is not the result of lowered
expectations of future earnings. Some analysts
have argued that the October crash, which fol
lowed a steep run-up in stock prices earlier in
1987, was just such an episode and that the crash
did not mean that market participants had fore
seen an economic downturn.4
Casual observation of stock prices over the
postwar period reveals that they do seem to be a
leading indicator of recessions, though an im
perfect one. Since 1947 the S&P 500-stock index,
shown in Figure 1 (p. 6), has often declined just
before the onset of recessionary periods (de
picted by the vertical bars). The recessions of
1959 and 1973 are examples. But stock prices do
not seem to be completely reliable as a leading
indicator. Sometimes, as in 1962, a bear market
cried wolf: stock prices fell dramatically, but no
recession followed. Ideally, a leading indicator
would not generate these false signals. Other
times, as in 1980, a recession started without a
decline in stock prices: that is, the stock market
gave no advance warning. An ideal leading
indicator would anticipate all recessions.
4For a discussion of experimental evidence suggesting
that bubbles are possible, see Herbert Taylor, "Experimental
Economics: Putting Markets Under the Microscope," this
Business Review (March/April 1988) pp. 15-25, and the
references therein. However, evidence that the run-up in
stock prices in 1986-87 was not the result of a speculative
bubble is presented in Gary Santoni, "The Great Bull
Markets 1924-29 and 1982-87: Speculative Bubbles or
Economic Fundamentals?" Federal Reserve Bank of St. Louis
Review (November 1987) pp. 16-30.
Leonard Mills
In practice, there is no leading indicator that
meets the ideal standard of emitting no false
signals and anticipating every recession. And a
precise answer to how many errors are accept
able for an indicator depends on the costs of
these errors. Nevertheless, the number of false
signals and the number of unanticipated re
cessions are useful quantitative measures in
assessing a leading indicator's reliability.
THE NEFTCI RULE HELPS
EXTRACT THE SIGNALS
Evaluating an indicator's success or failure as
a predictor requires some method of determining
when the indicator is signaling recession. One
method is the x-month rule. If the indicator
decreases for x consecutive months, then it is
said to be predicting that a recession is immi
nent. This kind of rule has been applied primarily
to the Index of Leading Indicators by analysts
who say that three consecutive monthly declines
in this index presage a recession. Another
method is the x-percent rule. In this rule, if the
indicator declines by x percent, then it is said to
be signaling a recession. This kind of rule has
often been applied to stock prices by analysts
who say that a 10 percent decline in stock prices,
for example, signals a recession.5 But any xmonth or x-percent rule is somewhat arbitrary
and may not take full advantage of the informa
tion provided by the indicator. An alternative
approach for extracting a turning-point signal is
to apply a more sophisticated statistical rule
called Neftci's optimal prediction rule.
How the Neftci Rule Works. The Neftci rule
starts with the same assumption underlying the
more popular rules: that a substantial downturn
in an indicator presages an upcoming recession.
After each new reading of the indicator, an
5For applications of the x-percent rule to stock prices as a
leading indicator, see Bryon Higgins, "Is a Recession In
evitable This Year?" Federal Reserve Bank of Kansas City
Economic Review (January 1988) pp. 3-16, and Alfred
Malabre, "As Economy Goes, So Goes Stock Market," Wall
Street Journal, February 9, 1987.
5
SEPTEM BER/OCTOBER 1988
BUSINESS REVIEW
FIGURE 1
The S&P 500-Stock Index and Recessions
1949 — Present
LOG OF S&P 500
analyst using the Neftci rule would assess the
probability that the indicator has gone into a
"down" phase. When this probability climbs
above a critical value prespecified by the analyst,
the indicator is interpreted to be signaling a
coming recession. Taking stock prices as an
example, each month the Neftci procedure will
calculate a probability that the stock market has
entered a "bear" market. If that probability is
higher than the critical value, the analyst will
interpret this to mean that the stock market is
calling for a recession.
The critical probability value that must be
reached before a recession is signaled also
Digitized 6for FRASER
determines the probability of false signals that
the analyst is willing to accept. For instance,
suppose an analyst—call her Denice D'spair—
sets her critical probability at 75 percent. When
the probability that the indicator has entered a
down phase increases to .75 or higher, Denice
warns that a recession is imminent. At this
critical probability value, Denice is willing to
accept the 25 percent probability that the indi
cator has not entered a down phase and hence
that the prediction of recession is wrong.
In general, choosing the critical value involves
a trade-off between the number of false signals
and the number of unanticipated recessions that
FEDERAL RESERVE BANK OF PHILADELPHIA
Leonard Mills
Can Stock Prices Reliably Predict Recessions?
arise. The higher the critical value, the smaller
the number of false signals but the larger the
number of unanticipated recessions. The ap
propriate critical value depends on the relative
costs of these errors to the analyst. As an example,
suppose Denice's boss tells her that an unantici
pated recession is very costly to the firm because
it would leave the company with large inven
tories of unsold goods. Denice might then
decide to lower her critical value to, say, .50. So
when the probability that a downturn in stock
prices has occurred is .50 or higher, Denice warns
that a recession is coming. That is, Denice will
predict a recession every time a recession is at
least a 50-50 proposition. Thus, while it is un
likely that Denice's company will be caught by a
surprise recession, there is also a good chance
that a false signal of recession will be given.
For contrast, consider an analyst with a differ
ent company—call him Horatio Hope. Horatio's
company is more concerned with preserving its
market share and does not want to lose any
customers because of orders going unfilled.
False signals of recession are more costly to
Horatio's employer than are unanticipated re
cessions. Consequently, he chooses a high
critical value, say .90. Horatio calls for a reces
sion only when the Neftci probability value
climbs above .90, implying only a 10 percent
chance that a signal is false. (See Figure 2.)
To estimate the actual probability of a down
turn, the analyst uses each new reading of the
indicator to update the probability of recession
by applying Neftci's rule. (See Appendix for a
technical description of calculating the proba
bility of recession.) For example, suppose times
have been good so that Denice begins with a
recession probability of 10 percent. Then she
observes a large fall in stock prices, say a 7 per
cent monthly decline. Using this new informa
tion, Denice would then recompute the proba
bility of recession, which would show an in
crease to perhaps 30 percent. This new figure
then serves as her probability of a downturn
FIGURE 2
Effects of the Critical Value on the
Forecaster's Decision to Call for a Recession
Probability
0.9
Critical
Value
0.5
Critical
Value
0.0
7
BUSINESS REVIEW
until her next observation of the indicator. So
suppose in the next month Denice observes a 15
percent increase in stock prices. Using the Neftci
rule to combine the previous estimate of a 30
percent probability of a downturn with this new
observation would produce a lower probability
of recession, say 12 percent. Thus, as new in
formation on stock prices becomes available,
Denise's assessment of the probability of reces
sion is revised based on both current and past
movements in stock prices.
The updating aspect of the Neftci procedure
takes the advantages of the x-month and xpercent rules and improves upon them. Like the
x-month rule, the Neftci rule includes informa
tion from previous movements in stock prices.
Like the x-percent rule, the Neftci rule also uses
the information revealed by the magnitude of
the change in stock prices. That is, a large decline
in stock prices will raise the probability of re
cession more than a small decline will. But the xmonth and x-percent rules allow only the crude
statements that a recession is either likely or
unlikely. There will always be some uncertainty
in any economic forecast, but the popular rules
do not quantify the degree of uncertainty. The
Neftci rule improves on the popular rules be
cause it produces probability statements, such
as "the recent decline in the stock market implies
that the probability of a coming recession is 67
percent," thus indicating the analyst's degree of
uncertainty.
Using the Neftci Rule to Count Errors. Any
leading indicator can be evaluated by comparing
its signals of recession with the dates of actual
recessions. To define what he means by a correct
signal, however, the analyst must define an
acceptable lead time. The lead time is the
number of months between the time the in
dicator flashes the signal and the onset of the
recession. For our purposes a lead time of 12
months or less may be considered acceptable.
The shortest expansion in the postwar period
lasted 12 months. Since we will compute the
probability of a recession only while we are in an
expansion, 12 months is the longest lead time
8 FRASER
Digitized for
SEPTEMBER/OCTOBER 1988
possible for all of the expansions.6
With the prespecified critical probability and
a lead time that is considered acceptable, we can
label every signal of recession as either correct
or false and every recession as either anticipated
or unanticipated. If the indicator gave a proba
bility of recession above the critical value some
time within the 12 months prior to the recession,
then the indicator correctly anticipated the re
cession. The top panel in Figure 3 gives an
example of a correct signal. In contrast, if the
indicator switched on, and then off, more than
12 months prior to the recession, then it gave a
false alarm, as shown in the middle panel.
Finally, if the signal was never on within the 12
months prior to the recession, then the indicator
failed to anticipate the recession. The bottom
panel of Figure 3 illustrates this type of error.
HOW RELIABLE ARE SIGNALS FROM
STOCK PRICES?
The Historical Record. Applying the Neftci
rule to the monthly growth rate in the S&P 500stock index during the 1947-82 period pro
duced the probabilities of recession shown in
Figure 4 (p. 10). Clearly, stock prices contain
some information about the economy's future
direction; the probability of recession climbed
before each of the seven recessions that occurred
between 1949 and 1982 (represented by the
vertical bars). Before five of the seven recessions,
the probabilities based on the stock market rose
above the 50 percent critical value within 12
months of the economic downturn. These five
successful predictions of recession all occurred
before 1975. The lead times of the five correct
predictions ranged from one to 11 months.
Although all of the recessions were anticipated
during this period, stock prices did emit some
false signals. Using the 50 percent critical value
resulted in four false signals before the
December 1969 peak and one false signal before
6A lead time of zero months—or no lead time—is con
sidered to be a useful signal because it usually takes several
months to recognize that a recession has in fact occurred.
FEDERAL RESERVE BANK OF PHILADELPHIA
Can Stock Prices Reliably Predict Recessions?
Leonard Mills
FIGURE 3
Types of Signals
Probability
Correct Signal
0.5
Critical
Value
12 months
prior
Probability
12 months
prior
Probability
z
o
0.5
on
Critical ■ on
W
Value
O
Unanticipated
Recession
1
1
1
kAm
§
g
Z
o
03
on
W
u
12 months
prior
the November 1973 peak.7 Thus, of the 10
recession signals given before 1975, five were
false and five were correct.
Unfortunately, the two recessions in the
1980s were cases in which the stock market
failed to provide a useful signal. Before the
recession that began in January 1980, the stock
market sent a signal that was considerably
earlier than our 12-month lead time. The proba
bility of a downturn climbed above 50 percent in
April 1977 and stayed there for the remaining 33
months of the expansion. This type of signal is
considered correct, even though its lead time is
greater than 12 months, because the probability
never fell below the 50 percent critical value
prior to the recession. But the severe pre
maturity of this signal, relative to the lead times
of the previous correct signals, means that stock
prices had little value in predicting the timing of
the 1980 recession. Before the recession that
began in July 1981, the stock market did not
send any signal at all; stock prices failed to push
the probability o f recession above the 50 per
cent level. In short, using the .50 critical value for
extracting recession signals from the stock
market worked reasonably well through the
1970s, but the stock market's performance as an
indicator seems to have deteriorated in the
1980s.
In Figure 4, raising the critical value for re
cession signals to .90 reduces the number of
false signals slightly, from five to four over the
entire postwar period. But the number of un
anticipated recessions increases dramatically,
from one to six. Apparently, we cannot presume
that a high probability of a stock market down
turn is associated with a high probability of
recession. We should certainly be suspicious,
then, of claims that stock prices have always
been a reliable leading indicator.
The Crash of 1987. The stock market crash of
7In fairness to stock prices, some of these false signals
were associated with pronounced economic slowdowns
that were not quite severe enough to be labeled recessions;
an example is 1966-67.
9
SEPTEMBER/OCTOBER 1988
BUSINESS REVIEW
FIGURE 4
Probabilities of Recession — S&P 500
1949 — 1982
Probability
49
54
59
64
1987 can now be interpreted with the benefit of
this historical perspective. Figure 5 shows the
probabilities of recession given by stock prices
since the beginning of the current expansion in
December 1982. Stock prices generated false
signals early in this expansion: at the .50 critical
value, they flashed a recession warning between
February and December of 1984. Thereafter,
generally rising stock prices reduced the proba
bility of recession to very low levels. The low
point was achieved at the stock market peak, in
August 1987, when the probability of recession
was only about 5 percent. After climbing to 14
percent in September, the probability of reces
sion shot up to 88 percent after the crash in
October. Thus, the probability of recession as
determined by stock prices was certainly in
creased by the crash. Since stock prices sub
sequently fell further and have yet to fully re
cover, the current probability of recession is
Digitized10
for FRASER
69
74
79
even higher, 98 percent as of May 1988. But as
we have seen, probabilities of a downturn ex
ceeding 90 percent have turned out, more often
than not, to be false signals of recessions. Thus,
while it may be too early to tell whether stock
prices will accurately predict the next recession,
it would not be too surprising if even this strong
signal turned out to be false.8*
A BROADER INDICATOR SENDS
A CLEARER SIGNAL
Because stock prices may move for reasons
8In a recent article, Joe Peek and Eric S. Rosengren, "The
Stock Market and Economic Activity," Federal Reserve Bank
of Boston New England Economic Review (May/June 1988) pp.
39-50, suggest that real stock prices are more reliable than
nominal prices in predicting economic slowdowns. Apply
ing the Neftci rule to real stock prices (measured as the S&P
500 divided by the CPI), however, did not improve the stock
market's recession predictions.
FEDERAL RESERVE BANK OF PHILADELPHIA
Can Stock Prices Reliably Predict Recessions?
FIGURE 5
Probabilities of Recession
S&P 500
1983 — Present
Probability
82
84
86
88
unrelated to the economic fundamentals, the
information that these prices provide may be
noisy. Our statistical analysis certainly indicates
this. But many other economic statistics are
subject to the same criticism. For example,
measures of the money stock may exhibit this
noise problem as well. Dramatic changes in the
public's demand for money, such as those that
occurred during the period of deposit deregu
lation in the early 1980s, can distort the signal
the money supply provides about the economy's
future direction.9
Because any single economic statistic is sub
ject to idiosyncratic movements that may not
9See Herbert Taylor, “What Has Happened to M l?" this
Business Review (September/October 1986) pp. 3-14, for a
discussion of the deterioration of the relation between Ml
and future GNP movements.
Leonard Mills
have broad economic implications, analysts
usually look at several variables that convey
information about the economy. It is in this
spirit that the Index of Leading Indicators (ILI),
computed by the Department of Commerce,
was designed. This index is an average of many
variables that seem to lead the business cycle,
and it includes stock prices.10 The hope is that
this index averages out the disturbances specific
to each statistic and retains the information that
each statistic provides about the overall
economy.
Does a broad-based approach, as summarized
by the Index of Leading Indicators, perform any
better by the Neftci standard? The answer seems
to be yes. Figure 6 (p. 12) is comparable to
Figure 4, except that the ILI replaces the S&P
500 in computing the probabilities of recession.
The results are encouraging. Just by comparing
Figures 4 and 6, we see that the peaks in the
probabilities provided by the ILI are sharper
than those provided by stock prices.11 A closer
look at the results reveals that a clearer signal is
provided by such an index that combines several
indicators. With a .50 critical probability, the ILI
anticipated all seven of the postwar recessions
and sent only four false signals. Choosing the
higher .90 critical value reduced the number of
false signals to two, but at the cost of two un
anticipated recessions. Finally, the range of lead
times seems narrow enough for the ILI to provide
a useful signal; lead times ranged from two to 15
months with the .50 critical value and from zero
to eight months with the .90 cutoff.
"Sure," someone might say, "but what has this
10Gary Gorton, "Forecasting With the Index of Leading
Indicators," this Business Review (November/December
1982) pp. 15-27, describes the Index of Leading Indicators in
more detail and discusses its usefulness.
11Stock prices are clearly a superior leading indicator
with respect to timeliness. In particular, stock prices are
observed instantaneously and are not subject to revision.
The Index of Leading Indicators, like several other indi
cators, is observed with a one-month lag and is subject to
several revisions.
11
SEPTEMBER/OCTOBER 1988
BUSINESS REVIEW
FIGURE 6
Probabilities of Recession
Leading Indicators
1949 — 1982
Probability
49
54
59
64
index done for me lately?" Figure 7 shows the
probabilities of recession generated by the ILI
since December 1982. Like stock prices, the ILI
generated some false recession signals early on
in the current expansion. But the important dif
ference between the ILI and stock prices is in the
recent behavior of both. While the likelihood of
a recession is almost certain if we use stock
prices as a leading indicator, the likelihood is
much smaller using the ILI. Although the proba
bility of a recession based on the ILI increased
after October 1987, it remained below even the
.50 critical value. The probability based on the
ILI peaked at 45 percent in January 1988 and has
since fallen to 31 percent in May.12 In contrast,
the probability based on stock prices soared
above the .90 critical value and has remained
12Based on preliminary data released June 29, 1988.
Digitized12
for FRASER
69
74
79
there. Given the relative performance of these
two indicators in the past, the prediction from
the Index of Leading Indicators seems more
reliable.
CONCLUSION
While economists are always looking for clues
about the economy's future course, no indicator
has proven infallible in its predictions. Some
times an indicator will fail to signal an upcoming
recession. Sometimes it will send false signals.
Stock prices have proven to be a particularly
unreliable leading indicator in recent years, and
the stock market crash of 1987 may prove a
telling example. Movements in stock prices do
seem to offer some information about the
economy's future. But our analysis suggests that
a combination of various indicators, such as the
Index of Leading Indicators, provides more re
liable signals of future economic activity.
FEDERAL RESERVE BANK OF PHILADELPHIA
Can Stock Prices Reliably Predict Recessions?
Leonard Mills
FIGURE 7
Probabilities of Recession
Leading Indicators
1983 — Present
Probability
0.9
-
0 0 —I— I— 1....1...1...1
82
84
86
88
APPENDIX
Estimating the Probability of Recession
The Neftci approach to estimating the probability of recession from observing a selected indicator,
such as a stock price index, builds on two assumptions. The first is that the indicator is always operating
under one of two regimes: an upturn regime, during which we are more likely to see increases in the
indicator, or a downturn regime, during which we are more likely to see the indicator decline. The
second assumption is that the probability of the indicator being in its downturn regime is related to the
probability of the economy as a whole going into a recession.
The analyst begins computing the probability of an upcoming recession in the first month of the
expansion. At that point the initial probability of a downturn in the indicator (and the economy) is equal
to zero. Then, each month, as the analyst gets a new reading on the indicator, he revises his probability
that the indicator (and hence the economy) is in its downturn regime by applying the Neftci rule:
13
SEPTEMBER/OCTOBER 1988
BUSINESS REVIEW
nt = {[1^.! + p(i-nt. 1)]Pf}/{[nt.1+ p u -n ^ip f + (l-n^plfa-P)}
where I lt = the conditional probability that the indicator is in the downturn regime;
Pb pf =
probability that the observed movement in the indicator came from the upturn regime
and downturn regime, respectively;
P = the unconditional probability that a switch from an upturn regime to a downturn regime will
occur in the current period.
This rule produces the best estimate of the probability that the indicator has entered its downturn
regime. Salih Neftci shows that using this rule minimizes the average delay in signaling a downturn for a
given critical value.3 We use a procedure that is similar to that used by Francis Diebold and Glenn
Rudebusch in implementing the Neftci rule.b
p^and p^ are the probability densities for the event that an observed change in the indicator variable
was drawn from the upturn regime and downturn regime, respectively. Estimation of these densities
requires some judgment on the dating of the downturn and upturn regimes for the indicator variable.
Because the expansions have lasted about four times as long as recessions, we define a downturn regime
as one year (the shortest expansion in the sample) prior to the business cycle peak through three months
prior to the business cycle trough. This dating captures the major movements in both the S&P 500 and
the Index of Leading Indicators. Alternative dates for the regimes using shorter lead times did not alter
the results. The probability densities, p^ and p^, were assumed to be normally distributed using the
mean and standard deviation of the monthly growth rates estimated for each regime. These parameters
were estimated from the 1948-82 period. Thus, the Neftci probabilities for the period 1949-82 are
analogous to within-sample predictions, and the probabilities for the period 1983-88 are analogous to
out-of-sample predictions.
P is the unconditional transition probability, that is, the probability that a switch from a downturn
regime to an upturn regime will occur in the current period given that it has not yet occurred. P is an
unconditional probability because it is not based on the movement of the indicator variable. In Neftci's
original application, this transition probability was determined by the length of the expansion because of
an assumption that expansions "age" and become weaker. This assumption has recently been ques
tioned and was not used in this application so that we might focus more sharply on the proposed
indicators.0 Instead, a constant transition probability of switching from the upturn to the downturn
regime was used. This probability was estimated to be .029 by following the procedure outlined in J.
Huston McCulloch.d Further, the hypothesis that this probability is a constant could not be rejected at
usual significance levels.
aFor derivations of the Neftci rule, see Salih Neftci, "Optimal Prediction of Cyclical Downturns/'journal of Economic
Dynamics and Control 4 (1982) pp. 225-41, and Francis X. Diebold and Glenn D. Rudebusch, "Scoring the Leading
Indicators," Federal Reserve Board Special Studies Paper No. 206 (1987). Carl J. Palash and Lawrence J. Radecki, "Using
Monetary and Financial Variables to Predict Cyclical Downturns," Federal Reserve Bank of New York Quarterly
Review (Summer 1985) pp. 36-45, use the Neftci rule to evaluate the leading indicator properties of other financial
variables.
bFrancis X. Diebold and Glenn D. Rudebusch, "Scoring the Leading Indicators."
cStudies that find that business expansions do not become weaker with age include J. Huston McCulloch, "The
Monte Carlo Cycle of Business Activity," Economic Inquiry 13 (September 1975) pp. 303-21, Francis X. Diebold and
Glenn D. Rudebusch, "Does the Business Cycle Have Duration Memory," Federal Reserve Board Special Studies Paper
No. 223 (1987), and Victor Zamowitz, "The Regularity of Business Cycles," National Bureau of Economic Research
Working Paper No. 2381 (1987). This issue has not been settled, however; see Frank de Leeuw, "Do Expansions Have
Memory?" Bureau of Economic Analysis Discussion Paper 16 (1987).
dJ. Huston McCulloch, "The Monte Carlo Cycle of Business Activity."
Digitized14
for FRASER
FEDERAL RESERVE BANK OF PHILADELPHIA
Private-Sector Decisions and
the U.S. Trade Deficit
Behzad Diba*
Many analysts have argued that the United
States needs to correct its trade imbalance, but
much of the commentary is rather vague in
stating why. The conventional argument against
trade deficits—that they create prosperity abroad
at the expense of domestic industries and
workers—does not seem relevant to the current
*Behzad Diba, now Associate Professor of Economics at
Georgetown University, wrote this article while he was an
Economist in the Banking and Financial Markets Section of
the Research Department of the Federal Reserve Bank of
Philadelphia.
U.S. experience. Although many U.S. manufac
turing firms were hurt by the trade deficit's
growth from 1982 through 1985, overall profits
and capacity utilization at U.S. firms increased.
And during 1986 and 1987, as the trade deficit
continued to widen, even the manufacturing
sector grew strongly. Moreover, the unemploy
ment rate has been declining since 1982, despite
the trade deficit, and most economists think it is
about as low as it can go without risking a serious
acceleration in inflation.
One reason the trade deficit might be harmful
is that it may reduce the welfare of future U.S.
15
BUSINESS REVIEW
SEPTEMBER/OCTOBER 1988
generations. To pay for the excess of U.S. imports
over U.S. exports, the current generation of
Americans must either sell assets to foreigners
or borrow from them. In the 1983-87 period,
Americans increased their net indebtedness to
the rest of the world by more than $500 billion,
to pay for persistent and unprecedentedly large
trade deficits. And since 1985, the total value of
foreigners' claims on the U.S. economy has sur
passed the total value of foreign assets held by
Americans, for the first time in over half a
century.
Some observers consider the recent increase
in net U.S. indebtedness alarming because of the
burden it will impose on future generations,
who will have to consume less than they produce
in order to service or to repay the current gen
eration's foreign debt. But even with this debt,
those future generations may nonetheless be
able to consume more goods and have a higher
standard of living than we do today, as long as
we have used the borrowing opportunity to
finance expanded productive investment.
The U.S. trade deficit is the outcome of many
private- and public-sector decisions, in the
United States as well as abroad. In particular,
changes in private savings behavior in the U.S.
have played a major role during the past few
years. To evaluate the trade deficit's effects on
the welfare of current and future generations,
we must first understand the underlying deci
sions that have contributed to its emergence and
persistence. But before turning to this question,
we need to review some basic concepts from the
national income accounts.1
ence between imports and exports of goods and
services. We can view the trade deficit as the
difference between the quantity of goods and
services that a country uses up in a year and the
quantity it produces—or, more technically, the
difference between "gross domestic purchases"
and "gross national product."
In the national income accounts, total U.S.
purchases of goods and services are broken down
into three categories:
1. personal consumption expenditures, which
consist of household spending on goods and
services;
2. gross private domestic investment, which is
defined as business spending on plant, equip
ment, and inventories plus spending on new
residential construction; and
3. government purchases of goods and ser
vices, which include the purchases of federal,
state, and local governments.
The sum of these three categories of spending—
which represents the total purchases of American
households, businesses, and governments—is
called gross domestic purchases. Gross national
product (GNP), in contrast, is a measure of the
total production of goods and services by American
residents. Whenever gross domestic purchases
exceed GNP—that is, whenever American
households, businesses, and governments are
collectively purchasing more goods and services
than the nation is producing—the United States
becomes a net importer of goods and services
from other countries. In other words, the U.S.
trade deficit is simply the difference between
gross domestic purchases and GNP:
PERSPECTIVES ON THE TRADE DEFICIT
There are several measures of a country's
balance of international payments. One standard
measure is the trade deficit, which is the differ
Trade Deficit = Gross Domestic
Purchases - Gross National Product
1-The national income accounts are government statistics
measuring the economy's output, income, and expenditures,
which are broken down into various categories. They are
published by the U.S. Department of Commerce in the
Survey of Current Business.
Digitized16for FRASER
Thinking of the trade deficit as the difference
between domestic purchases and domestic out
put provides us with an important insight: any
policy that aims to reduce the trade deficit must
either accelerate the growth of domestic output
or slow the growth of domestic purchases (or
both). With the U.S. economy close to full em
FEDERAL RESERVE BANK OF PHILADELPHIA
Private-Sector Decisions and the U.S. Trade Deficit
ployment in 1988, any attempt to accelerate the
growth of U.S. output would probably run into
capacity constraints and cause inflationary pres
sures. Accordingly, a noninflationary policy
aimed at reducing the trade deficit would have
to involve slower growth of personal consump
tion, domestic investment, or government
purchases.
Another measure of the imbalance in inter
national payments is “net foreign investment in
the U.S."2 To the trade deficit, it adds the deficit
resulting from unilateral transfers, which reflects
items such as U.S. government grants and private
gifts to foreigners. When U.S. imports exceed
U.S. exports, foreign countries can use the pro
ceeds from their trade surplus with the United
States either to reduce their indebtedness to
Americans or to acquire U.S. assets (such as
bonds issued by U.S. companies or government
agencies, or stocks of U.S. corporations). Simi
larly, unilateral transfers from the United States
enable foreigners to reduce their indebtedness
to Americans or to acquire U.S. assets.
Thus, the sum of the U.S. trade deficit and the
U.S. deficit on unilateral transfers is matched by
an increase in foreign claims on the United States
or a decrease in U.S. claims on other countries—
that is, by net foreign investment in the U.S.
A positive value of net foreign investment in the
U.S. would indicate that Americans sold assets
to foreigners or increased their indebtedness to
foreigners. According to the Commerce Depart
ment's estimate, net foreign investment in the
U.S. totaled $156.9 billion in 1987.3
2The concept of "net foreign investment in the U.S." (by
foreigners) used here coincides with "net foreign invest
ment" (by Americans in other countries) as reported in the
U.S. national income accounts, but with the signs reversed.
In the balance of payments accounts, the conceptual
counterpart of "net foreign investment in the U.S." is the
"U.S. current account deficit."
3This figure is obtained by dropping the minus sign in
front of the "net foreign investment" figure reported in the
Survey of Current Business (May 1988) p. 11. See Footnote 2
above. All numbers cited are from the May 1988 issue.
Behzad Diha
The "Saving-Investment" Identity. In the
national income accounts, there is a relationship
among net foreign investment in the U.S., private
savings, domestic investment, and the govern
ment budget deficit. Most macroeconomics text
books present the derivation of this relationship,
referred to as the "saving-investment" identity.4
The idea behind the identity is easy to understand
even without looking at the derivation. When
the need for funds to finance domestic business
investment and the U.S. budget deficit exceeds
the flow of private savings from American
households and businesses, then Americans
must borrow from foreigners or sell existing
assets to foreigners in order to raise part of the
needed funds. Borrowing from or selling assets
to foreigners constitute foreign investment in
the U.S. Accordingly, net foreign investment in
the U.S. is always equal to the government
budget deficit (for all levels of government,
combined) plus domestic investment minus
private savings:
Net Foreign Investment in the U.S. =
Government Budget Deficit +
Private Domestic Investment Private Savings
We can think of the government budget deficit
as the public-sector counterpart of net foreign
investment in the U.S. and of the gap between
private domestic investment and private savings
as its private-sector counterpart.
The saving-investment identity provides a
framework for analyzing the links between the
trade deficit and the relevant private- or publicsector decisions. If Americans increase domestic
investment but do not save more to finance the
additional investment, then net foreign invest
ment in the U.S. must rise. An example of do
mestic investment being financed by foreign
4See, for example, Robert E. Hall and John B. Taylor,
Macroeconomics (New York: W.W. Norton & Company, 1986)
pp. 34-38.
17
SEPTEMBER/OCTOBER 1988
BUSINESS REVIEW
investment in the U.S. would be the building of a
new auto plant that is financed by selling bonds
to foreigners. Similarly, if private savings fall or
if the government budget deficit increases while
domestic investment remains unchanged, the
identity implies that net foreign investment in
the U.S. must rise. An example of a decline in
savings matched by a rise in net foreign invest
ment in the U.S. would occur if households paid
for increased spending by liquidating foreign
assets.
Net foreign investment in the U.S. rose stead
ily from about -0.5% of GNP in 1980 to about
3.5% of GNP in 1987 (Figure 1). The rise was
notable in historical perspective. Between 1950
and 1979 there were only six years in which net
foreign investment in the U.S. was positive, and
even in those years its magnitude never rose
above 0.7% of GNP. From 1981 to 1983 the rise
in net foreign investment in the U.S. reflected a
sharp increase in the government budget deficit,
which increased from 1% of GNP in 1981 to
about 3.8% of GNP in 1983.
But budget deficits did not by themselves
account for the steady rise in net foreign invest
ment in the U.S.; the steady rise also reflected
the fact that the difference between domestic
investment and private savings rose steadily
from -3.5% of GNP in 1982 (indicating that
private savings exceeded private investment) to
1% of GNP in 1987.
WHY DID NET FOREIGN INVESTMENT IN
THE U.S. RISE?
The saving-investment identity tells us that
net foreign investment in the U.S. must always
FIGURE 1
Percent
4
Net Foreign Investment
in the U.S. and Its Counterparts
as a Percentage of GNP
1981
1982
1983
1984
1985
1986
1987
Figure 1 shows net foreign investment in the U.S. and its private- and public-sector counterparts as
percentages of GNP. The private-sector counterpart is the difference between gross private domestic
investment and gross private savings; the public-sector counterpart is the total government budget
deficit (on a national income accounting basis).
Digitized18
for FRASER
FEDERAL RESERVE BANK OF PHILADELPHIA
Private-Sector Decisions and the U.S. Trade Deficit
equal the sum of its public- and private-sector
counterparts. But it tells us nothing about the
economic forces maintaining this equality. For
net foreign investment in the U.S. to be positive,
Americans must be induced to liquidate their
foreign assets and/or foreigners must be induced
to increase their holdings of U.S. assets. What
were the inducements behind the net foreign
investments in the U.S., and the associated trade
deficits, in the 1980s?
A partial answer may be that foreigners wished
to accumulate U.S. assets because they came to
view the United States as a “safe haven" for their
investments. The safe haven story says that the
pro-investment image of the Reagan administra
tion, in conjunction with the debt crises in some
less developed countries, generated a flow of
funds seeking the safety of U.S. assets. The safe
haven story, however, is at best a partial explana
tion for the inflow of foreign capital to the U.S. in
the 1980s. If it were the whole story, we would
expect real, or inflation-adjusted, interest rates
to fall in the U.S. as foreigners competed with
each other to lend to Americans. In fact, real
interest rates rose sharply in the United States
relative to other industrial countries' in the early
1980s.5
The increase in U.S. real interest rates could
by itself account for the capital inflows, regard
less of the verdict on the safe haven story. The
high yields of U.S. assets could have made foreign
assets seem relatively less attractive, both to
Americans and to foreigners, and thus given rise
to the net foreign investments in the U.S. during
the 1980s. To increase their holdings of U.S.
assets, foreigners would first try to buy dollars in
the foreign exchange market, which would cause
5For more detailed discussions of real interest rate fluct
uations in the 1980s, and of economists' explanations for
these fluctuations, see Stephen A. Meyer, "Trade Deficits
and the Dollar: A Macroeconomic Perspective," this Business
Review (September/October 1986) pp. 15-25, and Olivier J.
Blanchard and Lawrence H. Summers, "Perspectives on
High World Real Interest Rates," Brookings Papers on Economic
Activity 2 (1984) pp. 273-334.
Behzad Diba
the dollar to appreciate. The stronger dollar in
turn would reduce U.S. exports and increase
U.S. imports, leading to a rise in the trade deficit
and allowing the desired increase in net foreign
investment in the U.S. to take place.
But what caused the increase in U.S. real inter
est rates? Partial answers are easy to come by.
Late in 1979, the Federal Reserve embarked on a
course of tight monetary policy to reduce the
high inflation rates of the 1970s. This policy
quickly translated into high real interest rates,
especially in 1980 and 1981. Moreover, the
growing government budget deficits (depicted
in Figure 1 as the public-sector counterpart of
net foreign investment in the U.S.) implied a
sharp increase in the government's need to
borrow, particularly after 1981, which also
helped raise interest rates. The combination of
tight money and large fiscal deficits is a textbook
recipe for high interest rates. But this combina
tion does not fully solve the puzzle of the U.S.
experience in the 1980s. Changes in private sav
ings and investment behavior also played a role.
Private Savings and Investment in the U.S.
An explanation that focuses solely on the com
bination of tight money and large budget deficits
fails to account for the changes in private savings
and domestic investment that occurred in the
United States during the 1980s. Consider the
textbook scenario about the effects of an increase
in interest rates caused by a monetary contraction
or by an increase in the budget deficit. The higher
interest rates would constitute a greater reward
for saving and therefore would stimulate private
savings.6 More importantly, the higher interest
rates would discourage domestic investment.
A typical course of events would run as fol
lows. The fiscal and/or monetary policy changes
would first raise interest rates on Treasury
6Numerous empirical studies, however, suggest that in
creases in interest rates do not have a large effect on private
savings. For a discussion of the relevant literature, see
Robert H. DeFina, "The Link Between Savings and Interest
Rates: A Key Element in the Tax Policy Debate," this Business
Review (November/December 1984) pp. 15-21.
19
SEPTEMBER/OCTOBER 1988
BUSINESS REVIEW
securities and thereby reduce the yield spread
between normally higher yielding corporate
bonds and bonds issued by the U.S. government.
This change in relative yields would curb the
demand for corporate bonds, causing their yields
to rise as well. This rise in interest rates in turn
would curb domestic investment by making it
more expensive for business firms to borrow.
The high interest rates would also make corpo
rate equities seem comparatively less attractive
to asset holders. The resulting lackluster stock
market also would make it difficult for businesses
to raise funds for financing investment
projects.
But the typical course of events outlined above
is markedly different from the actual U.S. experi
ence (illustrated in Figures 2, 3, and 4). Private
savings (as a percentage of GNP) declined fairly
steadily after 1981, and domestic investment (as
a percentage of GNP) rose sharply from 1982 to
1984 (Figure 2). Between 1980 and 1982, the
yield spread between corporate Aaa and
Treasury bonds was on the rise (Figure 3)—that
is, corporations with the highest credit rating
were willing to pay large premiums in order to
borrow, in contrast to the typical course of
events. The sharpest increases in the yield spread
occurred late in 1981 and early in 1982. Finally,
the S&P 500-stock index rose steadily from 1982
to 1987 (Figure 4). These figures show the actual
U.S. experience to be the opposite of what the
textbook scenario would lead us to expect.
These data are consistent with the view, ex
pressed in the Economic Report of the President for
1985, that the strong demand for dollar assets
during the first half of the 1980s reflected the
attractiveness of investment opportunities in
the United States. That corporations were willing
to borrow at very high interest rates until late
1982 (Figure 3) suggests that they had noticed
their attractive investment opportunities at an
early stage. The surge in corporate interest rates
subsided only after the booming stock market
(Figure 4) had made it easy to raise funds via
new equity issues. The stock market boom after
1982 suggests that asset holders came to share
businesses' enthusiasm about the investment
outlook. In sum, the rapid rise in domestic in
vestment from 1982 to 1984 was apparently due
to more attractive investment opportunities
offered by the U.S. economy. It also is one cause
of the rise in net foreign investment in the U.S.
What caused the attractive investment
opportunities offered by the U.S. economy?
FIGURE 2
FIGURE 3
Private Savings and
Domestic Investment
as a Percentage of GNP
Yield Differential Between
Corporate Aaa and
Long-Term Treasury Bonds
Basis Points
1/D
150
125
/\
100
75
1
\
DU
1981
Digitized 20
for FRASER
1983
1985
1987
1981
1983
N
s
/
r
1985
1987
FEDERAL RESERVE BANK OF PHILADELPHIA
Private-Sector Decisions and the U.S. Trade Deficit
Behzad Diba
FIGURE 4
S&P 500-Stock Index
Several answers come to mind. First, aided by
expansionary fiscal and monetary policies after
mid-1982, the U.S. economy seemed likely to
recover from the recession much faster than
other industrial economies. Domestic invest
ment has a general tendency to increase as the
economy recovers from a recession; in 1982 this
general tendency was probably accentuated by
the fact that investment prospects in other
industrial countries seemed likely to remain
mediocre. Second, the Economic Recovery Tax
Act of 1981 gave business firms substantial new
investment incentives, which were only partially
reversed in 1982.7 Finally, the success of the
Fed's earlier anti-inflationary policy seems to
have convinced the financial markets that the
7For a discussion of the effects of the 1981 and 1982 Tax
Acts on investment incentives, see Stephen A. Meyer, "Tax
Policy Effects on Investment: The 1981 and 1982 Tax Acts,"
this Business Review (November/December 1984) pp. 314.
economic expansion begun in 1982 could last a
long time without rekindling inflation.
While strong growth of investment spending
contributed to the growing gap between private
investment and savings in the 1980s, and thus to
the trade deficit, so too did a drop in private
savings. We have seen several reasons why U.S.
domestic investment rose in the early 1980s, but
an explanation of the decline in private savings
is harder to come by.8 Private savings is the sum
of two components: personal savings (the saving
done by households) and business savings
(composed of retained earnings and depreciation
8For a discussion of trends in U.S. savings rates and the
problems of finding an explanation for them, see Lawrence
Summers and Chris Carroll, "Why Is U.S. National Saving
So Low?" Brookings Papers on Economic Activity 2 (1987) pp.
607-42. Also see F. Gerard Adams and Susan M. Wachter
(eds.), Savings and Capital Formation: The Policy Options, pro
ceedings of a conference sponsored by the Savings Forum
and the Federal Reserve Bank of Philadelphia (Lexington
Books, 1985).
21
SEPTEMBER/OCTOBER 1988
BUSINESS REVIEW
allowances). Of the two components, business
savings remained fairly stable during the 1980s,
rising from 12.5% of GNP in 1980 to 13.5% by
1984, then declining back to 12.3% by 1987. But
personal savings dropped sharply, from a rate of
about 7.5% of disposable personal income in
1981 to about 3.8% in 1987 (Figure 5). This
decline in the personal savings rate during the
1980s is notable; between 1950 and 1979, it
averaged 7.2% and did not fall below 5.7% in
any year.
Why did American households decide to save
a smaller fraction of their disposable income—
or, equivalently, to consume a bigger fraction?
Economists have no definite answer. Some
claim, however, that the stock market boom
increased the value of household net worth and
made people feel wealthy enough to raise their
consumption expenditures faster than their
incomes were rising.
Even if we cannot answer the question of why
the personal savings rate declined, we can focus
on the critical question of whether the decline
had a quantitatively large effect on net foreign
investment in the U.S. A simple thought ex
periment will give a grasp of the magnitudes
FIGURE 5
Personal Savings
as a Percentage of
Disposable Personal Income
Percent
8 _
7
A
\/ v
>
3
1981
Digitized22
for FRASER
1983
—
1985
1987
involved. Suppose the personal savings rate in
1987 had been 7.2% (its 30-year average) rather
than the actual 3.8%. Personal savings in 1987
then would have been $229 billion instead of the
actual $120 billion. Assuming for our thought
experiment that domestic investment, business
savings, and the government budget deficit had
remained at their actual levels, the savinginvestment identity implies that net foreign
investment in the U.S. would decrease by the
same $109 billion amount as personal savings
increased. That is, instead of the actual 1987 net
foreign investment figure of about $157 billion,
the figure in the thought experiment would be
$48 billion. Since net foreign investment in the
U.S. represents an inflow of funds into the United
States to match the sum of the trade deficit and
the deficit on unilateral transfers, this sum also
would have been $109 billion smaller if the
private savings rate had been 7.2% in 1987 and
everything else had stayed the same.
It is, of course, difficult to say precisely how
net foreign investment in the U.S. would have
differed if the personal savings rate had not
declined; we don't know what changes in do
mestic investment, business savings, or the
budget deficit would have accompanied a hypo
thetically higher personal savings rate. But a
$109 billion improvement in net foreign invest
ment and in the trade deficit is essentially the
same as what we would get if we assumed, in our
thought experiment, a balanced budget for
federal, state, and local governments while
leaving private savings and domestic invest
ment unchanged. Thus, the change in private
savings behavior is as important as changes in
government budget deficits when it comes to
understanding the magnitude of U.S. trade
deficits in the 1980s.
ARE TRADE DEFICITS NECESSARILY
UNDESIRABLE?
A trade deficit is undesirable only to the extent
that its underlying causes are considered un
desirable. Our discussion suggests that at various
times during the 1980s, the causes of the U.S.
FEDERAL RESERVE BANK OF PHILADELPHIA
Private-Sector Decisions and the U.S. Trade Deficit
trade deficit included tight monetary policy, the
fiscal deficit, the reluctance of households to
maintain a high savings rate, and the attractive
ness of investment opportunities in the United
States. Economics does not provide a clear-cut
answer as to the desirability of a trade deficit that
reflects so many diverse factors—mainly because
some of these factors can benefit the current
generation of Americans at the expense of future
generations.
Suppose, for example, that American house
holds choose to accumulate foreign debt to
finance imports in order to increase their con
sumption. This increase in the current genera
tion's consumption will force future generations
of Americans to reduce their consumption rela
tive to their incomes because they will have to
spend part of their incomes to service the debt.
Economics provides no clear answer when it
comes to evaluating the gains of the current
generation vis-a-vis the losses of future genera
tions; it is a social and political issue.
In some cases, however, economics provides
us with a reasonably clear-cut answer. Consider,
for example, the rise in net foreign investment in
the U.S. from 1982 to 1984 and suppose that, as
argued above, it largely reflected the attractive
ness of investment opportunities in the United
States. Since the high yields of these U.S. invest
ments failed to raise private savings in the
United States, we can presume that the current
generation of Americans preferred not to sacri
fice their current consumption in exchange for
the future rewards of larger domestic invest
ment. Moreover, had the United States some
how avoided running the 1982-84 trade deficits,
foreigners would have been worse off because
they would have had to invest their savings in
less profitable projects in other countries.
Would future generations of Americans be
better off if the United States had somehow
avoided running the 1982-84 trade deficits?
Probably not; without the deficits, domestic
investment would have been lower, and future
generations would lose the income from some
of the investment projects. To see if future
Behzad Diba
generations would be better or worse off without
the 1982-84 trade deficits, we would have to
compare the interest payments on the foreign
funds borrowed during those years to the income
from the investment projects made possible by
the inflow of foreign funds. If American business
firms exercised good judgment in choosing
their investment projects, the income from the
projects should (on average) be large enough to
pay off the foreign creditors and leave a surplus
for the firms—which will be at least partly owned
by future generations of Americans. That profits
of American corporations have grown rapidly
during the past five years suggests that the in
vestment projects have generated such a sur
plus; that surplus is extra income that will allow
increased consumption for future generations.
The preceding example illustrates some
general principles. Trade balance fluctuations
are necessary whenever asset holders wish to
adjust their asset portfolios. They can serve to
allocate global savings to the most promising
investment opportunities. An increase in the
trade deficit that finances increased domestic
investment, as opposed to consumption or gov
ernment purchases, does not impose a burden
on future generations. Therefore, to arrive at a
simple measure of how a trade deficit will affect
the welfare of future generations of Americans,
we should look at the change in net foreign
investment in the U.S. in comparison to the
change in domestic investment. In other words,
we should use the gap between domestic in
vestment and net foreign investment in the U.S.
as a measure of the trade deficit's impact on
future generations' welfare. If that gap does not
narrow, then a growing trade deficit will not
make future generations worse off.
But even this measure is quite crude because
it implicitly assumes that future generations do
not benefit from borrowing abroad to finance
current government purchases. In fact, they
benefit from current government expenditures
that constitute public investment in creating
parks, highways, and other infrastructure.
Unfortunately, in practice we have no straight
23
BUSINESS REVIEW
forward way of classifying government expendi
tures into "public investment" and "public con
sumption." In many instances, the appropriate
classification is not even conceptually clear.
Expenditures on a military buildup, for example,
may or may not represent a valuable investment
in national security and technology that will
increase the welfare of future generations.
CONCLUSION
The U.S. trade deficit is the outcome of both
public- and private-sector decisions in the United
States and abroad. Focusing only on the trade
deficit masks the various factors that contributed
to the U.S. trade deficit in the 1980s. In particular,
the trade deficit's sharp increase in the early
1980s partly reflected an investment boom in
the United States that was not matched by an
increase in domestic savings and was not
necessarily undesirable. What might be cause
for concern is that after the investment boom
subsided, the trade deficit did not narrow; instead,
it was sustained by a decline in private savings
and by large government budget deficits.
The ultimate desirability of the government
expenditures that accompanied the budget de
ficits, or of any particular allocation of consump
tion between current and future generations,
cannot be judged on economic grounds alone.
However, assuming that concern about the trade
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SEPTEM BER/OCTOBER 1988
deficit is warranted, simple economic reasoning
has several implications for how the required
trade adjustment should be achieved. First, given
the likely inflationary consequences of any
attempt to generate substantially faster growth
of U.S. output, the adjustment to the trade bal
ance must involve slower growth of domestic
purchases. Second, because slower growth of
domestic investment would benefit neither cur
rent nor future generations, the required slowing
in the growth of domestic purchases must come
from temporarily slower growth of either gov
ernment purchases or consumer spending.
We have seen that a return of the personal
savings rate to a historically more "normal" level
could be as effective in reducing the trade deficit
as eradication of the combined government
budget deficits would be. So those who consider
the trade deficit alarming, and who also are pes
simistic about the prospects for a sharp reduction
of government budget deficits, can still hope for
a rebound in the personal savings rate. In fact,
since the stock market crash of October 1987,
the personal savings rate has rebounded some,
rising from 2.3% in the third quarter of 1987 to
3.8% in the second quarter of 1988. The increase
in the savings rate implies slower growth of
consumer spending, which, as long as a recession
is avoided, should be nothing but good news to
those concerned about the trade deficit.
FEDERAL RESERVE BANK OF PHILADELPHIA
Philadelphia/RESEARCH
Working Papers
The Philadelphia Fed's Research Department occasionally publishes working papers based on
the current research of staff economists. These papers, dealing with virtually all areas within
economics and finance, are intended for the professional researcher. Papers added to the Working
Papers Series in 1987 and the first part of 1988 are listed below.
A list of all available papers may be ordered from WORKING PAPERS, Department of Research,
Federal Reserve Bank of Philadelphia, 10 Independence Mall, Philadelphia, PA 19106-1574. Copies
of papers may be ordered from the same address. For overseas airmail requests only, a $2.00 per
copy prepayment is required.
1987
No. 87-1
Paul Calem, "Deposit Market Segmentation: The Case of MMDAs and Super-NOWs."
(Supersedes No. 86-3, "MMDAs, Super-NOWs, and the Differentiation of Bank
Deposit Products.")
No. 87-2
John J. Merrick, Jr., "Volume Determination in Stock and Stock Index Futures Markets:
An Analysis of Arbitrage and Volatility Effects."
No. 87-3
Richard P. Voith, "Compensating Variation in Wages and Rents."
No. 87-4
John J. Merrick, Jr., "Price Discovery in the Stock Market."
No. 87-5/R Loretta J. Mester, "Testing for Expense Preference Behavior Using Cost Data."
(Revision of No. 87-5.)
No. 87-6
Paul Calem and Janice Moulton, "Competitive Effects of Interstate Bank Mergers and
Acquisitions."
No. 87-7
Joel Houston, "The Policy Implications of the Underground Economy."
No. 87-8
Mitchell Berlin and Paul Calem, "Financing, Commitment, and Entry Deterrence."
No. 87-9
Joel F. Houston, "Estimating the Size and Implications of the Underground
Economy."
No. 87-10
Joel F. Houston, "Participation in the Underground Economy: A Theoretical
Analysis."
No. 87-11
John J. Merrick, Jr., "Hedging with Mispriced Futures."
No. 87-12
Linda Allen, Stavros Peristiani and Anthony Saunders, "Bank Size, Collateral and Net
Purchase Behavior in the Federal Funds Market: Empirical Evidence."
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for FRASER
FEDERAL RESERVE BANK OF PHILADELPHIA
No. 87-13
John J. Merrick, Jr., “Portfolio Insurance With Stock Index Futures."
No. 87-14
John F. Boschen and Leonard O. Mills, “Tests of the Relation Between Money and
Output in the Real Business Cycle Model."
No. 87-15
Anthony Saunders and Stanley Sienkiewicz, “The Hedging Performance of ECU
Futures Contracts."
No. 87-16
John J. Merrick, Jr., “Early Unwindings and Rollovers of Stock Index Futures Arbitrage
Programs: Analysis and Implications for Predicting Expiration Day Effects."
No. 87-17
Paul Calem, “On Estimating Technical Progress and Returns to Scale."
No. 87-18
Richard Voith, “Commuter Rail Ridership: The Long and Short Haul."
No. 87-19
Mark J. Flannery and Aris A. Protopapadakis, “From T-Bills to Common Stocks:
Investigating the Generality of Intra-Week Return Seasonality."
No. 87-20
Behzad T. Diba and Herschel I. Grossman, “Rational Bubbles in Stock Prices?"
No. 87-21
Brian J. Cody, “Exchange Controls and the Foreign Exchange Market: A Model of
Political Risk."
No. 88-1
1988
Mitchell Berlin and Loretta J. Mester, "Credit Card Rates and Consumer Search."
No. 88-2
Loretta J. Mester, “An Analysis of the Effect of Ownership Form on Technology: Stock
Versus Mutual Savings and Loan Associations."
No. 88-3
David Y. Wong, “Inflation, Taxation, and the International Allocation of Capital."
No. 88-4
Richard Voith and Theodore Crone, "Natural Vacancy Rates and the Persistence of
Shocks in U.S. Office Markets."
No. 88-5
Paul S. Calem and Gerald A. Carlino, “Agglomeration Economies and Technical
Change in Urban Manufacturing."
No. 88-6
Peter Linneman and Richard Voith, “Concentration, Prices, and Output in the Auto
mobile Industry."
No. 88-7
Brian J. Cody, “Exchange Controls, Political Risk, and the Eurocurrency Market: New
Evidence from Tests of Covered Interest Rate Parity."
27
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