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Federal Reserve
Bank of New York
Summer-Fall 1994
Volume 19
Quarterly Review
1
The Credit R ating Industry
Richard Cantor and Frank Packer
27
The Price R isk of Options Positions
Arturo Estrella, Darryll Hendricks, John Kambhu, Soo Shin, and Stefan Walter
44
M aking Sense of the Profits of Foreign Firms in the United States
D avidS. Las ter and Robert N. McCauley
76
The Baby Boom Generation and A ggregate Savings
Richard Cantor and Andrew Yuengert
92
M ortgage Security H edging and the Yield Curve
J u lia D. Fernald, Frank Keane, and Patricia C. Mosser
101
Has Excess Capacity Abroad Reduced U.S. Inflationary Pressures?
James A. Orr
107
Recent Trends in the Profitability of Credit Card Banks
Andrea Meyercord
112
Regional Employment Trends in the Second District
Charles Steindel and Lois Banks
Number 2
Federal Reserve Bank of New "York
Quarterly Review
Summer-Fall 1994
Table o f Contents
A
Volume 19
Number 2
r t ic l e s
1
T
he
C r e d it R a t in g I n d u s t r y
Richard Cantor and Frank Packer
Investors and regulators have been increasing their reliance on the opinions of the credit rating agencies.
This article shows that although the ratings provide accurate rank-orderings of default risk, the meaning of
specific letter grades varies over time and across agencies. N oting that current regulations do not explicitly
adjust for agency differences, the authors argue that a reassessment of the use of ratings and the adequacy of
public oversight is overdue.
27
T
he
P r ic e R is k
of
O
p t io n s
P o sit io n s
Arturo Estrella, Darryll Hendricks, John Kambhu, Soo Shin, and Stefan Walter
This article evaluates supervisory approaches to the measurement and capital treatment of the price risk of
options positions. The authors find that approximate value-at-risk rules tend to provide better estimates of
potential losses than simple strategy-based rules. The value-at-risk rules are particularly effective when they
adjust for nonlinear changes in options prices. The authors also consider the reporting burdens posed by the
different approaches and the consistency of the rules with existing and proposed supervisory frameworks.
44
M
a k in g
Se n se
of th e
P r o f it s
of
F o r e i g n F ir m s
in t h e
U
n it e d
S ta tes
DavidS. Las ter and Robert N . McCauley
The scant profit of foreign firms operating in the United States has prom pted many observers to suggest that
these firms understate their income to reduce their U .S. tax liability. This article offers an alternative expla
nation: a surge in foreign acquisitions of U .S. firms in the 1980s drove down the average profitability of foreign-owned firms in this country. The authors also find that high leverage and transfer pricing have con
tributed to the low U .S. profits of foreign firms.
76
T h e B a b y B o o m G e n e r a t io n a n d A g g r e g a t e S a v in g s
Richard Cantor and Andrew Yuengert
Many analysts predict a resurgence in national savings as baby boomers approach retirement. This analysis of
demographic trends and survey measures of savings and income suggests that such expectations may be ill
founded. Although baby boomer saving rates will likely rise over the next twenty years, aggregate saving
may not increase because other, low-saving age groups will be claim ing an increasing share of the population.
Moreover, despite a reputation for free spending, many baby boomers have accumulated substantial savings
already and may not raise their saving rates aggressively in their later years.
I n B r ie fs
92
M
ortgage
S e c u r it y H
Y
e d g in g a n d t h e
ie l d
C urve
Ju lia D. Fernald, Frank Keane, and 'Patricia C. Alosser
The authors find that the use of Treasury securities to hedge mortgage-backed security extension risk may
have magnified increases in long-term interest rates after the tightening of monetary policy in early 1994.
Substantial increases in the duration of m ortgage securities appear to have caused realignments of hedges and
portfolios that, in turn, had a significant im pact on the short-run movements of the Treasury market, partic
ularly for ten-year securities. This phenomenon may have altered the short-run dynamics of the yield curve
and thus changed the transmission of monetary policy.
101
H
as
E x c e s s C a p a c it y A b r o a d R
educed
U.S. I n f l a t i o n a r y P r e s s u r e s ?
James A. Orr
This article examines whether the sizable amount of excess capacity abroad in recent years has eased U.S.
inflationary pressures by keeping im port prices from rising as fast as the prices of U.S.-produced goods. The
analysis finds that overall import price growth has roughly kept pace with U .S. inflation because the effects
of lower inflation abroad have been offset by exchange rate changes. In the case of Japan, dollar depreciation
has rendered excess capacity basically ineffective against U.S. inflationary pressures.
107
R
ecent
T
r e n d s in t h e
P r o f it a b il it y
of
C r e d it C a r d B a n k s
Andrea Meyercord
Com petition among credit card issuers has increased sharply over the past few years. Despite this trend, the
profitability of credit card banks not only remains high relative to the rest of the banking industry but con
tinues to grow. This article examines recent trends in credit card bank profitability and, by looking beyond
the aggregate data, uncovers some important differences between credit card banks owned by bank holding
companies and those owned by nonbank firms.
112
R
e g io n a l
E m plo ym en t T
r e n d s in t h e
Second D
is t r ic t
Charles Steindel and Lois Banks
It is well known that job growth in the Second D istrict as a whole has not kept pace with national trends over
the last few years. This article offers a different perspective by assessing job trends in specific regions within
the District. The authors conclude that employment growth has resumed in most of the D istrict and that in
areas such as Northern New Jersey and Albany, the gaps with the national data are either small or narrowing.
The areas in the District that have been lagging are mainly those feeling the effects of corporate restructuring
and defense cuts— ills that should abate over time.
Note to
Q u a r t e r l y R e v ie w
With this issue o f the
Readers:
Q u a r t e r l y R e v ie w ,
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The Credit Rating Industry
Richard Cantor and Frank Packer
A
s financial market complexity and borrower
are used as the basis o f most investor guidelines and govern
diversity have grown over time, investors and
ment regulations, the variations in meaning could have seri
regulators have increased their reliance on the
ous im p licatio n s. M oreover, as the num ber o f agencies
opinions of the credit rating agencies. At the
increases, differences in ratings may encourage borrowers to
same time, the number of rating agencies operating in the
“shop” for the most favorable ratings. In light of the possi
United States and abroad has risen sharply. Together, these
b ilitie s for ratin g s m isu se, the current reevaluation o f
trends have prompted market participants and policymakers
ratings-dependent regulations and the adequacy of public
to reassess the perform ance o f the agencies and the adequacy
oversight seems well justified.
of public oversight of the ratings industry. This article pro
ratings-dependent regulations, and the reliability and com
T h e E v o l u t io n a n d E c o n o m ic s of th e
R a tin g s I n d u st r y
R a t in g A g e n c y O r ig in s , O w n e r s , a n d S ym bols
parability o f the agencies’ ratings. We examine the corre
The precursors of bond rating agencies were the mercantile
spondence of ratings with default rates and report differences
credit agencies, which rated merchants’ ability to pay their
among major agencies in their ratings for junk bonds, inter
financial obligations. In 1 8 4 1 , in the wake of the financial cri
national banks, and mortgage-backed securities.
sis o f 1 8 3 7 , Louis Tappan established the first mercantile
vides background for such a reassessment by investigating
the evolution and economics of the industry, the growth of
Our findings raise several questions about the cur
credit agency in N ew York. R ob ert D un su b seq u en tly
rent uses o f ratings. W hile the agencies provide accurate
acquired the agency and published its first ratings guide in
rank-orderings of default risk, the meanings o f specific rat
1859- A
ings vary over time and across agencies. Since these ratings
1849
sim ilar m ercantile rating agency was formed in
by John Bradstreet, who published a ratings book in
F R B N Y Q u a r t e r l y R e v ie w /S u m m e r - F a ll
1994
1
1857. In 1933, the two agencies were consolidated into Dun
contradict the agencies’ ratings. To the extent that the analy
and B r a d s tr e e t, w hich becam e the ow ner o f M o o d y ’s
ses underlying these recommendations are made public, they
Investors Service in 1962.
provide alternative perspectives to the ju dgm en ts o f the
The expansion of the ratings business to securities
rating agencies.
ratings began in 1909 when John Moody started to rate U.S.
As capital flows in international financial markets
railroad bonds. A year later, Moody extended his ratings
have shifted from the banking sector to capital markets, cred
activity to utility and industrial bonds. Poor’s Publishing
it ratings have also begun to make a mark overseas. Credit
Company issued its first ratings in 1916, Standard Statistics
ratings are in use in the financial markets of most developed
Company in 1922, and the Fitch Publishing Company in
economies and several em erging market countries as well
1924. The number of bond rating agencies in the U.S. revert
(Dale and Thom as 1991)- W ith demand rising in foreign
ed to three when Standard Statistics and Poor’s Publishing
countries, the number of foreign-based rating agencies has
Com pany m erged to form Standard and Poor’s (S& P) in
increased. Along with the four largest U.S. raters, one other
1941. The most significant new entry in the United States
U .S., one British, two Canadian, and three Japanese firms are
since that time has been the Chicago-based D uff and Phelps,
listed among the world’s “most influential” rating agencies
which began to provide bond ratings for a wide range of com
by the Financial Times in its publication Credit Ratings Inter
panies in 1982, although it had researched public utility
national. The principal characteristics of all eleven agencies
companies since 1932. Another m ajor ratings provider—
are reported in Table 1.
McCarthy, Crisanti, and Maffei— was founded in 1975 and
The ownership structures of the U.S. rating agencies
acquired by Xerox Financial Services before its fixed income
do not generally present serious conflict of interest problem s.1
rating and research service was merged into D uff and Phelps
The major agencies are all either independent or owned by
in 1991.
nonfinancial companies, though two had until recently been
The four major rating agencies face additional com
owned by financial companies. M oody’s is a subsidiary of Dun
petition from more specialized agencies. For example, Thom
and Bradstreet, which dominates the market for commercial
son Bankwatch and IBCA in the United States exclusively
credit ratings. Standard and Poor’s is a subsidiary of McGraw-
rate financial institutions, and A.M . Best rates insurance
H ill, a m ajor publishing company with a strong business
companies’ claims-paying abilities. More generally, the ana
information focus. Fitch, initially a publishing company, was
lysts employed by many financial institutions regularly make
bought by an independent investors group in 1989- D uff and
recommendations to buy or sell that im plicitly confirm or
Phelps Credit R atings is a subsidiary of D u ff and Phelps,
Table 1
S e l e c t e d B o n d R a t i n g A g e n c ie s
■■... ■...v .
. . .
Year Ratings
First Published
Credit Rating Agency
Home
Country
Year o f SEC
Designation
Employees
Ownership
Principal
Ratings Areas
19 0 9
M oody’s Investors Service (“M oody’s”)
U.S.
1975
674
Dun and Bradstreet
Full service
1922
Fitch Investors Service (“Fitch”)
U.S.
1975
200 +
Independent
Full service
19 2 3
19 7 2
Standard and Poor’s Corporation (“S&P")
U.S.
700+
M cG raw-H ill
Full service
Canadian Bond Rating Service (“CBRS")
Canada
1975
N .A.
26
Independent
Full service (Canada)
19 7 4
Thomson BankW atch (“Thom ”)
U.S.
40
Thomson Company
Financial institutions
1975
Japanese Bond Rating Institute (“JB R I”)
Japan
19 9 1
N.A.
91
Japan Economic Journal (Nikkei)
Full service (Japan)
19 7 7
D ominion Bond Rating Service (“D BRS”)
Canada
N .A.
20
Independent
Full service (Canada)
19 7 8
IBCA, Ltd. (“IB C A”)
U .K .
19 9 0
50
Independent
Financial institutions
19 8 0
D uff and Phelps Credit Rating Co. (“D u ff’)
U.S.
1982
Full service
Japanese Credit Rating Agency (“J C R A ”)
Japan
N .A.
160
61
D uff and Phelps Corp.
1985
Financial Institutions
Full service (Japan)
1985
Nippon Investor Service Inc. (“NIS”)
Japan
N.A.
70
Financial Institutions
Full service (Japan)
1975
McCarthy, Crisanti, and Maffei (“M CM ”)
(no longer in operation)
U.S.
19 8 3
N .A.
Acquired by D uff
and Phelps in 19 9 1
Full service (U.S.)
2
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Inc., whose affiliates offer investment management, financial
the performance risk o f m ortgage servicers, and the price
consulting, and investment research services. By late 1994,
volatility of mutual funds and mortgage-backed securities.
however, D u ff and Phelps C redit R atin gs is expected to
Increased foreign demand has also led to a dramatic
become an independent company as its shares are spun off to
overseas expansion of the established U .S. rating agencies.
the shareholders of D uff and Phelps, Inc., itself a closely held
Over the past ten years, M oody’s has opened offices in Tokyo,
company. Thomson Bankwatch was a subsidiary of Keefe,
London, Paris, Sydney, Frankfurt, and Madrid, and now rates
Bruyette, and Woods, a brokerage firm, until March 1989,
the securities of approximately 1,200 non-U.S. issuers (out of
when it was sold to the Thomson Corporation, a large private
more than 4 ,500 total). Standard and Poor’s has set up offices
international publishing conglomerate. Most of the non-U.S.
in Tokyo, London, Paris, M elbourne, Toronto, Frankfurt,
firms are also independent. The London-based rating agency,
Stockholm, and Mexico City, and has established affiliations
IBCA, is independently owned, as are the two Canadian rat
or acquired local rating agencies in Sweden, Australia, Spain,
ing agencies. Two of the rating agencies from Japan, however,
and Mexico. D u ff and Phelps has formed joint ventures in
are owned by consortia of financial institutions, including
M exico and several other Latin Am erican countries. The
some for which credit ratings are issued.
established U .S. agencies appear to have a competitive advan
Over time, the agencies have expanded the depth
and frequency of their coverage. The four leading U.S. credit
tage over their foreign counterparts in the business of provid
ing independent, credible securities ratings.
rating agencies rate not only the long-term bonds issued by
The bond ratings assigned by all the rating agencies
U .S. corporations, but also a w ide variety o f other debt
are meant to indicate the likelihood of default or delayed pay
instruments: municipal bonds, asset-backed securities, pre
ment of the security. Most of the rating agencies have long
ferred stocks, medium -term note programs, shelf registra
had their own system of symbols— some using letters, others
tions, private placements, commercial paper programs, and
using numbers, many both— for ranking the risk of default
bank certificates of deposit. More recently, ratings have been
from extremely safe to highly speculative. Gradually, howev
applied to other types of risks, including the counterparty
er, a rough correspondence among the major agencies’ ratings
risk posed by derivative products companies and other insti
has emerged (Table 2).2 To provide finer rating gradations to
tutions, the claim s-paying ability of insurance companies,
help investors distin gu ish more carefully am ong issuers,
Table 2
L o n g -T erm S enior D e bt R a ting S ymbols
Investment Grade Ratings
Speculative Grade Ratings
S&P and others
M oody’s
Interpretation
AAA
Aaa
Highest quality
S&P and others
M oody’s
Interpretation
BB +
Bal
Likely to fulfill
BB
Ba2
obligations; ongoing
BB-
Ba3
uncertainty
AA +
AA
A al
B+
B1
High risk
Aa2
B
B2
obligations
AA-
Aa3
B-
B3
A+
A1
Strong payment
A
A2
capacity
A-
A3
High quality
CCC+
ccc
Current vulnerability
Caa
to default, or in
CCC-
default (Moody’s)
BBB +
Baal
Adequate payment
c
Ca
In bankruptcy or
BBB
Baa2
capacity
D
D
default, or other
BBB-
Baa3
marked shortcoming
Notes: The other agencies listed in Table 1 use the rating symbols o f the first column, with the exception o f DBRS (H and L symbols in place o f + and —) and CBRS
(H and L symbols in place o f + and —, and + symbols that correspond to second and third letters). The agencies follow a variety o f policies w ith respect to the number o f
ratings symbols given below B—.
F R B N Y Q u a r t e r l y R e v ie w / S u m m e r - F a ll
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3
Fitch in 1973, Standard and Poor’s in 1974, and Moody’s in
Agencies charge fees that vary with the size and type
1982 started attaching plus and minus symbols to their rat
of issue, but a representative fee on a new long-term corporate
ings. Other modifications of the grading schemes — includ
bond issue ranges from 2 to 3 basis points of the principal for
ing the addition of a “credit watch” category to denote that a
each year the rating is maintained. Normally, the charge for
rating is under review — have also become standard. In the
any one bond issue has both a floor and a ceiling, and negoti
remainder of this article, the symbols currently employed by
ated rates are available for frequent issuers. For issuers o f com
Standard and Poor’s, Fitch, D uff and Phelps, and others are
mercial paper, M oody’s and Standard and Poor’s m aintain
used to refer to the ratings of all agencies.
quarterly charges based on amounts outstanding (up to 7
basis points) plus an annual fee.
T h e T r a n s it io n t o C h a r g in g I ssuers a n d t h e
R ole o f R epu ta tio n
encourage agencies to assign higher ratings to satisfy issuers,
Agencies initially provided public ratings of an issuer free of
the agencies have an overriding incentive to maintain a repu
charge, and financed their operations solely through the sale
tation for high-quality, accurate ratings. If investors were to
of publications and related materials. However, the publica
lose confidence in an agency’s ratings, issuers would no longer
tions, which were easily copied once published, did not yield
believe they could lower their funding costs by obtaining its
sufficient returns to justify intensive coverage. As the de
ratings. As one industry observer has put it, “every time a rat
mand on rating agencies for faster and more comprehensive
ing is assigned, the agency’s name, integrity, and credibility
service increased, the agencies began to charge issuers for rat
are on the line and subject to inspection by the whole invest-
W hile the current payment structure may appear to
ings. They then used these revenues to expand services and
products and to compete with private sector analysts at other
financial institutions.
The default of Penn Central on $82 million of com
mercial paper in 1970 was a catalyst in the transition to
W bile the cu rren t p a ym en t stru ctu re m ay appear
to encourage agen cies to a ssign h igh er ra tin gs to
charging issuers. The commercial paper market had grown
very rapidly in the 1960s with little regard for credit quality.
sa tisfy issuers, the agen cies h a ve an o verrid in g
Investors tended to assume that any firm with a household
in cen tive to m ain ta in a reputation f o r h ig h -
name was an acceptable credit risk. W hen Penn Central
defaulted during the 1970 recession, investors began to ques
q u ality, a ccu ra te ratings.
tion the financial condition of many companies and refused to
roll over their commercial paper. Facing a liquidity crisis,
many of these companies also defaulted. To reassure nervous
ment comm unity” (Wilson 1994). Over the years, the disci
investors, issuers actively sought credit ratings, and it be
pline provided by reputational considerations appears to have
came established market practice that new debt issues com
been effective, with no major scandals in the ratings industry
ing to m arket have at least one credit ratin g. W ith the
of which we are aware.1
demand for rating services rising, the agencies found they
In addition to putting an agency’s reputation at risk,
were able to impose charges on issuers. Fitch and M oody’s
inaccurate ratings m ight expose the agency to costly legal
started to charge corporate issuers for ratings in 1970, and
dam ages. However, the threat of legal liability for rating
Standard and Poor’s followed suit a few years later. (Standard
agencies has not yet materialized. Class action suits have been
and Poor’s started to charge municipal bond issuers for rat
brought against rating agencies following major failures —
ings in 1968.) Now, according to one estimate, roughly four-
such as the Washington Public Power Supply System default
fifths of Standard and Poor’s revenue comes from issuer fees
in 1983 and the Executive Life bankruptcy in 1991— but the
(Ederington and Yawitz 1987).
cases were dropped before verdicts were reached.
Digitized
4 for FRASER
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T he R a t in g s P r o c e s s
and
U
n so l ic it e d
R a t in g s
ings in these areas are often substantially lower than the
The process of obtaining a rating can be lengthy, requiring
solicited ratings and can affect the yield paid at issuance. Pro
significant time and effort on the part of the debt-issuer and
ponents claim that unsolicited ratings provide a powerful
its underwriter as well as the agency. The agencies base their
check against rating shopping, the practice of hiring only
ratings on both quantitative and qualitative assessments of
those agencies that offer favorable ratings. Critics complain
the borrowing company’s condition and the special provi
that unsolicited ratings are based on incomplete information,
sions of the particular security at hand. A staff committee at
because communication with the issuer is limited. Although
the agency usually votes on a recommendation by a senior
an agency assigning unsolicited ratings may appear to have
analyst after presentation and debate. The rating assigned,
an incentive to be unduly conservative so as to reward those
often accompanied by explanatory analysis, is first communi
firms that do pay for its ratings, this incentive may be offset
cated to the issuer and underwriter, and then to the public at
by the need to maintain a reputation for analytical credibility
large. The issuer frequently has the opportunity to appeal a
(Monro-Davis 1994).
rating if it is not satisfied, but in general the ratings process is
structured to hear the best case the issuers have to present
T he U se
of
R a t in g s
in
R e g u l a t io n s
before the rating is assigned. (More discussion of the informa-
Introduced as guides for unsophisticated investors, credit rat
tion-gathering and decision process can be found in Wilson
ings have acquired several new uses. Many mutual funds and
1994 and Ederington and Yawitz 1987.)
pension funds place limits on the amount of a portfolio that
The agencies maintain very different policies about
can be invested in non-investment-grade securities. Debt
assigning ratings not requested by the issuer. Some agencies
issuers and investors frequently introduce ratings explicitly
will issue ratings only upon request; other agencies will issue
into the covenants of their financial contracts and seek guid
unsolicited ratings. Standard and Poor’s rates all taxable secu
ance from the agencies on the structuring of their financial
rities in the U.S. domestic market registered by the Securities
transactions.
and Exchange Commission (SEC), regardless of whether the
As ratings have gained greater acceptance in the
rating was requested and paid for by the issuer. Standard and
marketplace, regulators of financial markets and institutions
Poor’s will not, however, assign unsolicited ratings for struc
have increasingly used ratings to simplify the task of pruden
tured securities and bonds issued by foreign companies
tial oversight. The reliance on ratings extends to virtually all
because it views the nonpublic information provided by the
financial regulators, including the public authorities that
issuer to be essential for analyzing these securities. Moody’s
oversee banks, thrifts, insurance companies, securities firms,
shares Standard and Poor’s policy of rating all SEC-registered,
capital markets, mutual funds, and private pensions. The
U.S. co rp o rate se cu ritie s, but Moody’s freq u en tly issu es u n so
early re gu lato ry u ses of ra tin g s drew on ly on the agen cy dis
licited ratings on structured securities and foreign bonds as
tinctions between investment grade securities, or those rated
well. In contrast, both Fitch and Duff and Phelps refrain from
BBB and above, and speculative securities, those rated BB
assigning unsolicited ratings to any security. Moreover, Duff
and below. Regulations required that extra capital be held
and Phelps will only make a rating public upon the request of
against speculative securities or prohibited such investments
its client (Ederington and Yawitz 1987).
altogether. Although the distinction between investment
Moody’s and Standard and Poor’s usually receive fees
grade and speculative securities remains an important one,
for ratings they would have issued anyway because companies
over time, regulatory capital requirements, disclosure re
want the opportunity provided by the formal rating process
quirements, and investment prohibitions have increasingly
to put their best case before the agencies. Moody’s unsolicited
been tied to other letter grades as well. The history of selected
ratings of issuers of structured securities and foreign bonds
uses of ratings by regulators is summarized in Table 3.4
are more controversial because such assessments are not part
Since the regulators adopted ratings-dependent
of an overall policy to rate all such securities. Unsolicited rat
rules, they have had to specify which agencies would qualify
FRBNY Q
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1994
5
for consideration under their regulations. The SEC currently
to be charged against capital. Similar rules were adopted by
designates six agencies as “nationally recognized statistical
many state banking departments.
rating organizations” (NRSROs), and the other regulators
In 1936, the Office of the Comptroller and the Feder
generally rely on the SEC’s designations. Given the large
al Reserve went further, prohibiting banks altogether from
number of designated agencies (and at least as many agencies
holding bonds not rated BBB or above by at least two agencies.
have applications pending), regulations must include meth
The new rules had far-reaching consequences because 891 of
ods for dealing with rating disagreements among the agen
1,975 bonds listed on the New York Stock Exchange were
cies. Most regulations simply accept either the highest rating
rated below BBB in 1936. Still in force for banks today, these
or the second highest rating, but the insurance regulators
restrictions on investments were extended to thrifts in 1989-
conduct independent analyses to resolve disagreements
As of the early 1930s, regulators of insurance com
among the agencies. The first approach is arbitrary and per
panies were relying on ratings to help determine the capital
haps inflationary, while the second approach incurs the cost of
to be put aside for securities held. In 1951, the National
establishing in-house analytical capacity.
Association of Insurance Commissioners (NAIC) established
a system of internal quality categories in which the top-qual-
T r a d i t i o n a l U se o f R a tin g s : D is tin g u is h in g
ity classification corresponded to ratings of BBB and above,
I n v e s tm e n t G r a d e F ro m S p e c u la tiv e S e c u r itie s
effectively establishing uniformity in the definition of
On the heels of a sharp decline in credit quality in 1931, the
“investment grade” across bank and insturance regulators
Office of the Comptroller of the Currency ruled that bank
(West 1973).5
holdings of publicly rated bonds had to be rated BBB or bet
Regulatory rules based on the distinction between
ter by at least one rating agency if they were to be carried at
investment grade and speculative securities have since
book value; otherwise the bonds were to be written down to
expanded. The SEC has required dealers to hold extra capital
market value and 50 percent of the resulting book losses were
against their inventories of speculative or “junk” bonds since
Table 3
S e l e c t e d U se s o f R a t i n g s in R e g u l a t i o n
Year
Adopted
Ratings-Dependent Regulation
Minimum
Rating
How Many
Ratings?
Regulator /Regulation
19 3 1
Required banks to m ark-to-m arket lower rated bonds
BBB
2
OCC and Federal Reserve examination rules
19 3 6
Prohibited banks from purchasing “speculative securities”
BBB
Unspecified
OCC, FDIC, and Federal Reserve joint statement
19 5 1
Imposed higher capital requirements on insurers’ lower rated bonds
Various
N.A.
N AIC mandatory reserve requirements
1975
Imposed higher capital haircuts on broker/dealers’
below-investment-grade bonds
BBB
2
SEC amendment to Rule 1 5 c 3 -l:
the uniform net capital rule
19 8 2
Eased disclosure requirements for investment grade bonds
BBB
1
SEC adoption o f Integrated Disclosure System
(Release # 6383)
19 8 4
Eased issuance o f nonagency mortgage-backed securities (MBSs)
AA
1
Congressional prom ulgation o f the Secondary
Mortgage M arket Enhancement A ct o f 1 9 8 4
19 8 7
Permitted margin lending against MBSs and (later) foreign bonds
AA
1
Federal Reserve Regulation T
19 8 9
Allow ed pension funds to invest in high-rated
asset-backed securities
A
1
Departm ent o f Labor relaxation o f
ERISA Restriction (PTE 89-8 8 )
1989
Prohibited S&Ls from investing in below-investment-grade bonds
BBB
1
Congressional prom ulgation o f the Financial
Institutions Recovery and Reform Act of 1989
19 9 1
Required money market mutual funds to lim it holdings
o f low-rated paper
A l*
It
SEC amendment to Rule 2a-7 under the
Investment Company A ct o f 1 9 4 0
19 9 2
Exempted issuers o f certain asset-backed securities from
registration as a m utual fund
BBB
1
SEC adoption o f Rule 3a-7 under the
Investment Company A ct o f 1 9 4 0
19 9 4
Proposal
W ou ld impose varying capital charges on banks’ and S&Ls’ holdings
o f different tranches o f asset-backed securities
AAA
& BBB
1
Federal Reserve, OCC, FDIC, OTS Proposed
Rule on Recourse and Direct Credit Substitutes
* Highest ratings on short-term debt, generally implying an A —long-term debt rating or better.
| If issue is rated by only one N RSRO , its rating is adequate; otherwise, two ratings are required.
6
FR BN Y
Q u a r t e r l y R e v ie w /S u m m e r - F a ll
1994
1975. In 1989, Congress passed legislation prohibiting
to essentially creating the nonagency mortgage-backed secu
thrifts from investing in junk bonds. In 1993, the Basle
rities market, SMMEA established a new regulatory cutoff
Committee on Bank Supervision proposed in its market risk
rating. The higher AA rating was chosen because mortgage-
guidelines that internationally active commercial banks deal
backed securities with full or partial government backing—
ing in securities should hold extra capital against their non-
the reference securities to which the new securities were com
investment-grade bond inventories as well. (This passage in
pared— were virtually all rated AAA or AA at the time.
the proposal mirrors a similar statement in the European
A few years later, the Federal Reserve Board, which
Community’s Capital Adequacy Directive governing the
had previously refrained from expanding its use of ratings
activities of security dealers domiciled in the Community.)
beyond the basic investment grade requirement for bank
The achievement of an investment grade rating eases
portfolio investments, also began to incorporate an AA cutoff
the burden of disclosure for the issuer of the securities. In
in certain of its prudential rules affecting bank supervision.
1982, the SEC started to require less detailed disclosure at
In recognition of the expanded role given to ratings by the
issuance for investment grade securities. In 1993, the SEC
Congress, the Board began to use AA as a cutoff in rules for
adopted Rule 3a-7, which made the investment grade rating
determining the eligibility of mortgage-related securities
a criterion for easing the public issuance of certain asset-
(1987) and foreign bonds (1989) as collateral for margin
backed securities (Cantor and Demsetz 1993).
lending.6
Embedding the investment grade distinction in reg
The single A rating has also served as a cutoff. The
ulations has simplified prudential oversight of financial insti
Labor Department, in its role as overseer of the private pen
tutions. Some of these regulations have, as a by-product,
sion industry, adopted a regulation in 1988 permitting pen
adversely affected the availability and cost of funds to below-
sion fund investments in asset-backed securities rated single-
investment-grade borrowers. West (1973) and Carey et al.
A or better (Baron and Murch 1993). The A rating gained
(1993) show that spreads rose for borrowers rated BB follow
further regulatory importance in 1990 when the N A IC
ing the adoption of regulations affecting bank and insurance
adopted new capital rules that applied the least burdensome
company investments in below-investment-grade securities.
capital charge to bonds with the NAIC quality designation
corresponding to a public rating of A or above.
T he E m e r g e n c e
of
N
ew
C u t o f f R a t in g s
Short-term ratings too have been important tools of
Regulators are increasingly using ratings other than BBB as
recent regulation. In 1991, the SEC adopted amendments to
thresholds in their rules. Each new regulatory use appears to
Rule 2a-7 of the Investment Company Act of 1940 that
have encouraged other regulators to expand their reliance on
imposed ratings-based restrictions on money market mutual
ratings. Some of these new rules have greatly influenced the
fund investments.7 Following the adoption of these amend
development of capital markets.
ments, mutual fund holdings of lower quality paper fell to
In 1984, to promote the development of a mortgage-backed securities market without the support of gov-
zero, and the total amount of lower quality paper outstanding
declined sharply (Crabbe and Post 1992).
ernment-related agencies (Government National Mortgage
Some regulations have gone beyond specific cutoff
Association, Federal National Mortgage Association, and
levels by incorporating schedules of multiple rating levels
Federal Flome Loan Mortgage Corporation), Congress passed
and corresponding restrictions and charges. As part of its
the Secondary Mortgage Market Enhancement Act (SMMEA).
1990 reform of rating procedures, the NAIC increased the
This act eased issuance and enhanced the marketability of
number of its quality categories from four to six and applied
mortgage-backed securities rated AAA or AA. In particular,
different regulatory restrictions to each category. Four years
it allowed these securities to be marketed up to six months in
later, the Federal Financial Institutions Examination Council
advance of the delivery of their underlying collateral and
(1994) joined bank and thrift regulators, including the Fed
exempted them from most states’ blue sky laws. In addition
eral Reserve, in a proposal to adjust capital charges on deposi
F R B N Y Q u a r t e r l y R e v ie w /S u m m e r - F a ll
1994
7
tory institutions’ holdings of structured securities on the
basis of credit ratings.
Nonetheless, the informality of the process and the
opaqueness of the acceptance criteria raise serious problems.
The requirement that an agency be widely used by major
T h e D e s ig n a tio n o f N R S R O s
investors before it can be designated as an N RSRO clearly
Under most current ratings-dependent regulations in the
favors incum bents. G iven the grow ing im portance of
United States, ratings matter only if they are issued by an
NRSRO status, new entrants in the ratings business who lack
NRSRO . The SEC first applied the NRSRO designation to
agencies in 1975 in referring to agencies whose credit ratings
could be used to determine net capital requirements for bro
Regulations generally refer directly to NRSRO
ker-dealers. Subsequently, the term was taken up by regula
rating levels without allowances fo r differences
tors other than the SEC and even by the private investment
across agencies.
community.
When the phrase N RSRO was first used, the SEC
was referring to the three agencies that had a national pres
this status may find it increasingly difficult to attract a wide
ence at that time, Moody’s, Standard and Poor’s, and Fitch.
following in the investment community. These concerns may
But as the public bond market and rating industry grew over
become more acute as the SEC considers applications from
time, other agencies have sought NRSRO designation from
foreign rating agencies.
the SEC. In 1982, Duff and Phelps received designation, fol
At present, the SEC does not require N RSR O s to
lowed by IBCA and Thomson Bank Watch in 1991 and 1992,
have uniform rating standards. In particular, the Commission
respectively. The designation of the latter two has been limit
has no explicit rule that “equivalent” letter grades must cor
ed to their ratings for banks and financial institutions only. In
respond to similar expected default rates. Nonetheless, regu
1983, the SEC granted NRSRO status to McCarthy, Crisanti,
lations generally refer directly to N RSRO rating levels with
and Maffei; however, this company’s credit rating franchise
out allowances for differences across agencies.8 Unless the
was acquired by Duff and Phelps in 1991- At least six foreign
way in which regulations use ratings is changed, all N RSRO
rating agencies currently have applications outstanding with
ratings of a certain level ought to correspond to the same level
the SEC for designation as NRSROs.
of credit risk. To achieve such consistency, the SEC may have
At present, the SEC’s procedures and conditions for
to develop additional acceptance criteria and ongoing moni
designating agencies as NRSRO s are not very explicit. If a
toring capacity. In recognition of these concerns, the SEC has
rating agency requests N R SR O status from the SEC, the
published a “concept release” that invites rating agencies,
SEC’s staff will undertake an investigation, analyzing data
corporations, and investors to comment on “the role of rat
supplied by the rating agency about its history, ownership,
ings in federal securities laws and the need to establish formal
employees, financial resources, policies, and internal proce
procedures for designating and monitoring the activities of
dures. Nevertheless, the principal test applied by the SEC to
N RSRO s” (SEC 1994a).
any agency seeking N R SR O status is that the agency be
“nationally recognized by the predominant users of ratings in
R e s o l v in g D is a g r e e m e n t s
the United States as an issuer of credible and reliable ratings”
A
(SEC 1994a). In effect, the SEC requires that the market
Most ratings-dependent regulations only require that a bond
already place substantial weight on the judgment of a rating
issue carry a single N R SR O ’s rating. However, issuers in the
agency. Market acceptance is determined by polling on an
United States commonly obtain at least two ratings on pub
informal basis. By giving the market a role in selecting
licly issued securities. Since both Moody’s and Standard and
NRSRO s, the SEC intends to weed out agencies that have not
Poor’s rate virtually all public corporate bond issues, a dual
already established a reputation for accurate ratings.
rating is fairly automatic. As a consequence, differences of
FR BN Y
8
Q u a r t e r l y R e v ie w /S u m m e r - F a ll
1994
a m o n g the
R a t in g
g e n c ie s
opinion across the rating agencies inevitably arise. Regula
the corresponding public credit rating. In practice, the SVO
tors have had to find a way to resolve these differences because
concentrates its resources on (1) determining a quality cate
most of their rules key off specific letter grades. Their
gory for unrated private placement securities and (2) resolv
approaches to the problem take two forms— explicit rules
ing differences of opinion among the agencies, where the
and independent analysis.
SVO may choose either the higher or lower rating (NAIC
The most common approach is to adopt an explicit
1994). At the cost of establishing the capacity to undertake
rule, recognizing either the highest or the second highest rat
independent analysis, the N A IC has developed a discre
ing, regardless of the number or level of the other ratings.
tionary use of ratings that calls for judgment in the interpre
The second-highest rating rule attempts to strike a balance
tation of split ratings and permits certain ratings to be dis
between a conservative policy (eliminating the highest rat
counted if they are viewed as too high.
ing) and a liberal policy (not necessarily using the lowest rat
ing). When the ratings industry was dominated by Moody’s
and Standard and Poor’s, this rule was effectively conservative
T he R e l ia b il it y
of
R a t in g s
In this section, we review the rating agencies’ historical
records in measuring relative and absolute risks of corporate
bond defaults. Many of the current uses of ratings presume
Agency ratings have been a less reliable guide...
to absolute credit risks: default probabilities
associated with specific letter ratings have
drifted over time.
accuracy on both counts. To be meaningful, ratings must, at a
minimum, provide a reasonable rank-ordering of relative
credit risks. In addition, however, ratings ought to provide a
reliable guide to absolute credit risk. In other words, the rat
ings levels corresponding to regulatory cutoffs should have a
fairly stable relationship to default probabilities over time.
Our review of the corporate bond defaults data assembled by
since the lower of two ratings was also the lowest rating. As
Moody’s and Standard and Poor’s suggests that the agencies
the number of NRSRO s has increased and issuers have begun
do a reasonable job of assessing relative credit risks: lower
to obtain three, four, or more ratings, the policy is potentially
rated bonds do in fact tend to default more frequently than
more liberal. Although regulators could conceivably adopt a
higher rated bonds. Agency ratings have been a less reliable
more conservative rule (such as the lowest rating), in areas
guide, however, to absolute credit risks: default probabilities
such as structured finance where Moody’s and Standard and
associated with specific letter ratings have drifted over time.
Poor’s do not attempt to rate every issue, issuers could re
sp o n d by d r o p p in g a g en cies th a t a ssig n e d the low er ra tin g s.
Our review is limited to Moody’s and Standard and
Poor’s ratings because only these agencies have a long history
The second approach, used by the NAIC, resolves
of rating a large number of corporate issues. We present data
differences of opinion among the rating agencies through
primarily from Moody’s because it has published more histor
independent analysis. The N A IC ’s Securities Valuation
ical data than Standard and Poor’s. By and large, however, we
Office (SVO) assigns each bond held by an insurance compa
believe that the patterns observed in Moody’s ratings are also
ny to one of six quality categories, and each category has a dif
present in Standard and Poor’s ratings, and we provide some
ferent implication for mandatory reserves. The six quality
support for this view in the text. In addition, the analysis is
categories are meant to correspond to different N RSRO pub
limited to corporate bond ratings and excludes commercial
lic ratings. (Category 1 corresponds to AAA,AA, and A; 2 to
paper ratings, m unicipal bond ratings, or asset-backed
BBB; 3 to BB; 4 to B; and 5 or 6 to CCC,C, or D ratings,
bonds. In these other markets, a study of rating reliability is
depending on the rating agency.) However, the SVO staff is
not possible either because defaults have been too rare, the
free to assign a rating that differs from the bond’s public cred
data are too hard to obtain, or the history of the market is too
it rating as long as their judgment implies a downgrade from
short.
FRBNY Q
u a r t e r l y R e v ie w /S u m m e r - F a ll
1994
9
M
e a su r in g
tion not already embedded in market yields. Even if ratings
R e l a t iv e C r e d it R is k s
Some very simple tests suggest that the rating industry mea
do not contain independent information about credit risk,
sures relative credit risks with reasonable accuracy. The capi
the use of ratings by investors and regulators may make sense
tal markets seem to validate the agencies’ judgments by pric
if ratings offer an efficient summary of this information.
ing lower rated bonds at higher average yields. Moreover,
Measuring ratings performance by contemporane
both average short-term and long-term default rates are cor
ous market yields, however, does not control for waves of
related in a sensible way with credit ratings. This evidence
market optimism or pessimism. The accumulation of ex post
implies that ratings provide a useful rank ordering of credit
evidence on bond performance provides a more precise score
risks.
card on ratings. Moody’s and Standard and Poor’s have made
For U.S. corporate bonds, market yields are general
such evidence available in their corporate bond default stud
ly closely related to their credit ratings. Table 4 reports the
ies, which calculate historical default rates among classes of
average yield spreads between corporate bonds and U.S. Trea
rated issuers.
suries by rating category for issues rated by Standard and
These studies indicate that lower corporate bond
Poor’s between 1973 and 1987. Each letter grade decline cor
ratings have indeed been associated with a higher probability
responds to a distinct increase in average yield spreads. The
o f default. The results of the M oody’s study (M oody’s
pattern of increasing yields as the ratings category is lowered
Investors Service 1994) are summarized in Chart 1, which
is extremely robust and holds without exception across all
reviews the default rates among rated issuers between 1970
years of the sample (Altman 1989)- While this correlation
and 1993. The upper left panel in Chart 1 presents the one-
may seem unsurprising and perhaps a weak test of ratings
year default rate for the entire sample of rated bonds. Mea
reliability, Artus, Garrigues, and Sassenou (1993) put forth
sured to 1/10 of a percentage point, the one-year default rates
evidence that, for the French bond market, a direct relation
are zero for all bonds rated A and above. The one-year default
ship between yield and the ratings of the largest French bond
rate rises to 2/10 of a percentage point for BBB issuers, and
rating agency is either weak or nonexistent.
1.8 and 8.3 percent for BB and B rated issuers, respectively.
This simple association of yields and ratings in the
The other three panels of Chart 1 show how the
U.S. bond market need not indicate the presence of a causal
default probabilities across Moody’s rating categories change
relationship. Rather, it may simply mean that the capital
as the time horizon is lengthened to five, ten, and fifteen
markets and the rating agencies basically agree on the factors
years.9 While the default probability increases with the time
that measure credit risk. Although the literature is volumi
horizon for each rating category, the negative relation
nous (see Ederington and Yawitz 1987), the evidence is
between default probability and ratings remains intact. A
mixed on whether credit ratings contain additional informa-
similar historical default study (Brand, K itto, and Bahar
1994) covering bonds rated by Standard and Poor’s between
Table 4
1981 and 1993 basically confirms the conclusions drawn
S preads betw een C o rporate B o n d s a n d U.S. T reasuries
1973—87 Averages
from the longer term study by Moody’s.
Rating
AAA
Consistent with the traditional importance of the
Basis Points
investment grade/non-investment-grade distinction, the
43
AA
73
A
99
BBB
1 66
BB
B
299
404
CCC
724
probability of default rises most dramatically once the invest
ment grade barrier is breached. In the Moody’s study, over a
five-year time horizon, the default probability is six times
higher for bonds rated BB than for those rated BBB. In con
Source: Altm an (198 9 ).
Note: Based on equally weighted averages o f monthly spreads per rating cate
trast, the comparable ratio of default probabilities for B-rated
versus BB-rated issues is much lower at 2.2, as is the ratio for
gory. Spreads for BB and B represent data for 1 9 7 9 —87 only; spreads for CCC,
BBB-rated versus A-rated issues at 3.2. The same ratios for
data for 1 9 8 2 —87 only.
10
FR BN Y
Q u a r t e r l y R e v ie w /S u m m e r - F a ll
1994
the Standard and Poor’s study were 4.8 (BB versus BB B), 3.0
default probabilities at the different ratings levels should
(BBB versus A), and 1.9 (B versus BB), respectively.
exhibit relative stability over frequencies longer than the
business cycle. In fact, legislators and financial regulators are
M ea su r in g A bsolute C r e d it R isks
presuming such a stability when they embed specific credit
The agencies do not intend their ratings to imply precisely
rating thresholds into law and regulation.
the same default probabilities at every point in time. In par
The reliability o f ratings as predictors of absolute
ticular, they are reluctant to make ratings changes based sim
credit risks can be evaluated by examining the default rates
ply on cyclical considerations even though the frequency of
associated with different ratings over time, particularly if the
defaults within rating categories clearly rises in recessions.10
time horizon is long enough to incorporate both ends of the
But even if cyclical variability in short-term default rates is
business cycle. Using M oody’s data between 1970 and 1994,
an inevitable result of a longer term perspective, long-term
Chart 2 reviews the progress of five-year cumulative default
Chart 1
A v e r a g e D e f a u l t R a t e s b y C r e d it R a t in g
P ercen t
10
One-Year Default Rates: 1 9 7 0 -9 3
AAA
AA
A
BBB
BB
B
AAA
P ercent
P ercent
50
50
Ten-Year Default Rates: 1 9 7 0 -8 4
AAA
AA
A
Fifteen-Year Default Rates: 1 9 7 0 -7 9
BBB
AAA
AA
A
BBB
BB
B
Source: Moody's Investors Service 1994.
FRBNY Q
u a r t e r l y R e v ie w /S u m m e r - F a ll
1994
11
rates for investment grade and non-investment-grade bonds.
In retrospect, the rise in default rates is unsurprising
The initial spike in 1970 for non-investment-grade bonds
given the general deterioration in credit ratios within rating
stems from the default that year of Penn Central and twenty-
classes that began in the m id-1980s. Chart 3 shows that the
six other railroad companies; default rates decreased dramati
median fixed-charge coverage and leverage ratios o f indus
cally the next year. For cohorts established since January
trial firms with B B B , BB , and B credit ratings from Standard
1971, however, the cumulative default rate within all rating
and Poor’s generally worsened between 1985 and 1991.
classes B B B and below has increased roughly threefold. The
These data suggest that a relaxation of credit standards may
1971 to 1989 increase is from 0.4 percent to 0.8 percent for
have occurred,11 perhaps as a result of the view commonly
A-rated bonds, 1.1 percent to 3.2 percent for BB B-rated
held in the late 1980s that even healthy corporations should
bonds, 5.1 percent to 19-7 percent for BB-rated bonds, and
increase leverage. In sum, the experience since 1970 indicates
11.1 percent to 34.3 percent for B-rated bonds. Five-year
that the correspondence of ratings to default probabilities is
default rates now lie well above the highs of 1970.
subject to substantial change over time.
T h ough five-year d efau lt rates rose d u rin g the
R a tin g s D ifferen ces across A g en cies
growth of the junk bond market in the 1980s, deterioration
in performance was common to both investment grade and
Differences among the agencies over specific ratings are com
non-investment-grade samples. The increase in default rates
mon, unavoidable, and even desirable to the extent that dis
actually began with the 1 976, 1977, and 1978 cohorts,
agreem ents prom ote better understanding. N onetheless,
whose five-year defaults rates incorporated defaults that
these differences can be highly problematic for ratings-based
occurred through the end of 1980, 1981, and 1982, respec
regulations in which the ratings o f any two N R SR O s are sub
tively. The rising trend in default rates, therefore, was initial
stitutable. Some of the observed differences can be attributed
ly related to the early 1980s recession but continued on
to alternative rating methodologies; others are the results of
through the decade.
the judgmental element in the ratings process. Many of the
Chart 2
T r e n d s in F iv e -Y e a r D e f a u lt R a te s b y C r e d it R a tin g
Percent
Percent
35
“ 1
BBB
Irivestment-Grade Is suers
B elow-I nvestment-(jrad e Issuers
A
1
b
1
1
25
\
#aa»•
♦
♦
A
♦■if•
♦
•
•
i i
1970
72
*
♦
♦
♦
*
#
•
•
76
78
1
15
1
V I1
\
¥
K
*T
'
BB
y\ <
K
r
r
__ i .
____
1
1
1
1'
*
10
*
i — l/ . - ?
74
••
•
•
•
* ..
1
••
•
•
•
•
\
20
y
___ A’ .___ .
I
1
1
#>
•
*
r
/
/
30
.V
p
i./\
i i
80
82
84
«
86
*
i
i
88 89
0 L
1970
. . .. i....i ..
72
74
t
76
i
l
78
1_L I I _
l
80
82
84
1
86
Source: Moody's Investors Service 1994.
Note: The five-year default rate indicates the share of issuers with a given rating at the beginning of the year that defaulted within the following five years.
FRBN Y
12
Q u a r t e r l y R e v ie w /S u m m e r - F a ll
1994
i
i ....
88 89
differences, however, may reflect system atic differences
ships among the scales are imprecise, the implicit presump
among agencies in the acceptable level of risk in any ratings
tion of the ratings-dependent regulations is that the corre
category. In this section, we review some of the basic differ
sponding ratings levels o f the different N R SR O s represent
ences in agency m ethodologies, average ratings, and rank
equivalent levels of credit risk and are interchangeable.
orderings of credit risks. We examine some of these differ
Periodically, the rating agencies articulate unique
ences in the context of three important areas of competition
ratings philosophies. For example, although M oody’s and
w ithin the in dustry— ratin gs for new-issue junk bonds,
Standard and Poor’s are primarily concerned with the likeli
banks, and asset-backed securities.
hood of default on interest or principal, Moody’s is prepared
to give a higher rating to an asset-backed security that is like
R a t in g D isa g r eem en ts St e m m in g F r o m
A lternative M e t h o d o l o g ie s
addition, in the area of rating sovereign credit risks, Moody’s
Although each agency publishes formal definitions of its var
is more reluctant to assign a higher rating to a country’s
ious letter ratings, these definitions provide very little insight
domestic currency obligations relative to its foreign currency
into the source of agency rating differences. The definitions
obligations than is Standard and Poor’s (Purcell, Brown,
imply that a different likelihood of default is associated with
Chang, and Dam rau 1 9 9 3 ) . The other agencies also differ
each letter grade, but do not quantify these differences.12 In
from their counterparts in certain particulars. For example,
addition, rating agencies do not explicitly compare their rat
unlike other agencies, D u ff and Phelps som etim es gives
ings with those of other agencies. As a practical matter, how
higher ratings for the medium-term notes than for the longer
ever, it appears that m arket participants have historically
term securities of the same issuers. And IBCA assigns higher
viewed the Moody’s and Standard and Poor’s scales as roughly
ratings to certain non-U.S. banks than do the U.S. agencies
equivalent and that the other agencies have attem pted to
because it attaches more weight to a foreign government’s
align their scales against those two. But while the relation-
implicit support of the banking system. Individual agencies
R a t io
R a t io
o f e a r n in g s t o f ix e d c h a r g e s
Coverage
o f d e b t t o a sse ts
Leverage
B rated firms
**»
>
„
B B B rated firms
%
• • • ...........
■
.
V
X
. - " ' X
\ -
.**
^
BB rated firms
----------- ^
\
\ _____
♦*
V
i
i
84
____ _______ m
86
i s..... i s i i ......
88
90
I
I
92
/
I
1982
I
I
84
—I
86
BBB rated firms
.........................
*•« *
__ _______
i
/
/
.+
' - X
B rated firms
1982
/
j
i
i
%
\
i
i
1
B B rated firms
✓
\/
M e d ia n C o v e r a g e a n d L e v e r a g e R a t io s o f I n d u s t r ia l Fir m s b y C r e d it R a t in g
1
Chart 3
■..........................................................................................................................................................-.
t-
ly to recover most of its principal in the event of default.13 In
I
..... !
88
I
....... 1
90
1
92
Source: Standard and Poor's.
Note: Data are three-year moving averages.
F R B N Y Q u a r t e r l y R e v ie w /S u m m e r - F a ll
1994
13
often describe the bases for their positions in their docu
ingly, M oody’s and Standard and Poor’s ratings were very
ments, but how their methodologies differ from other agen
highly correlated at 0 .9 7 , revealing a general consensus
cies’ generally m ust be inferred.
regarding rank ordering of relative risks.15
This rough equivalence in the rating standards of
B r o a d D ifferen ces O bserved in R a tin g s
Moody’s and Standard and Poor’s does not seem to extend to
Beattie and Searle (1992a) summarize the ratings differences
other rating agencies. Table 5 compares the ratings given by
observed in a large sam ple o f lon g-term cred it ratin gs
nine agencies with those given by Moody’s to the same bor
assigned in 1990 by twelve of the leading international rat
rowers. (Moody’s ratings are used as the basis of comparison
ing agencies and recorded by the Financial Times in its quar
simply because this agency has the most ratings in the data
terly publication Credit Ratings International. A m ong the
set.) Three measures of ratings differences are presented: the
5,284 rating pairs examined for 1,853 rated borrowers, 44
frequency of agreement, the correlation coefficients, and the
percent agreed precisely, 35 percent differed by one rating
average ratings differences. Standard and Poor’s agrees most
notch, 14 percent differed by two notches, and 6 percent dif
closely with M oody’s (64 percent), while the percentage
fered by three or more notches. (A “rating notch” is, for exam
agreement varies among the rest to a low o f 11 percent for the
ple, the gap between an A and A + rating.) The differences
Japan Credit R ating Agency. Compared with Standard and
across agencies as measured by the frequency of agreement
Poor’s ratings, the ratings of the other agencies exhibit larger
com pound two potential sources of disagreem ent— mean
average absolute ratings differences and less correlation with
rating scales and rank orderings.
Moody’s ratings.
The two largest N R S R O s, M oody’s and Standard
These differences in ratings reflect not only differ
and Poor’s, assign very sim ilar average ratings and rank order
ences in rank orderings of credit risks, but, to a large extent,
ings o f credit risks. O f the 1,398 cases in 1990 in which
differences in rating scales. Chart 4 shows that most of the
senior debt ratings were assigned by both companies, 64 per
cent were assigned the same rating, 16 percent were rated
higher by M oody’s, and 20 percent were rated higher by Stan
dard and Poor’s. The average (mean) difference in their rat
Chart 4
A v e r a g e D i f f e r e n c e in R a t in g s b e t w e e n M o o d y 's a n d
O t h e r A g e n c ie s in 1990
ings (including all those cases where their ratings were the
same) was only five-one-hundredths of a notch.14 N ot surpris-
R a t in g " n o t c h e s ”
2.0
Table 5
S e n i o r D e b t R a t i n g s o f N in e R a t i n g A g e n c ie s C o m p a r e d
w it h
M o o d y ’s R a t i n g s in 1 9 9 0
Name o f
Agency
Number
o f Join tly
Rated
Companies
Percentage
o f Ratings
That Are
Equal
Correlation
between
Ratings
Scales*
Average Ratings
D ifferences!
(“ +”=higher;
” =lower)
0 .7 8
CBRS
37
38
DBRS
28
0.8 3
0 .7 2
D uff
51
524
50
0 .9 2
-0 .2 5
0 .3 8
Fitch
295
47
0.9 0
0 .2 9
IBCA
13 4
28
0.83
0 .0 5
JBR I
65
11
0.6 7
1.75
3 43
26
0.90
-1 .0 4
33
13 9 8
33
64
0.6 3
0 .9 7
1.0 9
0.05
MCM
NIS
S&P
Lower ratings than Moody's
-1.5 I_______ I_______ I_______ 1_______ I_______ I_______ 1_______ I_______ 1_______ f
MCM DBRS IBCA
S&P
Fitch
D&P CBRS
NIS
JBRI
Source: Beattie and Searle 1992.
Source: Beattie and Searle 1 992a.
* The Pearson product-mom ent correlation.
t Differences are measured in rating “notches.” For example, the gap between
A+ and A - is two ratings notches.
FR BN Y
14
Q u a r t e r l y R e v ie w /S u m m e r - F a ll
1994
Note: Rating notches are the gaps between ratings. For example, the gap
between A+ and A- is two notches. Average differences are calculated using
only the ratings of issuers that were rated by both Moody's and the
other agency.
agencies rate higher than M oody’s, although M cCarthy,
(18.2 percent) in 1993 (Fridson 1994). O f the nearly 700 new
Crisanti, and Maffei (since merged with D u ff and Phelps)
U .S. junk issues between 1989 and 1993 listed in First
rates on average a whole rating notch lower. The two largest
Boston’s annual High-Yield Handbook, 96 percent are rated
American agencies after M oody’s and Standard and Poor’s,
by both Moody’s and Standard and Poor’s. Ju n k bond issuers,
Fitch and D uff and Phelps, each rate about a third of a notch
however, are increasingly seeking third and fourth ratings as
higher than Moody’s .16 The Canadian Bond Rating Service,
well. D uff and Phelps and Fitch, which respectively rated 16
N ip p on Investors Service, and the Ja p a n C redit R atin g
and 4 percent of all issues in the 1989-93 period, have signif
Agency rated on average 0.78, 1.09, and 1.75 notches higher
icantly increased their rating activity in the past few years
than Moody’s, respectively.
(see Table 6).
The junk bond sample reveals more striking differ
R a tin g s fo r N ew -I ssue J u n k B o n d s
ences in agency measurements of absolute and relative credit
From the point of view of regulatory practice, a rise in the
risks than does the broad sample. Standard and Poor’s and
number of rating agencies increases the likelihood that mar
M oody’s are much more often at odds in the ratings they
gin al borrowers w ill m eet m in im um ratin gs thresholds
assign junk bond issuers: if we compare the junk bond ratings
in Table 7 with the ratings for the broad sample in Table 5,
we find smaller frequencies of agreement and smaller correla
A rise in the num ber o f ra tin g agen cies increases
tion coefficients. The providers of third (and fourth) opinions
the lik elih ood th a t m a rgin a l borrow ers w ill meet
in this sector, D uff and Phelps and Fitch, also appear to dis
agree with Moody’s with greater regularity and on a greater
m inim um ra tin gs thresholds.
scale in the junk bond sample.
because (1) natural variation in opinion increases the proba
bility o f receiving at least one satisfactory rating, and (2)
some rating agencies may have higher average rating scales
Table 7
C r e d it R a t in g s A s s ig n e d t o J u n k B o n d I ssu e r s in
1 9 8 9 - 9 3 : C o m p a r in g t h e R a t in g s o f S& P, D u ff & P h e l p s ,
a n d F it c h w it h M o o d y ’s R a t in g s
enabling more borrowers to meet regulatory cutoffs. We can
definitions of investment grade securities by docum enting
Name of
Agency
Number
o fjo in tly
Rated
Companies
agency disagreements in the junk bond market.
S&P
67 2
41
0.83
D uff
11 3
28
33
14
0 .7 9
-0 .0 0 3
0 .9 65
0 .6 9
1.3 9 3
observe the impact of m ultiple rating agencies on regulatory
As generally defined, any issue is considered “junk”
that has at least one rating below the BB B - level from either
Moody’s or Standard and Poor’s. After falling off in the early
1990s, junk bond issues reached a new high of $57 billion
Fitch
Percentage
o f Ratings
That Are
Equal
Correlation
between
Ratings
Scales*
Average Ratings
Differences!
(“ +”=higher;
lower)
Sources: First Boston 19 90—94; Federal Reserve Bank of New York staff estimates.
* The Pearson product-mom ent correlation.
f Differences are measured in rating “notches.” For example, the gap between
A+ and A —is two ratings notches.
Table 6
M a r k et S hares
of
N f.w -I ssu e U .S . J
unk
B o n d R a t in g s : 1 9 8 9 - 9 3
Percent o f New Issues
Year
M oody’s
S&P
D uff
19 8 9
19 9 0
100
80
99
80
40
19 9 1
19 9 2
100
100
94
97
19 9 3
97
98
Fitch
Memo:
Total Number
o f Issues
116
24
0
0
12
24
5
13
4
233
301
7
5
42
Percent o f D ollar Volum e
Memo:
Total Volume
(Billions o f Dollars)
Year
M oody’s
S&P
D uff
19 8 9
19 9 0
100
100
21
99
99
72
0
0
19 9 1
19 9 2
100
100
21
24
9 .9
99
99
28
5
19 9 3
99
99
19
7
3 8 .9
54.1
Fitch
2.9
0.5
Sources: First Boston 1 9 9 0 —94; Federal Reserve Bank o f New York staff estimates.
F R B N Y Q u a r t e r l y R e v ie w /S u m m e r - F a ll
1994
15
For the newer rating agencies, many of the observed
grade rating from the major two agencies obtained a third
differences may be related to a difference in their absolute
opinion. O f these thirty-four firms, twenty-nine obtained a
scales in rating credit risks. W hile M oody’s and Standard and
second investment grade rating. Am ong issuers that received
Poor’s rate about the same on average for jointly rated issues,
m arginally below -investm ent-grade ratings (B B -ratin gs)
D uff and Phelps and Fitch ratings are between 1 and 1.5 rat
from both M oody’s and Standard and Poor’s, 26 percent
ing notches higher than M oody’s or Standard and Poor’s.
obtained a third rating. O f these thirty-four firms, sixteen
These differences greatly exceed those reported in Table 5 for
obtained an investment grade rating. In sum, the demand for
the aggregate sam ple o f bond issues. Thus, differences of
third ratings increases with the issuer’s proximity to invest
opinion between the two largest agencies and the smaller
ment grade, and the opportunity to seek third and fourth rat
agencies appear to be greater for junk bonds than for invest
ings has enabled a number of firms to achieve investment
ment grade securities.
grade status under certain regulations.
Given the possibilities for split ratings, the decision
to employ a third rating agency is not random. Chart 5 relates
I n t e r n a t io n a l B a n k R a tin g s
the frequency with which issuers seek a third rating to the
As capital markets have become increasingly global, interna
ratin gs received from M oody’s and Standard and Poor’s.
tional considerations have taken on greater importance in the
Issuers are more likely to obtain a third rating if they receive
ratings industry. U.S. rating agencies have been expanding
near-investment-grade or mixed (speculative grade/invest
their presence overseas, and non-U.S. rating agencies have
ment grade) ratings from M oody’s and Standard and Poor’s.
been proliferating. In this section, we review international
In particular, 46 percent of the firms with one investment
ratings differences in the senior debt ratings of banks.
Credit ratings are particularly important to banks
(through counterparty exposure lim its, letters of credit, and
Chart 5
nondeposit sources of funds),17 and a large number of ratings
T h e D e c is io n t o O b t a in a T h ir d R a t in g
Percent
in the industry are cross-border ratings. In addition, the
potential designation of certain foreign agencies as N R SR O s
o f is s u e s
60
may have considerable im pact on the activities of foreign
banks in the United States.
Dominant in many other industry sectors, M oody’s
and Standard and Poor’s are the leading agencies in the rat
ing of banks. O f the 1018 banks worldwide for which long
term bond ratings were available in January 1994, M oody’s
and Standard and Poor’s rated 64 and 55 percent, respective
ly (Financial Times 1994).18 When the sample is lim ited to
just those 580 rated banks dom iciled outside the U nited
States, Moody’s and Standard and Poor’s still rated 57 and 46
percent, while IBC A was in third position at 31 percent.
BBB/BB
BB/BB
C o m b in a t io n
BB/B
o f r a t in g s a s s ig n e d b y
B/B
M
o o d y 's a n d
B/CCC or
CCC/CCC
S&P
their home countries, most of the other agencies tend to spe
cialize in the ratings of banks of their own nationality (see
Source: First Boston 1990-94.
Notes: The sample consists of 671 junk bond issues brought to market
between 1989 and 1993. The issues received the following combinations of
ratings from Moody's and Standard and Poor's: 74 rated BBB/BB, 132 rated
BB/BB, 79 rated BB/B, 359 rated B/B, and 27 rated B/CCC or CCC/CCC.
Each bar in the chan indicates the fraction of issues that were given a third
rating from another agency.
Digitized
16 for FRASER
FRBN Y
W hile these three leading agencies rate many banks outside
Q u a r t e r l y R e v ie w /S u m m e r - F a ll
1994
Table 8).
Agencies appear to disagree more in their measure
ment of credit risks for banks than in their risk measurement
for other industries. In Table 9, the bank ratings of nine lead
ing rating agencies generally show lower frequencies o f
Japanese agencies, the wider disagreem ent reflects higher
agreement and higher absolute ratings differences relative to
average rating differentials.
Moody’s than does the broader ratings sample described in
National differences in methodology and approach
Table 5 .19 The differences are greater for the agencies of some
may also help explain the variation in international bank rat
countries than for the agencies of others: in particular, the
ings. For example, the accounting for nonperforming loans
ratings of Japanese agencies differ much more from those of
and reserves is not standardized by country, and opinions vary
M oody’s than do the ratings of other agencies. W hat accounts
widely regarding the extent to which particular governments
for the wide disagreement? For the U.S. and Canadian agen
lend im plicit support to specific banks in the banking sys
cies, agreement concerning relative risk declines as we move
tem. Indeed, judgm ents regarding controversial issues are
from the broad ratings sample to the bank sample, as evi
related to some degree to the nationality of rating agencies.
denced by lower correlation coefficients. By contrast, for the
When raters are from the same country, agreement about the
relative ranking of issuers, as measured by the coefficient of
correlation, tends to be higher than when they are not.20
Table 8
Are observed bank ratings consistent with earlier
P e r c e n t a g e M a r k e t S h a r e s o f In t e r n a t io n a l B a n k
R a t i n g s in
1994
research concluding that agencies judge issuers from their
Agency
Home
Country
A ll
Banks
U.S.
Banks
Non-U.S.
Banks
CBRS
DBRS
JC R A
JB R I
NIS
Fitch
D uff
M oody’s
S&P
Thom
IBCA
Canada
Canada
Japan
Japan
Japan
U.S.
U.S.
U.S.
U.S.
U.S.
U .K .
2.1
0.2
4 .0
5.5
4 .0
3.1
5.0
8 .4
17 .6
6 9 .6
50.3
9.7
3 0 .0
0.4
10.0
0.0
0.0
0.0
7.6
5.8
9.4
17.1
3 6 .8
7 5 .8
6 6 .3
16 .9
23.5
0.8
0.8
64 .3
3 5 .9
3.4
35.7
Memo:
Home Country
Ratings as a
Percentage o f
Total
Each i
9 5 .2
9 6 .1
7 8 .9
7 9 .3
7 0 .0
9 4 .9
9 7 .6
50 .8
6 1 .9
8 1.3
9.2
Sources: Financial Times 1994; Federal Reserve Bank of New York staff estimates.
own country more leniently (Beattie and Searle, 1992b)?
When the ratings of all banks evaluated by both home-coun
try and foreign agencies are aggregated, the average home
rating exceeds the average foreign rating by one-half of a rat-
Chart 6
A v e r a g e S e n io r D e b t R a t in g s A s s ig n e d t o B a n k s b y
H o m e a n d F o r e ig n A g e n c ie s
Ratings
Table 9
I n t e r n a t io n a l B a n k R a t in g s o f N i n e R a t in g A g e n c ie s
C o m p a r e d w i t h M o o d y ’s R a t i n g s i n
Name of
Agency
Number
o f Jointly
Rated
Companies
Percentage
o f Ratings
That Are
Equal
1994
Correlation
between
Ratings
Scales*
Average Ratings
Differences'^
(“+”=higher;
” =lower)
CBRS
11
9
0 .5 2
0 .3 6
DBRS
17
0 .6 1
0 .8 4
- 0 .5 3
0 .1 7
D uff
13 9
29
42
Fitch
68
44
0 .7 7
0 .3 8
IBCA
206
38
0.88
0 .5 1
JC R A
19
0.8 2
JBR I
19
0.7 3
0 .8 1
2 .6 3
2 .4 2
0.7 7
NIS
35
11
0
6
S&P
351
37
Canadian
banks
Japanese
banks
U.K. banks
2 .4 0
- 0 .1 5
Sources: Financial Times 1994; Federal Reserve Bank o f New York staff estimates.
* The Pearson product-mom ent correlation.
f Differences are measured in rating “notches.” For example, the gap between
A+ and A —is two ratings notches.
U.S. banks
A ll U.S.,
Canadian, Japanese,
and U.K. banks
Sources: Financial Times 1994; Federal Reserve Bank of New York
staff estimates.
Notes: Observations are limited to banks with both home country and foreign
country senior debt ratings. Sample sizes for the five bank groups (from left to
right) are 100, 17, 35, 18, and 170.
FRBNY Q
u a r t e r l y R e v ie w /S u m m e r - F a ll
1994
17
ing notch. However, the results differ greatly depending on
International ratings differences are o f particular
the nationality of the bank (Chart 6). While U .S. and Canadi
importance at the present time because the SEC is reviewing
an banks receive lower home ratings than foreign ratings,
numerous applications for N R SR O designation from agen
Japanese and U .K . banks receive higher home ratings. At
cies of foreign countries. Differences among the agencies of
least in this sample, observed differences between home and
different countries and the tendency of many agencies to
foreign ratings reflect the relative toughness of each country’s
focus on the rating of banks from their home countries imply
agencies rather than a more general hom e-country bias.
that if N R SR O status were to be granted to the two Canadian
W hether the rated bank was from the same country or not
and three Japanese rating agencies, the number of Canadian
bore little relationship to the differences between the ratings
and Japanese banks reaching regulatory cutoff ratings would
of non-U.S. agencies and M oody’s.
increase considerably. As Chart 7 shows, o f the fifty-three
Chart 7
Im p l i c a t i o n s o f E x p a n d i n g t h e N u m b e r o f N a t i o n a l l y R e c o g n i z e d S t a t i s t i c a l R a t i n g O r g a n i z a t i o n s ( N R S R O s )
Japanese Banks
Canadian Banks
Top N RSRO Rating
Top N RSRO Rating
Top O verall Rating
Top Overall Rating
Source: Financial Tim s 1994.
Notes: The Japanese sample and the Canadian sample consist of seventy-two and fifty-three banks, respectively. Top NRSRO rating is the highest long-term rating of
those assigned by Duff, Fitch, IBCA, Moody's, S&P, and Thomson. Top overall rating is the highest long-term rating of those assigned by the NRSROs and the
following non-NRSROs: CBRS, DBRS, JBRI, JCRA, and NIS.
FRBN Y
18
Q u a r t e r l y R e v ie w /S u m m e r - F a ll
1994
Canadian banks with senior debt ratings listed in the Finan
Standard and Poor’s was the undisputed leader in M BS and
cial Times Credit Ratings International (1994), the share receiv
A BS ratings. In the late 1980s, Moody’s caught up consider
ing an N R SR O credit rating of at least AA- would rise from
ably and D u ff and Phelps made significant inroads in the
23 percent to 55 percent. Sim ilarly, o f the seventy-four
A BS market. Since then, Fitch has made great strides in mar
Japanese banks with senior debt ratings listed in the same
ket share, actually leading the m arket for M BSs in 1994,
publication, the share receiving an N R SR O rating of at least
while the other agencies’ shares have fluctuated. Charts 9 and
AA- would rise from 20 percent to 48 percent.
10 summarize the available data on these two markets since
1989- (Since more than one agency can rate each security, the
R a tin g s fo r M o r t g a g e - a n d A sset -B a ck ed
S ecu rities
sum of the shares exceeds 100 percent.)
U nlike the corporate bond m arket, the M BS and
C o m p etition am on g the ratin g agencies is p articu larly
A BS m arkets are lim ited alm ost entirely to highly rated
marked in the rating of mortgage-backed and asset-backed
issues, typically either AA or AAA for M BSs, and A or AAA
securities (MBSs and ABSs).21 Issuers often seek ratings from
for ABSs. The need for high ratings appears to arise from the
just one or two companies, and as we see below, Fitch and D uff
advantages regulations confer on highly rated (particularly
and Phelps have increased market share. Banks and securities
M BS) issues and from investors’ concerns about the quality of
firms generally consult directly with the rating agencies to
the collateral as well as their unfamiliarity with the compli
find out how M BSs and ABSs can be structured to obtain high
cated structures of the securities. The relatively small share of
credit ratings. The agencies analyze the asset pools to be secu
M BSs and ABSs that are rated less than A consist largely of
ritized to determine the adequacy of the credit support under
“B ” tranches that are subordinate to much larger, highly
lying each tranche of structured transactions. Agency dis
rated senior tranches. The subordinated tranches tend to be
agreements normally center on the criteria that establish the
amount of credit enhancement required for a specific rating.
These differences of opinion are not normally evident in the
ratings per se because issuers structure their securities to
obtain the desired ratin gs from the agen cies they hire.
(Moody’s occasionally assigns unsolicited ratings that indicate
its disagreement with the higher ratings assigned by other
agencies.) Market observers have expressed concern that com
Chart 8
Is s u a n c e o f A s s e t - b a c k e d a n d N o n a g e n c y
M o r t g a g e - b a c k e d S e c u r it ie s
Billions of dollars
120
--------------
petitive pressures have led agencies to compete on ratings cri
teria, potentially underm ining the reliability of the ratin gs.22
Industry analysts normally distinguish between two
broad categories of M BSs, those backed by government agen
cies such as the Federal National M ortgage Association and
private label issues that securitize jumbo m ortgages, com
mercial m ortgages, and various other so-called nonconform
ing first m ortgages that the governm ent agencies do not
securitize. The ABS market securitizes shorter duration asset
pools such as credit card receivables, auto loans, and home
equity loans. The M BS and ABS markets have grown very
rapidly since 1989 (Chart 8).
Rating agency market shares for M BS and ABS rat
ings have shifted considerably over time. In the m id-1980s,
1989
90
91
92
93
94
Sources: Asset Sales Report; Inside Mortgage Finance; Federal Reserve Bank of
New York staff estimates.
Note: Mortgage-backed and asset-backed volumes for 1994 are annualized
using data through April and June, respectively.
FRBNY Q
u a r t e r l y R e v ie w /S u m m e r - F a ll
1994
19
privately placed and are often rated by just a single agency or
carry no rating at all.
emergence of market competition have been particularly dra
matic in the case of private-label mortgage-backed securities.
M BS and A BS structures typically contain credit
U n til the m id -1 9 8 0 s, Standard and Poor’s was the only
protection so that the securities are less risky than the underly
agency ra tin g these se cu ritie s, and its requ ired cred it
ing asset pools. The forms of the credit enhancements vary
enhancements for reaching target ratings represented the
widely and include bank letters of credit, bond insurance com
industry standard. In 1986, Moody’s entered the market with
pany gu aran tees, subordin ated interests, cash collateral
criteria that were slightly different. W hile its standards were
accounts, and reinvestment of the excess cash flows generated
stricter than those o f Standard and Poor’s in some areas,
by the asset pools themselves. Since all enhancements are cost
M oody’s set lower enhancement requirem ents for certain
ly, issuers prefer structures that achieve a given rating with the
types of mortgage pools (shorter term, negative amortization,
smallest enhancements and choose rating agencies with the
and convertible adjustable rate mortgages) and subsequently
most lenient credit enhancement requirements, provided the
gain ed m arket share in those areas. In 1987 and 19 8 8 ,
agencies’ ratings carry sufficient weight in the capital market.
Moody’s issued some unsolicited ratings (in areas where its
In principle, securities with lower credit enhancements can be
standards were stricter than those of Standard and Poor’s) and
discounted by the market. However, in practice, the market
caused yields to rise on these securities. In response, some
has trusted agencies to be prudent in the determination of
issuers changed their M BS structures and hired Moody’s. By
credit support requirem ents and has not required higher
1989, M oody’s share of the M BS business exceeded that of
yields from issuers that have switched to agencies with lower
Standard and Poor’s.
enhancement requirements (Bruskin 1994).
In 1990, Fitch began rating mortgage-backed secu
The evolution o f credit rating standards and the
rities using a model o f required credit enhancement that
Chart 10
Chart 9
R a t in g A g e n c y M a r k e t S h a r e s o f A sse t - b a c k e d
R a t in g A g e n c y M a r k e t S h a r e s o f M o r t g a g e - b a c k e d
S e c u r it ie s Iss u a n c e
S e c u r it ie s Is s u a n c e
Percentage
P ercentage
o f to t a l dollar vo lu m e
o f to tal dollar volum e
l00 ------------------------------
/
/
20 ------------------------------------------- / ------------------------------------------------f
Duff
B,«
/
0 I___ — —-1 —— ■J_____________ I___ I___________I_______ I
1988
91
90
91
92
93
94
Sources: Internal agency data; Asset Sales Report', Federal Reserve Bank
of New York staff estimates.
Sources: Internal agency data; Asset Sales Report; Federal Reserve Bank
of New York staff estimates.
Notes: Market shares for 19 9 4 are based on data through June. The sum o f the
market shares exceeds 100 percent because many issues receive multiple ratings.
Notes: Market shares for 1994 are based on data through April. The sum of the
market shares exceeds 100 percent because many issues receive multiple ratings.
FRBN Y
20
Q u a r t e r l y R e v ie w /S u m m e r - F a ll
1994
based its worst-case scenarios on the Texas recession of the
letter ratings as thresholds for determining capital charges
1980s. This approach resulted in required enhancements
and defining investment prohibitions. Although the agencies
below those of Standard and Poor’s (lower by as much as 50
make no such assurances, the current use of ratings in regula
percent for certain balloon payment m ortgages), whose
tion assumes a stable relationship between ratings and
model extrapolated from the mortgage default experience of
default probabilities. The historical record suggests other
the Great Depression. Duff and Phelps followed suit with a
wise: although ratings usefully order credit risks at any point
framework similar to Fitch’s in 1992. Standard and Poor’s,
in time, specific letter ratings corresponded to higher default
which once had a monopoly, saw its market share slide to 5 5
risks in the 1980s than in the 1970s.
percent in 1993 as many issuers who had at one time
The increasing number of agencies also poses prob
employed only Standard and Poor’s, then later used Standard
lems for the existing structure of ratings-based regulations.
and Poor’s together with Moody’s, had switched to a pairing
Some agencies appear to have different absolute scales, rating
of Fitch and Moody’s.
bonds higher or lower on average than other agencies. How
Most recently, in December 1993, Standard and
ever, even normal variations in opinion across agencies with
Poor’s came out with revised criteria for credit enhancements
the same basic scales confounds the application of existing
that implied a 30 percent reduction on average across a vari
regulations. These problems multiply as the number of agen
ety of mortgage pool types. Explanations for the changes fol
cies and the differences of opinion among them increase.
lowed the next month (Standard and Poor’s 1994). Some of
The impact of multiple rating agencies and ratings
the revisions were in those areas in which the agency had been
differences is apparent in the case studies of junk bond, bank
losing market share, including shorter term mortgages. Rival
debt, and m ortgage-backed securities ratings. For junk
rating agencies claimed that the move represented a competi
bonds, the availability of third opinions enables many bor
tive attem pt to win back market share. In the first four
rowers to climb out of the speculative grade zone into invest
months of 1994, Standard and Poor’s has regained market
ment grade territory. In the area of bank debt ratings, differ
share largely at Moody’s expense. It is difficult to tell at this
ences of opinion are particularly great between agencies of
point whether the shift reflects issuers moving from one
different countries and imply that the designation of more
agency to another or merely a growth in issuance by firms
foreign agencies as NRSRO s will allow more foreign banks to
that use Standard and Poor’s ratings (see Schultz 1994 and
achieve higher ratings. Regarding private-label mortgage-
Inside Mortgage Securities 1994a, 1994b).
backed securities, intensifying competition among the four
Clearly, M BS credit enhancem ent levels have
declined over the history of the market. Analysts and agen
major agencies has been associated with downward revisions
of required enhancement levels.
cies note that this in part reflects a progression along the
The Securities and Exchange Commission (1994a,
learning curve: more information has become available over
1994b) is currently reconsidering its procedures for designat
time about the performance of such securities, reducing the
ing nationally recognized agencies (NRSROs), the role of rat
degree of uncertainty. Skeptics remark that competitive pres
ings in regulations, and the degree of public oversight and
sures can lead to increased pressures to review standards.
mandatory ratings disclosure. Questions for which comments
Whether or not agencies compete on criteria, it does appear
have been solicited include:
that the incentive to innovate in structured finance ratings
tends to favor lower enhancement levels.
• What are the proper objective criteria to consider
when determining N RSRO status?
C o n c l u s io n
• Is it appropriate for NRSROs to charge issuers for
Regulators, like investors, value the cost savings achieved
ratings, and in particular, to vary the charge with
through the use of ratings in the credit evaluation process. As
the size of the transaction?
a result, they have have come to employ a variety of specific
• Would further regulatory oversight of NRSRO s
F R B N Y Q u a r t e r l y R e v ie w /S u m m e r - F a ll
1994
21
be appropriate and what type of oversight would
agencies. O f course, any changes in policy would entail com
that be?
plex tradeoffs; specific proposals and their implications will
• Should issuers be required to disclose activities
surely be explored in future research.
such as rating shopping— soliciting preliminary
The SEC has also invited comment on whether it
indications from numerous rating agencies in
should continue to employ an N RSRO concept. Although
order to identify the agency that will provide the
dropping the designation of N RSRO s would be a radical
highest rating?
measure, it might encourage regulators to revise their current
The SEC’s questions all raise the possibility of addi
use of ratings and to adjust for ratings differences across time
tional oversight or disclosure of NRSRO activity and the rat
and agency. Ratings can and do play an important and valu
ings process. Such measures could conceivably address some
able role in the functioning and oversight of financial mar
of the issues raised in this paper by improving the intertem
kets. But at a m inim um , regulators and investors alike
poral stability of default rates within ratings category and
should be critical users and should regularly review their
reducing differences am ong the officially design ated
application of ratings to the decisions they make.
FRBN Y
22
Q u a r t e r l y R e v ie w /S u m m e r - F a ll
1994
Endnotes
1. Government policy has helped to avert conflicts of interest. The Federal
Reserve Board discouraged a proposed acquisition of Duff and Phelps by
Security Pacific Bank in 1984. The Board ruled that if the merger were to
take place, Duff and Phelps would be prohibited from issuing public rat
ings because Security Pacific would effectively be rating its own borrowers
(Ederington and Yawitz 1987).
2. See the description of the agencies’ ratings methodologies in the
Financial Times 1994, pp. 25-79. Comparisons across the agencies’ rating
scales are more difficult in the lowest part of the range near default, where
the agencies carry different numbers of ratings (Dale and Thomas 1991).
3. For a more critical view, see Stein 1992.
Note 8 continued
time to time as they deem appropriate. Further, when determining ratings,
rating agencies neither use uniform criteria nor weigh the same criteria
equally” (Grafton 1992).
9. The Moody’s study calculates the default rate formally as a weightedaverage cumulative default rate, which is the complement of the product of
weighted-average marginal survival rates. For details concerning rate cal
culations, see the Appendix in Moody’s Investors Service 1994.
10. As reported by Fons (1991), most of the cyclical variation in the aggre
gate default rate on corporate bonds cannot be explained by cyclical varia
tions in Moody’s ratings on bond outstandings. Moreover, since yield
spreads between high- and low-rated bonds tend to rise during recessions,
4. Dale and Thomas (1991) and Baron and Murch (1993) provide compre
hensive discussions of the current use of ratings by regulators in the United
States and abroad. Harold (1938) provides a detailed account of the earliest
uses of ratings in the United States.
market pricing is consistent with a perceived rise in the default probabili
ties of lower rated issues relative to those of higher rated issues during
recessions. Alternatively, the rise in spreads in recessions may merely reflect
a concurrent rise in the market’s aversion to default risk or other supply and
demand factors.
5. Under this system, insurance companies were allowed to request that
specific BB rated bonds be treated the same as those more highly rated
bonds in the top quality category. This practice, which became common
over time, was halted by reforms adopted by the NAIC in 1990.
11. Wigmore (1990) documents a much more severe difference between
the 1986-88 average credit ratios and the 1983-85 ratios than is suggested
by the Standard and Poor’s data presented in Charts 7 and 8 for bonds rated
BB or B. According to Wigmore, the Standard and Poor’s data understate
6. In analyzing the margin rules for mortgage-related securities, Federal
the decline in credit quality because a greater proportion of the junk bonds
Reserve Board staff reasoned thus: “The question of using bond ratings by a
recognized service as a criterion for margin eligibility was discussed when
the initial definition o f ‘OTC margin bond’ was under consideration. The
leveraging events (mergers, acquisitions, and leveraged buyouts); there
fore, their current credit ratios were much weaker than the historical credit
National Association of Securities Dealers proposed a rating standard at
that time and most securities dealers endorsed its use for non-listed bonds
in comment letters, but the Board declined to adopt such a requirement.
issued in the later period were issued by companies in conjunction with
ratios included in the Standard and Poor’s data. In contrast, Fridson (1991)
argues that much of the apparent deterioration in credit ratios and increas
es in default rates for B-rated issues in the late 1980s can be explained by an
Since that time, however, the SEC has used these evaluations of third par
ties as a means of categorizing some debt securities; regulatory examiners
increase in the proportion of issuers rated “B-” as opposed to “B” or “B +
use them to determine investment grade; and the United States Congress
has mandated their use in the statutory definition under consideration.
Staff believes that developments subsequent to the 1978 decision warrant a
departure from the Board’s earlier decision” (Board of Governors 1987).
12. Moody’s and Standard and Poor’s now provide ex post analyses of cor
porate bond defaults by rating categories. Variations in default probabili
ties for Moody’s and Standard and Poor’s can, therefore, be inferred from
7. These rules key off the agencies’ short-term ratings, limiting money
funds from holding more than 5 percent of their assets in paper rated A2 by
13. Standard and Poor’s is generally less willing to base ratings on expect
ed recoveries even though it has always made such distinctions, as have all
Standard and Poor’s (P2 by Moody’s) or more than 1 percent in any paper of
a single A2/P2 issuer. Issuers with these weaker short-term ratings typical
the other agencies, for different classes of debt issued by the same firm.
Whenever a firm defaults on its subordinated debts, its senior debt is
these studies.
ly have long-term bond ratings that are still rated well above the invest
almost always drawn into default as well. Nevertheless, agencies regularly
ment grade cutoff.
award higher ratings to the senior debt because its expected recovery rate is
higher.
8. When voicing its concerns over the 1991 amendments to Rule 2a-7,
the Securities Industry Association noted that “rating categories were not
14. Other authors with other data sets also note a rough equivalence
designed as regulatory tools and NRSROs may change their criteria from
between Moody’s and Standard and Poor’s ratings (Perry 1985, Ederington
N o tes
FRBNY Q
u a r t e r l y R e v ie w /S u m m e r - F a ll
1994
23
E n d n o te s (Continued)
Note 14 continued
Note 17 continued
1986, Ederington and Yawitz 1987). Moreover, Billingsley, Lamy, Marr,
and Thompson (1985) show that the market views Moody’s and Standard
and Poor’s ratings as equivalent because the yields on bond issues with split
ratings do not depend on which agency assigned the higher rating.
banks were also put on CreditWatch.
15. The Pearson product-moment correlation coefficient, which can range
from -1.00 to a maximum value of 1.00, measures the extent to which rank
orderings agree while removing any confounding effects of differences in
average rating scores and differences in units of measurement.
18. The ratings of the French rating agency S&P-ADEF, a joint venture
founded in 1990 by Standard and Poor’s and Agence d e v alu ation
Financiere, are counted as Standard and Poor’s ratings for the purposes of
calculating global market share.
19- The one consistent exception is IBCA, which shows more agreement
with Moody’s on these measures for banks than does the wider sample. This
finding may reflect IBCA’s initial specialization in the rating of financial
16. These agencies acknowledge that their ratings are higher than
Moody’s and Standard and Poor’s on average; however, they attribute some
of the ratings difference to sample selection bias. They argue that ratings
from Fitch or Duff and Phelps are only sought when there is a strong expec
tation of improving upon Moody’s and Standard and Poor’s ratings. When
Fitch or Duff and Phelps might, in fact, rate lower, their ratings are not
institutions and the limitation of its NRSRO designation to that area.
20. The mean of the Pearson product-moment correlation for ratings of
agencies from the same country is 0.858, compared with a mean of 0.775
for the correlation coefficients for the ratings of agencies from different
countries. The standard errors of measurement for the two coefficients are
purchased.
0.018 and 0.054, respectively.
17. For example, U.S. issuers of commercial paper and long-term securi
21. In this article, we follow industry practice in using “asset-backed secu
rities” (ABSs) in the more narrow sense that excludes mortgage-backed
ties often obtain bank letters of credit in order to achieve targeted credit
ratings, but the attractiveness of such backing depends greatly on the cred
it rating of the bank issuing the letter of credit. When Standard and Poor’s
put three Japanese banks on its CreditWatch list (with negative implica
securities (MBSs).
tions) in March 1994, the bond issues of 144 U.S. bond issuers and 46 U.S.
commercial paper issues that were backed by letters of credit from these
ties (1994a, 1994b). This section’s discussion of the evolution of ratings cri
teria for MBSs draws heavily from these sources.
22. See Bruskin (1988, 1994), Schultz (1994), and Inside Mortgage Securi
R eferences
Altman, Edward I. 1989. “Measuring Corporate Bond Mortality and Per
formance.” J o u r n a l OF F in a n c e (September): 909-22.
Baron, Neil, and Leah Murch. 1993- “Statutory and Regulatory Uses of Rat
ings in the United States and Other Jurisdictions.” Fitch Investors Ser
vices, January 14.
Ang,J., andK. Patel. 1975. “Bond Rating Methods: Comparison and Vali
dation.” J o u r n a l
of
F in a n c e
(May): 631-40.
Beattie, Vivien, and Susan Searle. 1992a. “Bond Ratings and Inter-Rater
Agreem ent.” J
Artus, Patrick, Jean Garrigues, and Mohamed Sassenou. 1993- “Interest Rate
Costs and Issuer Ratings: The Case of French CP and Bonds.” J o u r n a l
of
I n t e r n a t io n a l S e c u r it ie s M a r k e t s
24
FRBNY Q
(S u m m er):
o u rn a l of
I n t e r n a t io n a l S e c u r it ie s M a r k e t s
167-72.
(Autumn): 211-18.
u a r t e r l y R e v ie w /S u m m e r - F a ll
1994
N
otes
R eferen ces
{Continued)
_____ . 1992b. “Credit-Rating Agencies: The Relationship between Rater
Federal Financial Institutions Examination Council. 1994. “Risk Based Capi
In t e r n a
tal Requirements— Recourse and Direct Credit Substitutes; Proposed
Rule.” F e d e r a l R e g is t e r , vol. 59, no. 100, pp. 27116-41.
Billingsley, Randall, Robert Lamy, M. Wayne Man, and G. Rodney Thompson.
Financial Times. 1994. F in a n c ia l T im es C r e d it R a t in g s I n t e r n a t io n a l
Agreement and Issuer/Rater Characteristics.” J o u r n a l
t io n a l
S e c u r it ie s M a r k e t s
of
(Winter): 371-5.
1985. “Split Ratings and Bond Reoffering Yields.” F in a n c ia l M a n a g e
m ent
(First Quarter).
(Spring): 59-65.
First Boston. 1990-94. H ig h - Y ie l d H a n d b o o k , annual issues.
Board of Governors of the Federal Reserve System. 1987. “Marginability of
Mortgage-Related Securities.” Office Correspondence from Division of
Banking Supervision and Regulation to the Board of Governors,
Fons, Jerome S. 1991. “An Approach to Forecasting Default Rates.”
M o o d y ’s S p e c ia l R e p o r t .
April 15.
Brand, Leo, Thomas C. Kitto, and Reza Bahar. 1994. “ 1993 Corporate
Fridson, MartinS. 1991. “Are Bond Ratings Consistent Over Time?” J u n k
B o n d R e p o r t e r , February 25.
Default, Rating Transition Study Results.” STANDARD AND P o o r ’s
_____ . 1994. “The State of the High Yield Bond Market.” J o u r n a l
C r e d it W e e k I n t e r n a t io n a l , June 6.
A p p l ie d C o r p o r a t e F in a n c e
Bruskin, Eric. 1988. “The Role of the Rating Agencies.” CONVENTIONAL
P a s s - T h r o u g h Q u a r t e r l y . Mortgage Securities Research, Goldman
of
(Spring):85-97.
Grafton, K. Susan. 1992. “The Role of Ratings in the Federal Securities
Laws.” I n s ig h t s (August): 22-27.
Sachs, July.
_____ . 1994. “The Rating Game: You Pays Your Money and You Take
Harold, Gilbert. 1938. B o n d R a t in g s
as a n
I n v e s t m e n t G u id e .
Y o u r C h o ic e .” M o r t g a g e M a r k e t C o m m e n t , M o r t g a g e S e c u r itie s
R esearch , G o ld m a n Sach s, Ja n u a r y 7.
I n s id e M o r t g a g e S e c u r it i e s .
1994a. “ In M B S R a t in g S e rv ic e B a t t le ,
H isto r ic a l L ead er S & P Q u ie tly D ro p s in to T h ird P lace d u r in g
Cantor, Richard, and R. Demsetz. 1993- “Securitization, Loan Sales, and the
Credit Slowdown.” F e d e r a l R e ser v e B a n k
R e v ie w (Summer): 27-38.
of
1993.”
M arch 18.
N ew Y o r k Q u a r t e r l y
_____ 1994b. “Four-Way Battle for Private-Label Rating Business Heats
Up As Moody’s Loses Market Share.” June 17.
Carey, Mark, Stephen Prowse, John Rea, and Gregory Udell. 1993. FEDERAL
R e ser v e B u l l e t in
(February): 77-92.
Lore, Kenneth. 1991. M o r t g a g e - B a c k e d S e c u r it i e s , 1990-91 Edition.
New York: Clark, Boardman Company.
Crabbe, Leland, and Mitchell Post. 1992. “The Effect of SEC Amendments to
Rule 2a-7 on the Commercial Paper Market.” Board of Governors of the
Federal Reserve System Working Paper no. 199-
1970-1993. ” January.
Dale, RichardS., and Stephen H. Thomas. 1991. “T h e R e g u la to r y U s e o f
C r e d it R a t in g s in In te rn a tio n al F in a n c ia l M a r k e ts.” J o u r n a l o f I n t e r
n a t io n a l
S e c u r it ie s M a r k e t s (S p rin g ):
Moody’s Investors Service. 1994. “Corporate Bond Defaults and Default Rates:
Monro-Davis, Robin. 1994. “Unsolicited Ratings Are for Investors.” T h e
T r e a s u r e r (February): 30-33-
9-18.
National Association of Insurance Commissioners, Securities Valuation Office.
Ederington, Louis. 1986. “Why Split Ratings Occur.” F in a n c ia l M a n a g e
m ent
1994. V a l u a t io n
of
S e c u r it ie s M a n u a l ,
vols. 1-2.
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O’Neill, Leo C. 1993. Speech before the IOSCO Annual Conference, Mexico
Ederington, Louis, and Jess Yawitz. 1987. “The Bond Rating Process.” In
Edward Altman, ed., H a n d b o o k
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N o tes
of
F in a n c ia l M a r k e t s .
City, October 24-26.
New York:
Perry, Larry G. 1985. “The Effect of Bond Rating Agencies on Bond Rat
ing Models.” J o u r n a l
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25
R efe re n c e s
(Continued)
Furcell, John, Ernest Brown, Joyce Chang, and Dirk Damrau. 1 9 9 3 . “ F erm en t
o v e r D e v e lo p in g C o u n tr y R a t in g s : T h e C a se o f M e x ic o .” E m e r g i n g
Standard and Poor’s. 1994. “Improving Outlook Spurs MBS Revisions.”
S t a n d a r d a n d P o o r ’s C r e d it w e e k , January 10.
M a r k e t s R e s e a r c h , S a lo m o n B ro th e rs, F eb ru ary 2.
Stein, Benjamin. 1992. A L i c e n s e
Schultz, Abby. 1994. “S&P Faces Criticism in Mortgage Area.” W a l l
S t r e e t J o u r n a l , January 4.
Securities and Exchange Commission. 1994a. “Nationally Recognized Statisti
cal Rating Organizations.” Release Nos. 33*7085, August 31.
to
S t e a l : T he U n t o ld St o r y of
M ic h a e l M i l k e n a n d t h e C o n s p i r a c y t o B i l k t h e N a t i o n . N e w
Y ork: S im o n an d Sch uster.
West, Richard R. 1973. “Bond Ratings, Bond Yields, and Financial Reg
ulation: Some Findings.” J o u r n a l
159-68.
of
L a w a n d E c o n o m ic s
(April):
Securities and Exchange Commission. 1994b. “Disclosure of Security Ratings.”
Release No. 33-7086, August 31.
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Wigmore, Barrie. 1990. “The Decline in Credit Quality of New-Issue Junk
Bonds.” F in a n c ia l A n a l y s t s J o u r n a l (September-October): 53-62.
1994
N
otes
The Price Risk of Options Positions:
Measurement and Capital
Requirements
Arturo Estrella, Darryll Hendricks, John Kambhu,
SooShin, and Stefan Walter
G
lobal m arkets for option products, both
of the different methods in providing capital coverage for
exchange-traded and over-the-counter, have
potential losses on a series of option portfolios.
expanded rapidly in recent years. The Bank
We find that the simple strategy methods provide
for International Settlements (1994) reports
only a rough measure of potential losses. Moreover, for mar
that outstanding options now exist on notional principal
ket participants with large option positions, the simple strat
amounts totaling at least $3-3 trillion. In the last four years,
egy approach could lead to an excessive reporting burden.
the outstanding interest rate, commodity, and equity-related
The value-at-risk methods, which are based on option pric
options of U.S. commercial banks have grown more than 40
ing models, tend to provide better estimates of the market
percent annually and the banks’ foreign exchange options
risk inherent in a position. The accuracy of the value-at-risk
more than 16 percent per year.
approach is also found to be significantly enhanced by adjust
The expansion of options markets underscores the
ments for gamma risk, the risk that an options price changes
need for supervisors to develop sound methods of monitoring
in a nonlinear fashion as a result of large movements in the
the risks associated with these markets. This article assesses
price of the underlying instrument.1
different supervisory approaches to the measurement and
capital treatment of the market risk of options— the risk that
Background
an d
M
eth odology
an options contract will decline in value with changes in mar
T he U n iq u e R i s k s
ket prices or rates. The methods for measuring the market
Like most other instruments, options contracts entail both
risk of options positions examined in the article fall into two
price (or market) risk and credit risk. Market risk arises when
broad categories: simple strategy methods and value-at-risk
the value of the interm ediary’s portfolio is sensitive to
(or price sensitivity) methods. We compare the performance
changes in market prices or rates. On some occasions, inter
of
O p t io n s
F R B N Y Q u a r t e r l y R e v ie w /S u m m e r - F a ll
1994
27
mediaries will attempt to eliminate such risk by engaging in
the charge. The most efficient charges would, for example,
offsetting transactions; that is, they attempt to “hedge” the
require substantial data about the composition of the options
market risk away. On other occasions, however, intermedi
portfolio and the risk factors affecting the portfolio’s value, as
aries may attempt to earn a risk premium for bearing the
well as estimates of the sensitivities of the portfolio’s value to
market risk. Credit risk arises because a financial asset, such
movements in the risk factors. To process such information in
as a purchased option or a business loan, could become worth
a timely fashion, an institution must be willing to commit
less if the counterparty to the asset does not make good on its
significant resources.
obligations. This article focuses on market risk.
The complexity of the capital calculation itself is
The form that market risk takes in options markets
also an important consideration. Complex supervisory charges
can be quite different from its form in other markets. This is
may be difficult to implement uniformly. Moreover, the more
true in part because the values of options contracts can change
specific the rule, the greater the opportunities for finding
extremely rapidly— often far more rapidly as a percentage of
exceptions or exclusions that were not intended. Neverthe
their value than do the assets that underlie options contracts.
less, complex calculations could lead to more accurate and
In addition, the price sensitivity and volatility of a position
efficient charges, thereby lessening the regulatory burden on
can themselves change quickly, further complicating the risk
the options market.
management of options positions. An intermediary must
A final consideration that is particularly important in
constantly track the changes in the volatility of its portfolio
setting supervisory capital for options is the use of option pric
that result from market movements. This task can be particu
ing models in the calculation. The development of these mod
larly difficult in periods of great market stress and lowered
els has been critical to the growth of the options market, and
liquidity, such as that experienced in the market for European
currency options in September 1992.
Alert to these difficulties, supervisors must consider
carefully how supervisory capital can best reduce the detri
mental impact of options risks in the financial markets.
There is a definite trade-off between the efficiency
o f the capital charge and the resources required
to compute the charge.
C o n s id e r a t io n s
in
S e t t in g S u p e r v is o r y C a p it a l
R e q u ir e m e n t s
Determining appropriate supervisory capital standards for
options positions involves several choices. A sufficient level of
their use in the market is pervasive. However, the markets do
prudence could probably be achieved by simply setting very
not always conform to the assumptions of the models. In par
high standards without regard to how the risks change in
ticular, options pricing models typically assume continuous
response to changing market conditions. This approach
price changes and liquid markets. The risk of systemic prob
could, however, require far more capital than is actually
lems, however, is very likely to go hand-in-hand with a loss of
needed. The costs of this excessive safety would then translate
market liquidity and discontinuous price movements. There
into a slowdown in potentially beneficial options trading or
fore, in setting supervisory capital requirements, regulators
perhaps a relocation of this trading to jurisdictions not
may not wish to rely solely on pricing models.
imposing such onerous standards.
More accurate measures of the risks of an options
C urrent
an d
P r o p o s e d S u p e r v is o r y A
ppro ach es
portfolio require more information about the composition of
At the international level, there are a number of different
the portfolio and more calculations. As the analysis below
existing and proposed supervisory capital treatments for the
makes clear, there is a definite trade-off between the efficiency
market risk of options. The European Community’s Capital
of the capital charge and the resources required to compute
Adequacy Directive (CAD), which takes effect in January
FRBNY Q
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1994
1996, includes a simple capital requirement for options that
C a p it a l R u l e s
for
O p t io n s
applies to all commercial banks and securities firms licensed
Capital rules for the price risk of options fall into two cate
in the Community. The Basle Committee on Banking Super
gories: value-at-risk (or price sensitivity) rules and strategy-
vision’s April 1993 market risk proposal (BIS proposal)
based rules. The value-at-risk approach uses option pricing
includes capital requirements for options similar to those of
models to estimate a portfolio’s potential losses. The strategy-
the CAD. Unlike the CAD, however, the BIS proposal also
based rules, by contrast, apply various formulas to the market
considers allowing banks to apply a more sophisticated sce
price of an option and its underlying asset.
nario-based methodology to calculate their capital require
ment for options positions.
While strategy-based rules estimate potential losses
very roughly, the option pricing models of the value-at-risk
The rules of both the United Kingdom’s Securities
approach in principle provide a much more accurate measure
and Futures Authority (SFA) and the U.S. Securities and
of potential changes in the value of options. Strategy-based
Exchange Commission (SEC) already include capital require
rules have the additional drawback of requiring a complex
ments for the market risk of options. The SFA’s requirements
parsing of a portfolio to rearrange its components into the
range from simple rules for small options players to a sce
particular set of strategies recognized for capital purposes.
nario-based approach for more sophisticated institutions.
The value-at-risk approach uses a simple aggrega
The SEC ’s capital requirements are based on a series of
tion of all positions relating to a given underlying asset (for
options trading strategies that are commonly employed by
example, a particular equity or exchange rate). This aggrega
financial institutions.
tion of positions of the value-at-risk approach more reliably
accounts for offsetting within a portfolio than does the strate
M
eth odology of
E v a l u a t io n
gy-based approach, which recognizes offsetting in only a
Conceptually, measuring the market risk of options for capi
piecemeal fashion— and only to the extent that positions fit
tal purposes consists of two basic steps. The first entails mak
into the trading strategies recognized by supervisors. Note,
ing assumptions about the potential movement of risk factors
however, that this conclusion applies only to aggregation
that could affect the value of an options portfolio over a
across instruments sensitive to a given underlying asset. The
defined holding period and at a certain level of confidence.
appropriate approach to aggregation of positions across mul
This step may also account for correlations among the differ
tiple underlyings is a separate problem.
ent risk factors. The second step consists of measuring the
sensitivity of options positions to the assumed movements in
V a l u e - at- R is k A
the underlying risk factors to arrive at an estimate of the port
A portfolio’s value at risk is a measure of its potential losses,
folio’s potential gain or loss. Each step can be carried out with
where the losses are expressed in terms of some confidence
various degrees o f sophistication. This article focuses
level (for example, a loss of such magnitude that it is likely to
primarily on the second step, examining the performance of a
occur in only one month out of a hundred). This risk mea
number of capital rules in approximating potential portfolio
surement approach lends itself quite readily to the construc
losses resulting from given movements in the underlying risk
tion of a capital requirement. Specifically, the potential losses
factors.
a portfolio might suffer are estimated and then used to deter
The following section describes various methods of
setting regulatory capital and the rationale that underlies
ppro ach es
mine an amount of capital sufficient to cover these losses with
the desired level of confidence.
each. Although in several cases the methods overlap with
those of specific regulatory entities, our intent is not to assess
S c e n a r io - b a s e d a n d S im u l a t io n M e t h o d s w it h F u ll
the particular rules of different regulatory bodies, but to
R e v a lu a t io n
evaluate the generic approaches that might be taken towards
The most precise method for estimating value at risk entails
regulatory capital.2
calculating a portfolio’s gains and losses by using option pric
FRBNY Q
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29
ing models to explicitly revalue the portfolio over a set of pos
the principal approach of the European Com m unity’s CA D ,
tulated price changes. The resulting capital charge is simply
is based only on the option’s delta value, while other rules use
the largest loss over the set of postulated price changes, mea
both the delta and gam m a values. Chart 1 illustrates the
sured at a certain level of confidence.
results of using first- and second-order approximations in the
The postulated price changes can be obtained using
case of a written call option.
either a scenario approach or a simulation method. The sce
N ote that the second-order approxim ation is not
nario approach revalues the portfolio at several distinct values
necessarily more accurate than the first-order approximation,
of the underlying asset within a given interval— for example,
particularly if the changes in the underlying value are large.
within the interval defined by the current underlying price
Thus, for applications that rely on accurate measures of port
plus or minus three standard deviations of monthly moves.
folio changes resulting from large market movements (for
Alternatively, changes in the price of the underlying asset
example, “stress testing”), models involving approximations
may be sim ulated, using either historical price changes or
should be used with caution.
Monte Carlo methods. In either type of simulation, the entire
An advantage of the price sensitivity approach is its
portfolio is revalued at each point generated by the simula
simplicity. It requires only the most basic options-related
tion. Either the largest loss or some conservative percentile of
data used by standard risk management systems: the stan
the losses, depending on the desired degree of confidence, can
dard deviation (volatility) of the underlying asset, the portfo
then be selec te d as the valu e at risk . T h e sim u la tio n
lio’s delta value, and the portfolio’s gam m a value. Addition
approaches allow for sam pling o f portfolio value changes over
ally, a convenient feature o f deltas and gam m as is their
a more continuous range of price changes in the underlying
additivity across instruments written on the same underlying
asset than does the scenario approach, which focuses on a
asset, allowing offsetting exposures within a portfolio to be
more limited number of specific price movements.
properly netted and reflected in the capital charge.
The scenario approach is included in the SFA capital
rules as a preferred alternative. It is also similar to the SPAN
system of margin requirements used by a number of deriva
tives exchanges.
Chart 1
M e t h o d s B a s e d o n P r ic e S e n s it iv it ie s — F ir s t - a n d
W r it t e n C a l l O p t io n
F ir s t - a n d S e c o n d -O r d e r A p p r o x im a t io n s o f a
S e c o n d - O r d e r A p p r o x im a t io n s
O
p t io n v a l u e
Another class o f value-at-risk rules relies on a simple approxi
Initial underlying value = strike price = 100
Volatility = 15 percent
Interest rate = 7 percent
mation of an option’s price sensitivity to changes in the price
of the underlying asset (see Appendix I). All of these rules use
various combinations o f an option’s basic price sensitivity
measures— the option’s delta and gam m a values. An option’s
delta value is the change in the price of an option resulting
from a small change in the price of the underlying asset. An
option’s gam m a value measures the change in delta with
respect to movements in the price of the underlying asset.
The gam m a value can be used not only to improve upon the
approximation obtained from the delta value but also to eval
uate the quality of hedges— a delta-hedged options position
with a large negative gam m a is vulnerable to large changes in
the price of the underlying asset. The delta-equivalent rule,
Digitized
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-150 I
I I 1 I I I____I____I____I____I____I____1____I____I____I____1____I
20 30 40 50 60 70 80 90 100 110 120 130 140 150 160 170 180
U n d e r ly in g v a lu e
Nevertheless, price sensitivity approximations, even
applies to securities firms holding options for proprietary
those that incorporate gamma values, may underestimate
trading, and Paragraph (c)(2)(x), which applies to market-
potential losses because the price sensitivity at current prices
making firms. Both rules apply a lower capital charge for cer
may not be representative of an option’s behavior at other
tain offsetting options strategies, but Paragraph (c)(2)(x) rec
prices. Option prices do not move in a linear fashion. Some
ognizes more offsetting strategies than does Appendix A.3
options portfolios can have a very small gamma at the current
The SEC has released for public comment (Federal
price of the underlying asset but possess a much more nega
Register 1994) a proposal that would permit broker-dealers
tive gamma at different prices (for example, a written out-of-
to calculate their capital requirements for listed options
the money put). In this case, price sensitivity approaches can
using a scenario-based approach similar to the one described
underestimate the fall in the portfolio’s value resulting from a
earlier in this section.4 According to the SEC’s proposal,
large decline in the price of the underlying asset.
“haircuts for options and related positions, when computed
Both the scenario and simulation approaches can
using this model, would more accurately reflect the risk
also be combined with price sensitivity approximations. In
inherent in broker-dealers’ option positions.” SEC require
this case, the portfolio is not explicitly revalued at each simu
ments for over-the-counter options would continue to be cal
lated price change, but instead the changes in portfolio value
culated using the strategy-based rules outlined in this paper.
are approximated for each simulated price change. Although
The strategy-based capital rules do not closely paral
the approximations are based on option pricing models, their
lel most firms’ risk control and/or trading systems because
use will inevitably lead to a loss of accuracy relative to the
the capital charges may not reflect portfolio-wide risks. For
explicit use of the models themselves.
instance, the risk of a delta-hedged short call strategy is equal
to the risk of a delta-hedged covered call strategy with the
I n c o r p o r a t io n o f V o l a t il it y R is k
same set of parameters. However, the capital charges could be
The discussion to this point has addressed only potential
different depending on the strategy chosen to compute them.
losses resulting from changes in the price of the underlying
asset. Unlike other instruments, however, options are also
Q u a n t it a t iv e A n a l y s is
of
P rice R is k R ules
exposed to changes in price volatility. A capital adjustment
This section assesses the performance of the two classes of
for volatility risk can be incorporated in the price sensitivity
rules discussed in the previous section. Under the value-at-
approximation approach and the simulation or scenario-
risk approach, we consider three different methods for con
based methods.
structing a capital charge: (1) the delta-equivalent rule,
which bases the capital charge on the delta-equivalent
S t r a t e g y - b a s e d R u les
amount (that is, delta multiplied by the value of the underly
The capital requirement under strategy-based rules is derived
ing position); (2) the Taylor series rule, which supplements
from a series of defined options trading strategies commonly
the delta-equivalent rule with an adjustment for gamma
employed by financial institutions. The strategy-based
(positive or negative); and (3) the gamma rule, which supple
approach may recognize offsetting for certain types of trades,
ments the delta-equivalent rule with an adjustment for nega
but in general, it does not easily accommodate the netting of
tive gamma. Under the strategy-based approach, we consider
opposite positions. Since strategy-based rules are collections
the SEC’s Appendix A rule and C2X rule.
of formulas that apply to various specific positions, it is
We evaluate the accuracy with which these rules
impossible to define a generic form for these rules. Thus, to
measure the price risk of a variety of options positions and the
test this type of rule, it is convenient to use its implementa
degree to which they provide adequate capital levels for the
tion by a particular regulatory authority, the SEC.
portfolios’ potential losses. Broadly, the analysis performed in
The SEC’s Net Capital Rule (15(c)3-l) for options
this exercise reveals that the approximate value-at-risk rules
contains two strategy-based rules: Appendix A, which
tend to estimate portfolio risk more accurately and thus pro
F R B N Y Q u a r t e r l y R e v ie w /S u m m e r - F a ll
1994
31
duce more efficient levels of capital than the simple strategy-
short position, where gamma is negative.
based rules. Within the value-at-risk category, the gamma
Each sample set contains thirty-five portfolios con
and Taylor series rules provide a more accurate measure of
structed from different combinations of common options
potential losses than does the delta-equivalent rule, high
positions. Among the thirty-five portfolios are several that
lighting the importance of an adjustment for gamma risk.
correspond to strategies recognized directly by the SEC rules.
Other portfolios are then added by building on the SEC
M
strategies. Portfolios include naked positions, simple strate
eth odology
The riskiness of an options portfolio is measured as the maxi
gies, and various combinations of SEC-recognized strategies.
mum potential loss that would occur over a range of changes
Delta-hedged portfolios are also included to generate results
in the underlying asset price. Using a scenario-based method
that more closely parallel gains and losses from realistic trad
ology, we calculate gains and losses by revaluing each portfo
ing practices. The composition of each portfolio and the para
lio over a set of postulated price and volatility changes to find
meters used to compute options prices and risks are listed in
the largest loss (price and volatility assumptions are listed in
Table 1.6 Portfolio sizes are normalized to ensure that differ
Table 1). Specifically, the underlying price is varied within a
ences in potential losses across portfolios result from the port
folios’ inherent riskiness rather than their size.7
Within the value-at-risk category, the gamma
and Taylor series rules provide a more accurate
measure o f potential losses than does the deltaequivalent rule, highlighting the importance o f
C o m p a ris o n o f C a p i t a l R u le s
E f f ic ie n c y o f C a pita l R u l es
To evaluate the efficiency of individual rules, we perform a
linear regression of the capital charge produced by a given
rule on the largest loss as measured by the scenario approach
discussed in the previous section. There are thus thirty-five
an adjustment fo r gamma risk.
data points in each regression, corresponding to the thirtyfive portfolios considered. The R 2 coefficient, which is one
range of ± 3 standard deviations of one-month price changes
measure of correlation between two variables, reflects the
in discrete increments of 5 percent of the initial price. The
strength of the linear relationship between portfolio losses
volatility of the underlying price is varied within a range of
and capital requirements. Rules with higher R 2 coefficients
± 5 percentage points of the initial volatility in increments of
tend to assign capital levels that are more closely correlated to
one percentage point.5 The parameters used in this analysis
potential losses. R 2 coefficients for the rules examined are
provide a consistent benchmark for comparing the different
summarized in Table 2.
capital rules. Although the parameters are intended to be
The Taylor series and gamma charge rules display a
realistic, they are not intended to represent a prescribed
stronger relationship between capital charges and losses than
absolute level of confidence.
does the delta-equivalent rule. The reason is that the capital
We measure potential losses for a set of options port
charge of the delta-equivalent rule is based only on a portfo
folios with 30 days to maturity and for otherwise equivalent
lio’s delta value at a given point in time and therefore does not
portfolios with 180 days to maturity. Analyzing the effect of
capture the nonlinearity of an option’s price changes. In con
an option’s time to maturity on the accuracy of a rule is
trast, both the Taylor series and gamma charge rules approxi
important because of its influence on an option’s time value
mate the option’s nonlinear price behavior by reflecting the
and gamma. Gamma is substantially larger for options near
gamma values in the capital computation.
ing expiration— especially around the money— than for
Overall, both strategy-based rules— Appendix A
options with longer time to maturity. The effect of gamma
and C2X — exhibit significantly lower R 2 coefficients than
risk is generally greatest for portfolios consisting of a net
the value-at-risk rules, suggesting that capital charges de-
Digitized
32 for FRASER
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1994
Table 1
O p t io n s P o r t f o l io s
*
*
1
2
*
3
4
Portfolio
Position
Strike
Price
Short call-in the money
Short 1 call
90
Short call-o u t o f the money
Short call—at the money
Short 1 call
Short 1 call
110
100
Delta-hedged/short call-in the money
Portfolio #1, delta-hedged
5
Delta-hedged/short call-ou t o f the money
Portfolio #2, delta-hedged
6
Delta-hedged/short call—at the money
Portfolio #3, delta-hedged
*
7
Covered short call-in the money
Long 1 underlying
Short 1 call
90
*
8
Covered short call-out o f the money
Long 1 underlying
Short 1 call
110
*
9
Covered short call-at the money
Long 1 underlying
Short 1 call
10
Synthetic long futures w ith split strike
Strikes o f put and call are different.
Long 1 call
Short 1 put
*
11
Bull call spread
Strike o f short is higher than
strike o f long.
Long 1 call
Short 1 call
12
Delta-hedged/bull call spread
Portfolio # 11, delta-hedged
*
13
Bear call spread
Strike o f short is lower than
strike o f long.
Long 1 call
Short 1 call
100
110
90
95
115
115
95
14
Delta-hedged/bear call spread
Portfolio # 13, delta-hedged
*
15
Bear call spread/symmetric to # 15
Sym m etrically in the money and
out o f the money, as in #15
Long 1 call
Short 1 call
16
Delta-hedged/bear call/symmetric
Portfolio # 15, delta-hedged
*
17
Short straddle
Short 1 call
18
Delta-hedged/short straddle
Portfolio # 17, delta-hedged
*
19
Protected call-in the money
(synthetic put)
Short 1 Underlying
Long 1 call
90
*
20
Protected call-ou t o f the money
(synthetic put)
Short 1 Underlying
Long 1 call
110
*
21
Protected call—at the money
(synthetic put)
Short 1 Underlying
Long 1 call
100
22
Delta-hedged/protected call-in the money
Portfolio # 19, delta-hedged
23
24
Delta-hedged/protected call-o u t o f the money
Portfolio #20, delta-hedged
Delta-hedged/protected call—at the money
Portfolio # 21, delta-hedged
105
85
100
110
*
25
Short put—in the money
Short 1 put
*
26
Short p u t-ou t o f the money
Short 1 put
90
*
27
Short put—at the money
Short 1 put
*
28
Long put—in the money
Long 1 put
100
110
*
29
Long p u t-o u t o f the money
Long 1 put
90
*
30
Long p u t-at the money
Long 1 put
31
Ratio call spread
2:1 ratio
Long a call with a lower strike and
short 2 otherwise identical calls w ith a higher strike
Long 1 call
Short 2 calls
100
100
110
32
Delta-hedged/ ratio call
Portfolio #31 delta-hedged
33
Ratio call backspread
2:1 ratio
Short a call w ith a lower strike and
long 2 otherwise identical calls with a higher strike
Long 2 calls
Short 1 call
34
Delta-hedged/ratio call backspread
V ertical box
Combination o f a bull spread and a bear spread
Long call at higher strike and short call at lower strike
Long put at higher strike and short put at lower strike
35
100
90
Portfolio #33 delta-hedged
Long 1 call
Short 1 call
Long 1 put
Short 1 put
115
95
115
95
Note: The parameters used in the portfolio simulation program are as follows:
U nderlying price = 10 0
Annual dividend rate = 0 percent
Annual volatility = 3 0 percent
Interest rate = 3.5 percent
Time to expiration = 1 8 0 days (set 1)
3 0 days (set 2 )
*Option strategies that are officially recognized under the SEC’s Appendix A and C 2X capital rules.
F R B N Y Q u a r t e r l y R e v ie w /S u m m e r - F a ll
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33
rived under the simple strategy-based approach are not closely
Appendix A slope coefficient is significantly above one for the
correlated with the potential losses of options portfolios. The
30-day options, and below one (although not significantly so)
low R 2 could be attributed to the fact that strategy-based
for 180-day options. The C 2 X coefficients are significantly
rules provide only a rough measure of the portfolios’ risk,
lower than those of the other rules and are closer to zero than
largely because they do not account for internal risk manage
to one.
ment practices or changing market conditions.
The capital coverage of the various rules is captured
One notable exception to this overall finding occurs
graphically in Charts 2 through 6. The “45 degree” lines in
when options are nearer to maturity (30-day series). In this
the charts depict capital-to-loss ratios o f 1:1. The points
case the correlation between capital charges and potential
above the 45 degree line in charts 2 through 6 represent port
losses is stronger under Appendix A than under the delta-
folios for which the capital requirements exceed portfolio
equivalent rule. The consistently high capital charge of the
losses. The points falling below the 45 degree line represent
Appendix A rule appears to mesh well with the high gam m a
portfolios for which the capital requirements are insufficient
risk often associated with short-dated options.8 In contrast,
to cover portfolio losses. From the charts, it is clear that the
the delta-equivalent rule performs less efficiently in this case
gam m a and Taylor measures produce the patterns most sim i
because it does not capture gam m a risk.
lar to the 45 degree line itself, while the patterns for strategybased rules are the least similar.
Another approach to the evaluation of the methods
C o v e r a g e o f C a p it a l R u le s
C apital rules should provide not only a high correlation
is to exam ine the “errors” produced by each m ethod. In
between capital requirements and losses but also adequate
Charts 2 through 6, capital deficits and surpluses can be mea
coverage of portfolio losses. One way to evaluate coverage is
sured by the vertical distance, expressed in absolute dollar
to compare the slope coefficients of regression lines produced
amounts, of a portfolio from the 45 degree line. To compare
by each rule. A slope coefficient gives the marginal amount of
the aggregate m agnitude of the capital shortages and excesses
capital that corresponds to a $ 1 difference in the risk exposure
resulting from each rule, we summed the portfolio deficits
of a portfolio. For example, a slope coefficient of 1 indicates
and surpluses separately (Table 2).
that an incremental loss of $1 is associated with $1 more of
From a supervisory perspective, the gam m a charge
capital. The slope coefficients are also summarized in Table 2.
rule appears slightly more attractive than the Taylor series
The differences between slope coefficients for the
rule. The total deficit is higher under the Taylor series rule
Taylor series and gam m a charge rules are slight. In contrast,
than under the gam m a charge rule. As Appendix I explains in
the delta-equivalent rule produces m aterially lower slope
greater detail, the Taylor series rule gives capital credit when
coefficients than do the gam m a and Taylor series rules. The
ever gam m a is positive, while the gam m a rule does not pro-
Table 2
C om pa rison of V alue - a t -R isk a n d Stra teg y -B ased R ules
Statistic
30 -D ay O ptions
R 2 coefficient
Slope coefficient
Total capital deficit
Total capital surplus
180-D ay O ption s
R 2 coefficient
Slope coefficient
Total capital deficit
Total capital surplus
Taylor
Gamma
Delta
Appendix A
C 2X
0.842
0.96*
188
173
0.8 28
0 .9 1*
158
274
0.381
0.52
497
204
0.555
1.54
131
1176
0 .0 26
0.1 9
634
580
0 .9 74
1.02*
60
16
0.927
1.02*
33
74
0.667
0.6 9
187
62
0.1 12
0.6 7*
112
695
0.0 10
0.12
253
325
*The hypothesis that the slope coefficient equals 1 cannot be rejected at the 5 percent level.
34
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Chart 2
T a y l o r S e r ie s R u l e
C a p it a l
C a p it a l
ch arge
La r g e s t
ch arge
L
lo ss
a r g e s t lo ss
Note: To maintain comparability of scale across charts, the coordinate pair (161, 205) is not shown in the left panel.
Chart 3
G a m m a C h a r g e R ule
C a p it a l
C a p it a l
ch arge
ch arg e
J
200
La r g e st
La r g e s t
lo ss
lo ss
Note: To maintain comparability of scale across charts, the coordinate pair (16 1, 205) is not shown in the left panel.
F R B N Y Q u a r t e r l y R e v ie w /S u m m e r - F a ll
1994
35
Chart 4
D e l t a Eq u iv a l e n t R ule
C a p it a l
ch arge
C a p it a l
La r g e s t
ch arge
lo ss
La r g e s t
loss
Chart 5
SEC
A p p e n d ix A R u le
C a p it a l
C a p it a l
ch arge
La r g e s t
La r g e s t
lo ss
Note: To maintain comparability of scale across charts, the following coordinate
the right panel.
36
FRBN Y
Q u a r t e r l y R e v ie w /S u m m e r - F a ll
ch arge
1994
lo ss
are not shown: (100,264) (149,408) in the left panel and (2,99) (53,149) in
vide for such credit. Under the delta-equivalent rule, the
gy-based rules may be partly attributable to their intended
m agnitude of uncovered losses is much greater than under
coverage of nonprice risks. When the results of the strategy-
either o f the foregoing m ethods. In Chart 4, the capital
based rules are examined on a portfolio-by-portfolio basis,
charges computed for several portfolios under the delta rule
however, a systematic pattern appears. For portfolios repre
diverge significantly from the 45 degree line.
senting SEC-recognized strategies, the strategy-based rules
If we turn from the value-at-risk approaches to the
tend to underestim ate the potential loss, generating very
strategy-based rules, we find that Appendix A and C 2 X tend
sm all capital requirem ents. For p ortfolio s representing
either to underestimate risk significantly, yielding large capi
strategies not recognized by the SEC, the rules tend to overes
tal deficits, or to overcompensate for risk, producing large
timate the potential loss, generating correspondingly large
capital surpluses. The C 2 X rule, which is designed for mar
capital requirements.9
ket makers on the trading floor, could result in especially
Finally, all of the rules provide a better estimate of
large uncovered losses. It produces the highest deficits among
potential losses for the set o f portfolios with 180 days to
all of the capital rules considered.
m aturity than for the set with 30-day options. As noted
The Appendix A rule appears to perform well when
options with 30 days to maturity are considered. However,
above, this result can be a ttrib u ted to the high level of
gam m a risk associated with short-dated options.
Table 2 shows that Appendix A also leads to significant capi
In summary, our evaluation o f the efficiency and
tal surpluses. By incorporating only simple trading strate
coverage of the capital rules indicates that the approximate
gies, Appendix A does not entirely allow for hedging or off
value-at-risk rules tend to perform better than the simple
setting portfolio effects, causing substantial excess capital
strategy-based rules. W ithin the category o f value-at-risk
burdens for a number of portfolios.
rules, the gam m a and Taylor series rules provide relatively
The large capital surpluses produced by the strate-
sim ilar results. Both outperform the delta-equivalent rule,
Chart 6
SEC C 2 X R u le
C a p it a l
ch arge
C a p it a l
La r g est
lo ss
ch arge
La r g e st
lo ss
F R B N Y Q u a r t e r l y R e v ie w /S u m m e r - F a ll
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37
and the gamma rule tends to be a bit more conservative than
Consequently, these methods do not create excessive report
the Taylor series rule.
ing burdens for banks that rely on only a few simple options
strategies, primarily for hedging purposes. But while the
V o l a t il it y R is k A d d - o n s
capital requirement of simple strategy-based methods may
To investigate the potential benefits of a volatility risk add
be relatively easy to calculate, these methods can lead to sub
on, we supplement the Taylor series rule with a charge equal
stantial reporting burdens for more sophisticated institutions
to the absolute value of the vega of each position multiplied
that carry out a wide range of trading strategies, since each
by a 5 percentage point change in volatility.10 Since vega rises
type of position would require a different capital requirement.
with the tenor of the option, the volatility add-ons are sub
In addition, capital requirements that rely exclusively on the
stantially larger for the options with remaining maturity of
strategy-based method may compel regulators to revise their
180 days than for those with remaining maturity of 30 days.
capital requirements repeatedly as financial institutions
Across all of the positions, the add-on specification increases
develop new options instruments and trading strategies.
total required capital by 4.2 percent for options with remain
Com pared w ith the sim ple strategy m ethods,
ing maturity of 30 days and 14.4 percent for options with
methods based on price sensitivity require a higher level of
remaining maturity of 180 days.
sophistication on the part of both banks and regulators. Nev
For the 30-day positions the vega add-on has little
ertheless, price sensitivity methods rely on standard risk
tangible effect on measures of capital efficiency. The R 2
management techniques already employed by most major
increases from 0.842 to 0.844, while the slope increases from
financial institutions to manage the risk of their options port
0.96 to 0.97. With respect to coverage, the total capital
folios. Most larger banks use internal risk management sys
deficit decreases from 188 to 168, while the surplus increases
tems that track on an ongoing basis the delta, gamma, and
from 173 to 189- The effect of the volatility risk add-on is
volatility risks of their options portfolios. As a result, in the
larger for the 180-day option positions. The R2 of the regres
sion of capital on largest loss rises from 0.974 to 0.978, while
the slope rises from 1.02 to 1.06. The total capital deficit
declines from 60 to 21, while the surplus rises from 16 to 31.
In summary, a volatility risk add-on certainly does
not reduce the efficiency of the capital charge, but neither
does it markedly increase it relative to the Taylor series rule.
The volatility risk add-on does increase coverage of the
largest losses as measured by the total capital deficit.
an d
methods based on price sensitivity require a
higher level o f sophistication on the part o f both
banks and regulators. Nevertheless, price
sensitivity methods rely on standard risk
management techniques already employed by
O t h e r C o n s id e r a t io n s
S im p l ic it y
Compared with the simple strategy methods,
most major financial institutions to manage
R e p o r t in g B u r d e n
In general, the introduction of specific supervisory capital
requirements for the market risks arising from banks’ options
the risk o f their options portfolios.
positions requires a certain level of sophistication on the part
of both banks and supervisors. Nevertheless, the proposals
case of larger options players, the price sensitivity approach
examined in this paper vary significantly in their complexity
should impose lower reporting burdens than the strategy-
and therefore in their potential reporting burden.
based approach because the methodology reflects banks’
Strategy-based methods can be easily applied by
existing hedging practices and can be applied uniformly to
even the least sophisticated options players because they do
all options positions. In addition, the price sensitivity
not require the use of complicated options pricing models.
approach can simplify the task of regulators: it is flexible
FRBN Y
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1994
enough to incorporate market innovations in options instru
St ra te g y- base d M
ments and trading strategies without requiring additional
The principal advantage of strategy-based capital require
capital standards.
ments is their simplicity. Strategy-based methods do not
eth ods
Scenario methods also tend to be more complex than
require the use of option pricing models and are therefore
simple strategy-based methods. However, like the price sensi
most appropriate for banks that carry out only a limited
tivity approach, these methods rely on variables that most
amount of options business, primarily for the purpose of
larger banks already monitor through their standard risk man
hedging. However, simple strategy-based methods can only
agement systems. Simulation methods are the most complex
roughly estimate the potential losses of an options portfolio.
to implement and may lead to excessive reporting burdens for
all but the most sophisticated banking institutions.
A further drawback of the strategy-based method is
that it may pose reporting problems for sophisticated options
players. Each trading strategy is subject to a different capital
C o n f o r m it y
w it h
E x is t i n g
an d
P r o po se d R ules
requirement, and the approach is generally unrelated to the
The methods examined in this article also vary in the degree
internal risk management systems employed by banks.
of their conformity with existing capital measurement
Moreover, the method lacks the flexibility to incorporate
approaches. By combining credit risk and market risk in one
future market developments in options instruments and
capital charge, the simple strategy method conflicts with the
trading strategies. As a result, regulators must continuously
SFA, CAD, and proposed BIS market risk standards, which
upgrade and expand their capital requirements.
apply separate capital charges for the two types of risk. In
addition, while the SFA, CAD, and BIS proposals allow for a
V a l u e -at- R is k M
limited number of simple strategy-based trades, none of
The value-at-risk methods examined above differ from each
these supervisory approaches permits an across-the-board
other primarily in the treatment of gamma risk. One advan
application of strategy-based methods. In contrast, the price
tage of these methods is that they can be incorporated in the
sensitivity approach can easily be incorporated into the capi
framework of the SFA, the CAD, and the proposed BIS and
tal framework of the SFA, the CAD, and the BIS and SEC
SEC market risk capital requirements.
proposals, each of which allows for a price-sensitivity-based
D e l t a - E q u i v a l e n t M e t h o d . The delta-equivalent rule
method.
provides banks with a relatively simple capital rule. Since
eth ods
The SFA allows a scenario method, while the BIS
most banks that are active in options activities generally mea
market risk proposal considers permitting scenario or simula
sure delta risk as part of their overall risk management strategy,
tion methods as alternatives to the price sensitivity approach.
the delta-equivalent method would not present an excessive
However, because the scenario approach does not strictly
reporting burden for these banks. Further advantages of the
employ the building block methodology as defined by the
delta-equivalent method are that it can be applied to all
BIS market risk proposal— which distinguishes specific from
options positions uniformly, it may allow for portfolio effects,
general market risk— it might have to be “carved out” of the
and it is flexible enough to incorporate market innovations.
building block methodology of the BIS framework.
However, the delta-equivalent rule can seriously
underestimate potential losses in the case of large price move
Sum m ary
of
F in d in g s
ments because it does not incorporate gamma risk. In addi
We have compared various supervisory approaches to the cap
tion, it cannot by itself account for changes in the volatility of
ital treatment of the market risk of options. Our comparison
the underlying instrument.
rested on three criteria: capital coverage of potential losses,
D e l t a - E q u iv a l e n t M e t h o d w it h G a m m a A d j u s t m e n t .
simplicity and reporting burden, and conformity with exist
The delta-equivalent method with gamma adjustment is
ing and proposed supervisory approaches. The main findings
similar to the delta-equivalent method except that it also
of the analysis are summarized below.
modifies the capital requirement for the risk that delta will
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39
change as the price of the underlying moves. Our calculations
sophistication but generally rely on options pricing models
show that adjusting for gam m a risk (with either the Taylor or
to measure the gains or losses on each option position in
gam m a rules) typically leads to a significantly im proved
response to defined movements in the price or volatility of the
approximation o f an options portfolio’s potential losses.
underlying instruments. Scenario methods with full revalua
D elta -E q u iv a l e n t M e t h o d w it h G a m m a a n d V o l a t il it y
tion implicitly account for delta and gam m a risk, and they
A d ju s t m e n t s . In addition to measuring delta and gam m a
can also explicitly account for volatility risk. As a result, these
risk, this approach also takes into account volatility risk, the
methods may provide a more exact measure of potential losses
risk that the variability of the underlying instrument’s price
than the approxim ation-based price sensitivity m ethods.
will increase or decrease, affecting the price of the option. A
Sim ulation m ethods, using either real historical data or a
volatility adjustment could play an important role, depend
Monte Carlo methodology, may facilitate the incorporation
ing on the specific portfolios involved.11
of other variables, such as an option’s time value or its sensi
S c e n a r io - b a se d
and
S im u l a t io n
M e t h o d s w it h
tivity to changes in interest rates.
F u l l R e v a l u a t i o n . Scenario m ethods can vary in their
A p p e n d ix I: D etailed D esc r ipt io n o f V alue - at -R isk R ules
B asic F r a m e w o r k
replaced by a measure o f the asset’s price volatility. For exam
The change in the value (V) o f an options portfolio associated
ple, with a m ultiple m of the standard deviation of the price
with a given change in the price (u ) o f the underlying asset is
change, equation 2 becomes:
given by:
<3)
(1)
AV = V ( « + A # ) - V («).
AV = ^
(mCT) + 2
(mCT>2'
The m ultiple of the standard deviation determines the confi
T h is change may be approxim ated using a second-order
dence level of the capital rule.13
The m agnitude o f value at risk typically depends on
Taylor series expansion:
both the portfolio’s sensitivity to changes in the price of the
/o\
(2)
<3V a
1 d2V a 2
underlying asset and the price volatility o f the underlying
AV ' T u A * + 2 ~Su1 Aa ’
asset. In term s o f equation 3, if the p ortfolio were well
where AV and A u are changes in the values o f the portfolio
hedged, then the price sensitivity terms dNIdu and d2V/d&2
and the underlying asset, and the partial derivatives dVIdu
would both be small because of the offsetting positions in the
and d2Y ldu2 are the portfolio’s delta and gam m a values.12
portfolio, thereby leadin g to a low capital requirem ent.
To determine the size o f the capital requirement, the
Given the price sensitivity of the portfolio, however, the capi
measure o f price sensitivity is combined with a measure o f the
tal requirement would also be smaller if the underlying asset
volatility of the underlying asset’s price. In terms of equation
had a small price volatility: a smaller likelihood o f large price
2, the change in the price o f the underlying asset, A u, is
changes implies that potential losses will be smaller.
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A p p e n d ix I: D e t a i l e d D e s c r ip t io n o f V a lu e - a t - R is k R u le s
M eth o d s B ased o n P rice S en sitiv ities —
F irst - a n d S e c o n d -O r d e r A pp r o x im a t io n s
Delta-Equivalent Rule. The delta-equivalent rule uses only
the first term in equation 2, the delta value of the portfolio:
(Continued)
price increase as well as a price decrease (of magnitude mcr) is
applied to the Taylor series equation, and the capital charge is
the largest resulting loss:
/e\ v- i • r/dV „ 1 d2V,
o w dV,
\ 1 d2V ,
n1,
(5) K = lm in C (¥ m a + 2 ^ ( m a ) 2) , ( ^ ( - m a ) + 2 du2 (ma)2),0]L
(4)
K -I^ m al,
For a book of written options (when options risk is
where K is the capital charge and m is a m ultiple of the stan
most extreme), the Taylor series rule will always produce a
dard deviation that determines the degree of confidence in
larger capital requirement than the delta-equivalent. How
the capital rule. The delta-equivalent is the basic component
ever, for a book of purchased options, the Taylor series rule
of the C A D ’s rule and the proposed BIS rule.
will require less capital than the delta-equivalent because the
latter overestimates the price risk o f purchased options.
Example. Consider a portfolio consisting of a $ 1 0 0
Gamma Charge Rule. A more conservative application o f
long position in the underlying asset and a written
gam m a values is to use the sum of the absolute values o f delta
call option on $ 1 0 0 of the asset. If the delta of the
and gam m a (when gam m a is negative):
option equals .2 5 , then the delta of this portfolio is
(6)
K = l^(ma)l + lmin(^-^(maf,0)l.
equal to .75 (the written call has a negative delta of
—.25 and the underlying has a delta o f 1, where both
This gam m a charge capital requirement is one of the alterna
are weighted equally since the underlying amount is
tive rules in the SFA capital requirements.
the same for each position). If we assume that a three
The capital charge in this rule is at least as large as
standard deviation confidence interval for the capital
the Taylor series rule (equation 5) because of the way the delta
rule implies a $20 change in the price of the under
and gam m a interact in the Taylor series when they have dif
lying asset, then the capital charge will be $15
ferent signs. For a portfolio o f w ritten options (negative
($ 1 5
gam m a), the Taylor series rule and the gam m a charge rule
= ( .7 5 ) x ($ 2 0 ) ) .
produce identical capital charges. In a portfolio of purchased
The delta-equivalent can often underestimate risk
options, however, the delta term will overestimate potential
because it is a linear approximation to the price sensitivity of
losses, and in the Taylor series rule, the positive gam m a (of
options, which are inherently nonlinear. This approximation
the long options) will reduce the capital charge by moderat
error can be reduced by incorporating an option’s gam m a
ing the effects o f the delta term in equation 5. The gam m a
value, a measure o f the nonlinearity o f an option’s price sensi
charge rule (equation 6), however, does not provide such
tivity. The augmented delta-equivalent rules include such an
“credit” for the delta’s overestimate o f risk. In this case (a
adjustment.
book of purchased options), the delta-equivalent and the
Taylor Series Rule. One use of the gam m a value to augment
gam m a charge rule produce the same capital charge.
the delta-equivalent rule is the direct application o f the Tay
lor series in equations 2 and 3. An option’s price sensitivity
Example. Recall the earlier example o f the delta-
can be different for increases and decreases in the price of the
equivalent rule, and suppose that the option had a
underlying security. Hence, to obtain the capital charge, a
gam m a value o f -0 .1 . The gam m a charge, in this
F R B N Y Q u a r t e r l y R e v ie w /S u m m e r - F a ll
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A p p e n d i x I: D e t a i l e d D e s c r i p t i o n o f V a l u e - a t - R i s k R u l e s
case, is $20 =1 (—0.1) ($20)2/2 I, and the total capital
(Continued')
or, if an approximation is used,
requirement is $35 = $15 + $20. (The $20 term that
is squ ared in the ca lc u latio n is derived from a
v o la tility o f 20 p ercen t w eigh ted by the $ 1 0 0
underlying asset; the $35 term is the sum o f the
where Acr denotes the change in volatility. In equation 8, the
d e lta ch arge from the earlier exam p le and the
options’ volatility sensitivity (vega or lambda) is weighted by
gam m a charge.)
the change in volatility, while in equation 7 the options are
revalued at different volatilities. The SFA capital require
I n c o r p o r a t io n o f V o la tility R isk
ments incorporate such a volatility risk add-on, using a one
C ap ital coverage for v o latility risk can be incorporated
percentage point change in volatility. Although equation 7 is
through an additional capital charge. This charge would be
a more exact estim ate, an option’s sensitivity to volatility
based on
changes tends to be a linear relationship, and the use o f a
volatility sensitivity measure as in equation 8 is a reasonable
(7)
estimate of volatility risk.
V (a + Act) - V(cr)
A p p e n d ix II: E xam ples o f S trategy - based R ules
The following two examples of strategy-based rules are taken
Strategy 2: Long call option and short the underlying stock
from the SE C ’s Appendix A rule, which applies to securities
firms holding options for proprietary trading.
Capital charge: If the call is out-of-the-money, the lesser of
a) 30 percent of the underlying, or
S t r a t e g y 1 : Long
call option
b) the out-of-the-money amount.
If the call is in-the-money, no charge is
Capital charge: 50 p ercen t o f the m arket value o f the
option.
42
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required.
Endnotes
1. A more detailed discussion of options risk and supervisory capital rules
8. Appendix A appears to overcompensate substantially for losses of a few
is found in a related paper by the same authors: “Options Positions: Risk
portfolios, resulting in points with extreme capital levels: capital-to-loss
Measurement and Capital Requirements,” Federal Reserve Bank of New
ratios under the Appendix A rule are as high as 69 :1, in contrast to 6:1
under the delta equivalent rule. Charts 4 and 5 illustrate the differences in
capital levels.
York Research Paper.
2. The paper cited in the preceding note provides a detailed account of
specific methodologies actually used or proposed by regulatory authorities.
9 . Portfolios that have extreme capital-to-loss ratios are synthetic long
3. For examples of specific strategy-based rules, see Appendix II.
futures, delta-hedged protected call, delta-hedged bull call, delta-hedged
bear call, ratio call spread, protected call, delta-hedged ratio call spread,
4. In the interim, the SEC’s Division of Market Regulation issued a “no
action letter” on March 15, 1994, that effectively allows broker-dealers to
use the proposed method.
5. The annual volatility of underlying price changes is assumed to be 30
percent. Historical volatility for the U.S. S&P 500 index has typically
ranged from 10 to 20 percent, but individual stocks can display much
higher volatilities. The average volatility for individual stocks in the Dow
delta-hedged ratio call back spread, and box spread. The portfolios that
represent SEC-recognized strategies are so indicated in Table 1.
10. Vega is defined as the change in the price of an option in response to a
unit change in the volatility of the underlying asset.
11. Volatility risk is largest for one-sided portfolios (all written or all pur
chased), for options with longer maturities, and for options that are close to
the money.
Jones Industrial Average is currently around 30 percent.
12. These delta and gamma values represent net portfolio values that are
6. Capital requirements under the SEC rules could differ depending on the
sequence in which recognized strategies are pulled out from a portfolio.
the arithmetic sum (taking account of the signs) of the deltas and gammas
of all instruments and transactions in the portfolio.
Recognizing that a firm is likely to use the lowest cost interpretation of the
capital rule, we chose the sequence that yielded the lowest level of capital
requirement.
13. Although the degree of confidence provided by a specific multiple of
the standard deviation depends on the precise underlying probability dis
tribution, a rough idea of the degree of protection provided by, say, two or
7. The normalization method used is a delta-based normalization; that is,
the larger of the sum of gross negative delta-equivalent values or the sum of
three standard deviations may be obtained. Given a normal probability dis
tribution, at three standard deviations, losses will exceed capital with a
gross positive delta-equivalent values of the options in a portfolio, excluding
positions in the underlying asset, is normalized to $ 100.00. Further discussion
likelihood of 1 in 700, whereas at 2.33 standard deviations, losses will
exceed capital with a likelihood of one in a hundred.
of approaches to normalization is contained in the paper cited in note 1.
R eferen ces
Bank, for International Settlements. 1994. A n n u a l R e p o r t .
F e d e r a l R e g is te r .
1994. Vol. 59, No. 54, March 21.
N otes
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Making Sense of the Profits of
Foreign Firms in the United States
David S. Laster and Robert N. McCauley
T
he scant profit of foreign firms operating in the
industry (Appendix I).
United States has emerged as one of the biggest
The pretax income reported by foreign firms has
puzzles in international finance. That 4.7 mil
remained low, dropping to $4 billion in 1990, according to
lion workers using $1.8 trillion in assets to gen
the most recently published Internal Revenue Service data
erate sales of $1.2 trillion could fail to turn a profit strikes
(Chart 1, bottom panel). Had foreign firms earned the same
many as unbelievable. Could foreign companies have paid
return on sales as U.S. firms, they would have made an addi
$316 billion in the past decade for firms earning $10.7 bil
tional $32.1 billion in profits. Some claim that such addi
lion in the year before acquisition only to lose money overall
tional profits would yield the U.S. Treasury substantially
on their holdings in 1992— a year in which U.S.-owned firms
larger tax revenues each year (U.S. Congress, House Commit
earned record profits?1
tee on Ways and Means 1990, pp. 186, 250, 288, 300).
Although foreign firms have earned lower U.S. prof
This article attributes the depressed earnings of for
its than their domestic counterparts since World War II, the
eign firms to the firms’ rapid buildup of U.S. operations in
gap has widened substantially in the last two decades. In
the late 1970s and the 1980s. These companies paid top dol
manufacturing, the gap in return on equity averaged 3.4 per
lar for underperforming U.S. firms, borrowed heavily, and
cent in 1951-75, then doubled to 6.8 percent in 1976-80,
then spent freely on investment and marketing. As the share
and reached 8.8 percent in 1981-91 (Chart 1, top panel).
of recently acquired foreign firms in the United States rose in
Returns worsened in petroleum, wholesale and retail trade,
the 1980s, aggregate returns deteriorated.
and finance and insurance as well (Chart 1, middle panel).
The article also investigates two other explanations
Realized returns also deteriorated in real estate, and mark-to-
often advanced for the low returns of foreign firms: 1) a weak
market losses wiped out much of the foreign stake in this
dollar has depressed the firms’ profits, and 2) foreign firms are
44
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Chart 1
P r o f i t a b i l i t y o f F o r e i g n F i r m s in t h e U n it e d S t a t e s
P ercen t
20
Return on Position in Manufacturing
The longstanding gap
between the returns
of foreign-owned
manufacturing firms in
the United States and
U.S. manufacturing firms
widened in the late 1970s
and again in the 1980 s.
15
10
5
0
1951
60
70
80
90
93
P ercen t
10
Return on Sales by Sector of Foreign Firms in the United States
6
Foreign firms' returns
in other sectors deteriorated
in the 1980 s as well.
,
4
2
0
-2
B illio n s o f d o lla r s
40
30
As a result, the taxable
income of foreign firms
remained low.
10
0
-10
1983
84
85
86
87
88
89
90
Sources: U.S. Department of Commerce, Bureau of the Census and Bureau of Economic Analysis, balance o f payments data (top panel)
and operations data (middle panel); Internal Revenue Service (bottom panel).
Notes: In the top panel, petroleum products are included in U.S. manufacturing but excluded from foreign manufacturing; before
1974, U.S. manufacturing included affiliates abroad. Top panel plots both post-tax profit and interest earned by foreign firms as a
percentage of their equity and debt claims on affiliates. Position is average of beginning-of-year and end-of-year data on a historic-cost
basis; position so measured was only 14 percent lower than the position on a current-cost basis in 1993. Middle panel plots only
post-tax profit as a percentage of sales. Bottom panel plots pretax profits.
FRBNY Q
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45
understating their earnings to avoid paying U.S. taxes. We
acquisitions market. Because foreign firms generally denomi
find no clear evidence for the first claim and some support for
nate their U.S. affiliates’ debt in dollars, any cheap foreign
the second. Firms with the most incentive and opportunity to
currency debt confers little advantage. The cost of foreign
shift profits out of the country report lower profits than other
equity matters far more. When the stock exchange in Tokyo
firms. Nevertheless, the rapid rate at which foreign firms
or London places a higher value on a given stream of earnings
divest their U.S. subsidiaries suggests that many investments
than does the N ew York Stock Exchange, a Jap an ese or
really have performed poorly.
British firm can outbid a U.S. firm and still satisfy its share
The last section of the article considers the im plica
holders. In the late 1970s, foreign companies took advantage
tions of our findings. Ju st as the rush of foreign acquisitions
of low U.S. equity prices in the first postwar wave of foreign
in the 1980s depressed returns, so the subdued pace of such
acquisitions. The more sizable surge of foreign acquisitions in
acquisitions in the 1990s points to higher returns in the near
the 1980s drew strength from the high valuations in foreign
future. Improved profits of foreign firms should narrow the
equity markets, especially the Japanese market.
R egression analysis o f acquisitions by companies
internal or fiscal deficit but widen the external, current
from the seven m ajor source countries o f foreign direct
account deficit.
investment shows the importance of both foreign and U.S.
A c q u is it io n s : C auses a n d C o n seq u en c es
equity prices in the tim ing of purchases over the 1980-92
The U .S. Com m erce D epartm en t defines foreign direct
period. We set out to relate the variation over time in acquisi
investment as a U.S. company or partnership in which a for
tion activity (measured against home-country G D P) to equi
eign entity holds a voting share of more than 10 percent. The
ty prices, real interest rates, overall economic growth, the
term “foreign direct investment” may conjure up images of
exchange rate, unit labor costs, and other plausible variables
construction workers building car factories in the Midwest.
Yet such “greenfield” entry represents a small share of the
increase in foreign holdings of U.S. corporate assets: for every
dollar foreign investors spend to establish a new business,
they spend five dollars to acquire existing ones.2
Chart 2
O u t l a y s b y F o r e ig n In v e s t o r s f o r t h e A c q u is it io n
of
U.S. B
B il l io n s
C auses o f F o r e ig n A c q u is it io n A c tiv ity
in t h e 1 980s
u s in e s s e s
of
19 8 7
d ollars
70
60
Before exam ining how strong acquisition activity drove
down the aggregate returns o f foreign com panies in the
50
U n ited States, let us consider the reasons for grow th in
40
acquisitions (Chart 2). As mergers and acquisitions acceler
ated in the United States in the mid- to late 1980s, foreign
firms won more and more bidding contests. After a wave of
30
20
activity in 1978-81 that carried the foreign share of U .S.
acquisitions outlays to a fifth or a quarter of total U.S. m erg
10
ers, foreign acquisitions subsided only to surge to a third of
0
total activity in 1987-90 (Merrill Lynch Business Services
1992, pp. 7, 50).
Foreign firms’ cost of equity advantage (McCauley
and Zimm er 1994, 1989) permitted them to outbid domes
tic firms for corporations “in play” in the U.S. mergers and
FRBNY
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1975
80
85
90
94
Sources: U.S. Department of Commerce, Bureau of Economic Analysis; Merrill
Lynch Business Brokerage and Valuation, Mergerstat Review.
Notes: Reported dollar amounts were converted from current to 1987 dollars
using the GDP implicit price deflator. The 1994 datum is through June,
annualized.
(Table 1). Equity prices exert a substantial influence: a 10 per
sitions: poor selection, high acquisition prices, heavy debt,
cent rise in foreign prices relative to U.S. prices raises foreign
and a rise in post-acquisition operating expenses. Profitabili
ty improves only slowly over time as investment and consoli
acquisitions by 18 to 32 percent.3
dation expenditures pay off, as new managers learn through
C o n seq u en c es o f A c q u isit io n s
experience, and as foreign paren ts sell o ff un successful
The wave of foreign acquisitions in the 1980s raised the share
acquisitions.
of foreign-owned assets that were recently acquired. This
The profitability of new acquisitions traces a J curve
share can be measured as the ratio of outlays by foreigners in
(Chart 4), dropping after acquisition and then recovering
acquiring and establishing U .S. firms to the total foreign
over tim e.5 Consider the factors behind this profile.
ownership stake in U .S.-based firm s (Chart 3).4 By 1990
about half of foreign holdings in the United States had come
P o o r S e l e c t io n . Foreign firms buying U.S. firms do not get
into foreign hands by acquisition in the previous five years.
the p ic k o f the litte r (C h art 5). In the 1 9 8 0 s, fo reign
Another 10 percent o f foreign holdings had been newly
multinationals bought U .S. manufacturers that were only a
established in that same period.
qu arter as p ro fita b le as a broad U .S . norm (Landefeld,
The preponderance o f new acquisition s helps to
Lawson, and Weinberg 1992, p. 83).
explain the weak aggregate profitability o f foreign firm s
because recently acquired firms tend to have low returns. We
review several factors that depress the profits of recent acqui-
Chart 3
I m m a t u r i t y o f F o r e i g n F ir m s in t h e U n i t e d S t a t e s
Acquisition and Establishment Outlays over the Preceding Five Years in Relation
to Foreign Direct Investment Position
Table 1
R e g r e s s io n A n a l y sis o f F o r e ig n A c q u is it io n s in t h e
U n ite d S ta te s,
1980-92
Percent
Dependent variable: Acquisition outlays in the United States as a fraction of
70
Acquisitions and establishments
(Bureau of Econoinic Analysis)
source-country GDP for the United Kingdom, Japan,
Canada, Germany, France, the Netherlands, and Switzerland
60
1 8 2 * **
0 .4 2
Real U.S. equity price
—3 .2 1 * *
1.42
- 0 .1 2 ***
0 .0 4
Foreign unit labor costs relative to U.S.
0 .7 4
0.60
Real foreign GD P growth
0 .0 8
0.05
Real foreign GD P growth, lagged
0 .0 8 *
Real U.S. GD P growth
Real U.S. GD P growth, lagged
0 .0 8 *
0 .0 7 *
0.05
0 .0 4
0 .0 4
Foreign currency per dollar
Real foreign bond yield
Real U.S. bond yield
Exchange rate volatility
Time trend
0.01
- 0 .20 **
-0 .1 7
0.05
0 .0 4
\
$
A
/
y \
# /
i /
i /
i* /I
i /
# /
50
!!* !l!l!| I l® i
1
Real foreign equity price
Independent Variable
A
$
/
40
*%
Coefficient
Standard
Error
Acqu isitions
30 — (Bureau o f Eco
V
- ' '
f
0 .0 9
2.20
0.10
t
%
\
V
»%
\
\\
*%
\
I
\
*
\ *
\\ t%
%
\
%
1
%
V
%
\
\
\
%
»
\
\
» Acquisitions
(Mergerstat)
**
\\
%
%
%
V
20
*
N = 91
Adjusted R 2 = 0.55
Sources: U.S. Department o f Commerce, Bureau o f Economic Analysis;
national sources.
10 i
1977
i
i
i
. . . i i i i
80
-J.
..ill__ 1
85
...... L.........J
90
i......1
94
Notes: Observations are weighted by 19 9 2 position. Dependent variables are
de-meaned by country. A ll variables are expressed in logarithmic form except
for GDP growth rates, bond yields, and the time trend. Estimated intercept is
not reported. Real equity price is stock index deflated by GD P deflator. Real
bond yield is nominal bond yield less contemporaneous inflation as measured
Sources: U.S. Department of Commerce, Bureau of Economic Analysis;
Merrill Lynch Business Brokerage and Valuation, Mergerstat Review.
Notes: Foreign direct investment position is valued at current cost. The 1994
datum is through June, annualized.
by GDP deflator.
♦Significant at 10 percent level.
♦♦Significant at 5 percent level.
♦♦♦Significant at 1 percent level.
F R B N Y Q u a r t e r l y R e v ie w /S u m m e r - F a ll
1994
47
O f course, foreign companies did not buy money-
as the percent excess of the price per share at acquisition over
losers exclusively. The m odal target made a profit in the
price per share pre-bid, have not consistently shown that for
broad range of the U.S. norm, and some were very profitable
eign firms pay higher premia than domestic firms (Cakici,
indeed (Chart 6). Nonetheless, year after year, 40 percent of
Hessel, and Tandon 1991; Cebenoyan, Papaioannou, and
the foreign firms’ targets lost money, and many lost substan
Travlos 1992; Dewenter 1992; Swenson 1993; Harris and
tial sum s.6
Ravenscraft 1991; K ogut and Chang 1991). Foreign firms
could be paying premia similar to those paid by U.S. firms,
H ig h A c q u is it io n P r ic e s . Foreigners pay full price for sub-
say 30 to 50 percent, for a set of firms that contains more
par performers. A s noted at the outset, in 1980-90, foreign
money-losers than do the targets of U.S. firms. In that case,
firm s p a id $ 3 1 6 b illio n for firm s th at had earn ed an
aggregate of $10.7 billion in the year before acquisition. This
price-earnings ratio of nearly thirty-to-one well exceeded the
F oreign firm s b u yin g U.S. firm s do not g et the
price-earnings ratio for the Standard and Poor’s 500, which
pick o f the litter.
ranged from the high teens to the low twenties in the late
1980s, when most of the acquisitions took place.7
The observation that foreign firms in aggregate pay
prices well above market norms for a dollar of earnings need
foreign firms would not overpay by the test of these studies
not imply that they pay more for their U.S. targets than do
but would nonetheless pay a hefty aggregate price-earnings
U .S. acquirers in m erger contests. Takeovers, foreign or
ratio. Similarly, if foreign firms concentrated their purchases
dom estic, require a prem ium to be paid over usual share
in periods with higher acquisition premia (that is, the late
prices. Thus, studies measuring acquisitions premia, defined
1980s) or in industries with high premia, then they could
pay a full price without paying more than U.S. acquirers in
Chart 4
Chart 5
P r o f i t a b i l i t y o f F o r e i g n A c q u i s i t i o n s in t h e
U n it e d St a t e s
Foreign-owned Manufacturing Firms
P r o f it a b il i t y o f Fo r e ig n A c q u is it io n s in Y e a r b e f o r e
A c q u is it io n C o m p a r e d w it h P r o f it a b il it y o f A ll
U .S . M a n u f a c t u r i n g F i r m s
R e t u r n o n s a l e s in p e r c e n t
5 --------------------------------------------------------------------------------------------------Average U.S. manufacturing returns in 1990=3-8
0
e t u r n o n sa l e s in p e r c e n t
p
Returns of newly
acquired U.S.
manufacturers,
1.6
1987-90
\
R
2.2
.♦*'3.0
/
» /
/
12
1
1
-----------------------------\
\
/
Returns reported
in 1990 tax returns, by
year after incorporation
•
\
-2.6
/
U.S. manufacturing 1irms
t\V I
-
*
*
A._
i
i
i
i ...... ...1...........1...........1............1.......... 1......... i............1
-1
0
1
2
3
Y
4
5
6
7
8
9
i
10+
1978
e a r s a f t e r a c q u i s i t i o n /i n c o r p o r a t i o n
i
i
80
i
*%
\
/\
Acc uisitions i n \ X
marlufacturing
-■5 i
\
%
%
%
All acquisitions \
i
i
.... ...J _
85
I-----
J_...
x ...
. ...
....• .....J
90
Sources: U.S. Department of Commerce; Internal Revenue Service, Corporate
Statistics Branch.
Sources: U.S. Department of Commerce, Bureau of Economic Analysis and
Bureau of the Census.
Notes: 10+ includes corporations that did not report year of incorporation.
Returns o f newly acquired U.S. firms represent an average for year before
acquisition.
Notes: Manufacturing excludes petroleum products. Values plotted for
acquisitions in each year show profitability of firms acquired in subsequent
year.
FRBNY Q
48
u a r t e r l y R e v ie w /S u m m e r - F a ll
1994
92
those periods or in those industries. N ote also that the stud
age of foreign firms in the United States, just as such acquisi
ies of acquisition premia cited above take the firm as the unit
tions pushed up U.S. firms’ leverage from 1984 through the
of analysis, whereas the price-earnings ratio of thirty gives
end of the decade.
more weight to large transactions and so could reflect a few
big money-losers.
The m ore leveraged foreign in d u stries show ed
weaker profits. Across manufacturing, the greater the excess
of foreign firms’ debt ratio over that of their domestic coun
H ea v y D e b t : Servicing the debt that often finances a high-
terparts, the weaker the foreign firms’ relative performance as
priced acquisition eats up profits. R JR -N abisco— to offer a
measured by return on assets (Chart 8).
purely domestic example— changed from a money-spinner
How much did higher leverage reduce affiliate prof
to a m oney-loser after it was taken private in a h igh ly
its? Foreign-owned manufacturing firms financed their $429
leveraged buyout in 1989-
billion in assets with 10.9 percentage points more debt in
In manufacturing, foreign companies in the United
1990 than did their U .S. counterparts. The resulting $47 bil
States have generally operated with more debt than have U.S.
lion in excess debt, at an interest rate of 8 percent, lowered
firms. Including debt to parent group, foreign firms’ lever
taxable profit by $3-8 billion. This figure is just shy o f an esti
age— the ratio of debt to assets— ranged from 5 to 15 per
mate of $4.0 billion derived by a parallel calculation using
centage points higher than that of domestic manufacturers
Internal Revenue Service data on net interest paid in relation
(Chart 7). The increase in foreign firms’ leverage here in the
to sales by “foreign-controlled” and “other dom estic” manu
late 1980s contrasted with the general deleveraging trend of
facturers (Table 2). The latter calculation, extended to all
companies in major countries abroad (Remolona 1990). We
industries, shows the total shortfall of taxable income owing
hypothesize that debt-financed acquisitions in the late 1970s
to comparatively high leverage to be $14.5 billion, almost
and again in the late 1980s (Chart 2) ratcheted up the lever
half of the profit gap (Table 2; Chart 1, bottom panel).
Chart 7
Chart 6
Leverage of
P r o f it a b ility D is trib u tio n o f
U.S.
F irm s A c q u i r e d b y
F o r e i g n F ir m s 1 9 8 7 - 8 9
U.S.
M a n u f a c t u r in g F ir m s O w n e d b y
Fo r e ig n In v e s t o r s
R a t io
o f d e b t t o a s se t s in p e r c e n t
65
Percent
—
o f a f f il ia t e s in in d ic a t e d r a n g e
Ratio for foreign
firms including
intercompany debt
60
50
S
55
40
50
*»
U.S. firms
30
45
„
"" 9•* —‘
40
20
35
-......i
1977
J
_J___
80
l
I
Ratio for foreign firms
excluding intercompany debt
1.......1
l
1
85
1
1
i
1
90
92
10
Sources: U.S. Department of Commerce, Bureau of Economic Analysis and
Bureau of the Census.
0
-20.0
or less
-10 .0 to
-19-9
Percent
0.0 to
-9.9
More than
0.0 to 9 9
10.0 to
19-9
20.0
or more
r e t u r n o n sa l e s in y e a r b e f o r e a c q u is it io n
Source: Fahim-Nader 1994, p.58.
Notes: Debt denotes current liabilities plus long-term debt. Payables to
foreign parents have been subtracted from debt, and receivables from foreign
parents have been subtracted from assets, in the numerator and denominator,
respectively, of the ratio for foreign firms excluding intercompany debt.
Petroleum products are included for U.S. companies but excluded for foreign
affiliates.
F R B N Y Q u a r t e r l y R e v ie w /S u m m e r - F a ll
1994
49
P o s t -A c q u i s i t i o n C o s t s : Profits deteriorate further after
therefore explain just $1.7 billion of the $4 billion decline in
acquisition. In manufacturing, acquisition targets in 1987-
profits.
90 managed after-tax profits o f $2.0 billion in the year before
The sharp decline in profitability of newly acquired
acq u isitio n (C hart 5 ).8 Yet 1 9 9 0 tax returns show that
firms thus seems to derive largely from a deterioration in
foreign manufacturers incorporated in 1987-90 collectively
operating margins. Stepped-up investment, increased mar
lost $2.1 billion.
keting expenditures, and consolidation expenses all raise
This $4 billion decline in profits derived from two
operating costs.10 Anecdotes support this inference. An exec
sources: finance and acco u n tin g charges and op eratin g
utive from Sony of America described the high initial invest
results. If foreign manufacturers incorporated in 1987-90
ments required after the acquisition of Colum bia Pictures
financed 10.9 percent more of their assets with debt than did
and Tristar as follows: “The operation spent a lot of money the
domestic manufacturers (as indicated above), their interest
first year....We had to make more movies. They had to spend
expense would have been $1 billion higher.9 A lso, newly
more. They renovated the Culver City studio. They installed
acquired firms sometimes increase their depreciation expense
a lot of new technology from Sony.” 11 To cite another exam
by revaluing tangible assets or increase their amortization by
ple, Thomson of France bought RCA for $1 billion in cash
revaluing intangible assets. Under the generous assumption
and assets five years ago, quadrupled capital spending in two
that recently incorporated firms accounted for the entire dif
years, and only began to post operating profits, not including
ference between “foreign-controlled” and “other dom estic”
interest payments, in 1992 (Browning 1993, p. A7).
manufacturers’ propensity to deduct depreciation and amor
In this matter, foreign acquisitions perform differ
tization expenses, the extra expense would have amounted to
ently from U .S. acquisitions in the period. In contrast to
only $0.7 billion (Policy Econom ics Group, K P M G Peat
recently incorporated foreign-owned firms (Chart 9), U.S.-
M arwick, 1994, pp. IV-2 through IV-4). Taken together,
owned manufacturers incorporated in the three preceding
higher debt, depreciation, and am ortization expenses can
years turned a profit in 1990. U.S. manufacturing industries
with heavy (unrelated) acquisition activity in the 1980s show
declines in nonproduction workers, a development that is
Chart 8
con sisten t w ith im proved operatin g resu lts (Caves and
R e tu r n o n A s s e t s a n d L e v e r a g e o f F o re ig n - o w n e d
Krepps 1993, pp. 251-54). U.S. leveraged buyouts, hardly
F i r m s 1 9 7 7 -9 2
Manufacturing Industry Averages
F o r e ig n
a f f il ia t e r e t u r n s m in u s
Table 2
d o m e s t ic r e t u r n s in p e r c e n t
Q--------------------------------------------------------------------Primary metals
L e v e r a g e a n d P r o f i t o f F o r e i g n -o w n e d F i r m s i n t h e
U n it e d S t a tes
Return gap = -2.56 - 0.17 * Debt ratio gap
Ratio o f Net Interest to Sales (Percent)
ForeignOther
controlled
Domestic
Corporations Corporations Difference
(3)
( 1)
( 2)
2 .7 1
1.82
.89
446
4.0
Wholesale and
retail trade
1.28
1.00
0.2 8
416
1.2
Finance,insurance
and real estate —9.00
- 1 7 .2 0
8.20
113
9.3
2.97
- 0.02
86
0.0
10 6 0
14.5
2.95
Total
Fo r e ig n
5
10
15
20
25
30
a f f il ia t e d e b t r a t io m in u s d o m e s t ic d e b t r a t io in p e r c e n t
Sources: U.S. Department of Commerce, Bureau of Economic Analysis and
Bureau of the Census; Federal Reserve Bank of New York staff estimates.
Notes: Debt ratio denotes liabilities as a proportion of assets. The t-statistic
is in parentheses.
FRBN Y
50
Q u a r t e r l y R e v ie w /S u m m e r - F a ll
1994
Additional
Profit
(3 )x (4 )
(Billions
of
Dollars)
Manufacturing
Others
0
Sales
(Billions
of
Dollars)
(4)
Source: Hobbs 19 9 3 .
Notes: Foreign-controlled corporations and other domestic corporations w ith
in finance, insurance, and real estate are said to differ in that most foreign
banks operate as branches, which are excluded from these data. The negative
net expense is said to reflect financial firms’ earning interest on their unbor
rowed funds. See Policy Economics Group 19 9 4 .
typical acquisitions but the only ones where the target firm
phenomenon both here and abroad ascribe it to payoffs from
continues to report independent results, generally show
investment in plant, equipment, and market share, the slack
improvements in operating results, usually because o f cut
ening o f consolidation expenses, m anagerial learning, and
backs in investment and working capital (Long and Raven-
the divestment of unsuccessful enterprises. A study of 1966
scraft 1993; Kaplan and Stein 1993).
benchmark data on U.S. direct investment abroad found that
A d iffere n ce in p o s t- a c q u is itio n e x p e n d itu re
the return on equity earned by U.S.-owned manufacturers
between U.S. and foreign acquirers is entirely consistent with
rose by 1 percent per year since incorporation.12 More recent
our explanation of the surge in foreign acquisitions. If foreign
Internal Revenue Service data on foreign operations of U.S.
buyers enjoyed a cost of equity advantage, then they were
multinational corporations confirm this strong positive rela
able to put more money in a U.S. firm than its previous man
tio n sh ip betw een p r o fita b ility and experien ce am o n g
agement could justify. By contrast, domestic acquisitions in
m an u factu rin g affiliates in 19 8 8 ; this relation sh ip also
the 1980s have been interpreted as a device for disciplining
applies to affiliates in the finance and trade sectors (Lutzy and
managers to accept the consequences of their (high U.S.) cost
M iller 1992, p. 86).
of capital (Blair and Litan 1990).
The relation holds even more strongly for foreign
firms’ operations in the U nited States. Cross-sectional data
S u b s e q u e n t R e c o v e r y o f P r o f i t s : D irect in vestm ent
for 1990, provided at our request by the Corporation Statis
profits improve with age. Researchers who have observed this
tics Branch of the Internal Revenue Service, show that return
Chart 9
P r o f i t a b i l i t y o f F o r e i g n F irm s in t h e U n i t e d S t a t e s i n 1 9 9 0 , b y N u m b e r o f Y e a r s s i n c e I n c o r p o r a t i o n
R eturn
R
o n e q u i t y in p e r c e n t
12 ----------------------------------------
e t u r n o n e q u i t y in p e r c e n t
Manufacturing
Finance, Insurance, and Real Estate
Wholesale and Retail Trade
All Industries
-8 L
0-3 years
4-6 years
7-9 years
10 or more years
0-3 years
4-6 years
7-9 years
10 or more years
Source: Internal Revenue Service, Corporation Statistics Branch.
Note: Affiliates whose age was not reported are grouped together with affiliates of ten or more years of age.
F R B N Y Q u a r t e r l y R e v ie w /S u m m e r - F a ll
1994
51
on equity improves at a rate of about 1.2 percent per year
has a median value of 4 percent per year (Chart 10). Thus, sub
(Chart 9). The results are equally strong in a fixed sample over
stantial new investment and expansion of existing businesses
the years 1980-87.13
m ust occur each year just for the existing stock o f foreign
direct investment to remain stable. When new foreign invest
S u b s e q u e n t D i v e s t m e n t : R eturns im prove over tim e as
ment slackened in 1992, the number of Americans working
foreign firm s sell off their U .S . operations at a su rp ris
for foreign firms declined for the first time in at least fifteen
in gly rapid rate. B ecause d raw in g inferences from the
years (Zeile 1994). The attrition rate reached as high as 10
p o s t- m e r g e r p e rfo rm an c e o f firm s p o se s d iffic u lt ie s
percent in 1986 (Chart 10). At the latter figure, the half-life of
(M agenheim and M ueller 1988; Franks, H arris and Tit-
foreign holdings in the United States is seven years— a year
man 1991; Healy, Palepu, and R uback 1992), researchers
longer than Renault’s investment in American Motors and
have m easured the success o f dom estic m ergers by their
three years longer than Volkswagen’s venture producing cars
survival over tim e. T h u s, analysts have interpreted the
in Pennsylvania (Hood and Young 1986, pp. 175-78).
sale by th e m i d - 1 9 8 0 s o f 4 7 p e rc e n t o f 6 0 0 0 f i r ms
U .S. D ir e c t I n v e s t m e n t A b r o a d : A natural test for any
explanation o f low profits o f foreign firm s in the U nited
States is whether it can account for the respectable perfor
R eturns im prove over tim e as fo r eig n firm s sell
mance of U .S. direct investment abroad, which earned 8.3
o f f th eir U.S. operations a t a su rp risin gly
percent on position valued at current cost in 1993 (Weinberg
ra p id rate.
1994, p. 114; Scholl 1994, p. 63; see also Kapler 1994). Our
explanation, which relates profitability to the recency o f
acquisitions, passes this test. Internal Revenue Service data
acquired between 1950-76 (Ravenscraft and Scherer 1987)
and the sale by 1989 of 44 percent of 271 large firms acquired
between 1971 and 1982 (K aplan and W eisbach 1992) as
demonstrating that hoped-for results remained elusive. Sim i
larly, major corporations had divested half of the 2000 acqui
Chart 10
A t t r i t i o n o f F o r e i g n F i r m s in t h e U n i t e d S t a t e s
Proportion of Foreign Firms' Employees Whose Firm Was Sold, Liquidated,
or Cut Back
sitions that they had made between 1950 and 1986 by the
Percent
latter date (Porter 1987).
14
The Bureau of Economic Analysis has measured the
sales and liquidations of whole divisions by foreign firms in
the United States for selected years. Liquidation refers to the
fate of the foreign owners’ interest rather than the fate of the
corporate assets. Thus, the 1992 data (Zeile 1994, p. 157)
Sales and liquidations
12
10
8
apparently include the Allied-Federated store chain, which
passed from its Canadian owner’s hands when the firm exited
6
Chapter 11, and perhaps the Santa Fe railroad, whose Canadi
4
an m inority owners, the real estate developers the Reichmanns, sold off their share. The unit for this count is employ
2
ees: the number of U.S. workers at firms or divisions sold or
liquidated by foreign-owned firms. We chart these numbers as
H Cutbacks
0
i
U
n 11i n■ i ii
■■■■■■■
1984
85
86
89
90
91
92
a fraction of all Americans working for foreign-owned firms at
the end of the previous year.14 The attrition rate so measured
Digitized
52 for FRASER
FRBN Y
Q u a r t e r l y R e v ie w /S u m m e r - F a ll
1994
Sources: Howenstine 1987, p.38; Herr 1988, p.6 1; Bezirganian 1993, p.92;
and Zeile 1994, p.156.
for 1988 show that the median year of incorporation (mea
wedge between the profitability of foreign and domestic
sured by sales) for U.S.-owned firms abroad was between
I960 and 1964 overall and between 1955 and 1959 for man
ufacturers (Lutzy and Miller 1992, p. 86). By contrast, Inter
nal Revenue Service data for 1990 indicate that the median
foreign-owned firm in the United States dated only to the late
firms.
in the United States in the 1980s. As foreign firms’ recent
acquisitions bulked larger in their overall holdings here, the
1970s, a generation later. Despite the shortcomings of years
low returns associated with these acquisitions dragged down
since incorporation as a measure of the maturity of direct
the aggregate profitability of foreign firms.
In summary, the after-effects of a wave of acquisi
tions help explain the declining profitability of foreign firms
investment stocks, U.S. direct investment abroad clearly has
Before proceeding to consider the role of the weak
stood the test of time and shows it in its returns. Moreover,
dollar, let us estimate how the characteristics that we have
U.S. manufacturers abroad showed weak profits in the 1950s
ascribed to foreign firms in the United States—higher lever
and 1960s, when their holdings were growing rapidly.
age and recency of acquisition (immaturity)—may have hurt
profits. As noted above, if foreign firms paid the same net
Foreign acquisitions of
interest in relation to receipts as U.S. firms, the profits of the
U.S. firms have to some extent yielded poor returns for the
former would have been higher by $14.5 billion in 1990. If
same reasons as have domestic acquisitions. Foreigners pay
all foreign firms earned as much as the ones that had been
acquisition premia between 30 and 50 percent, not much
here for ten years, then they would have earned $11.9 billion
more than U.S. acquirers. Rapid rates of divestiture suggest
more income in 1990 (Table 3). On this showing, leverage
that foreign and U.S. managers alike experience disappoint
and recency account for much of the 1990 shortfall of profits
ment with their acquisitions. Foreign firms may differ from
of $32.1 billion (Chart 1, bottom panel).
F o r e ig n v e r s u s
U.S.
A c q u isit io n s:
domestic acquirers, however, in their selection of targets.
W hile domestic firms purchase targets whose profits are at or
T h e D o l l a r ’s V a l u e
near industry standards (Ravenscraft and Scherer 1987, pp.
Observers have proposed another explanation for the low prof
56-74), foreign firms buy a large proportion of money-losers.
its of foreign-owned companies in the United States: the sharp
Another major difference lies in money spent after acquisi
depreciation of the dollar since 1985. Because U.S. affiliates of
tion: new foreign owners open their wallets wider than new
foreign firms import nearly twice as much as they export, a
U.S. owners. Even absent any differences between foreign
decline in the dollar could easily raise their dollar-denominat
and domestic acquisitions, the fact that recently acquired
ed input costs more than it raises their export revenues.
firms constitute a substantially larger share of foreign firms
Certain high-profile industries provide support for
than of domestic firms allows acquisition activity to drive a
this hypothesis. Affiliates engaged in automotive wholesale
Table 3
M a t u r i t y a n d P r o f it , 1 9 9 0
Return on Sales
(Percent)
A ll
Affiliates
M anufacturing
W holesale and retail trade
Incorporated
before
19 8 1
Profit
(Billions o f dollars)
Incorporated
after
19 8 1
Sales
(Billions
o f Dollars)
A t p re - 1 9 8 1
Return on
Sales
Actual
Difference
1.8
3.0
0.3
446
13 .4
8.1
5.3
- 0.6
- 0 .5
- 1.6
416
- 2.1
- 2.6
0.5
Finance, insurance, and real estate
—0.6
0.5
- 2.1
113
0.6
- 0 .7
1.3
Other
- 1.1
4 .7
- 4 .7
85
4 .0
-0 .9
4.0
4 .9
Total
10 6 0
15 .9 *
1 1 .9
Source: Internal Revenue Service, Corporation Statistics Branch.
*Datum is sum o f four hypothetical profits above.
F R B N Y Q u a r t e r l y R e v ie w / S u m m e r -F a ll 1994
53
trade have suffered a sharp decline in profitability owing to a
weak dollar (Chart 11). In particular, each 10 percent depre
centage points, which at 1992 levels amounts to $850 mil
man 1987; Froot and Klemperer 1989; Hooper and Mann
1989; Okuro 1989; Marston 1990; Knetter 1994; Rangan
and Lawrence 1993).16 Chart 11 suggests that foreign auto
companies have not only maintained dollar prices on their
lion. During the mid-1980s, when the dollar was strongest,
exports but have also squeezed wholesaling margins in the
return on assets peaked at over 9 percent. In 1990 and 1991,
United States—a strategy that serves the same goal of keep
with the dollar 35 percent lower, the affiliates suffered losses.15
ing prices to U.S. consumers competitive. In short, the pric
The compression of profits in automotive wholesale
ing strategies of multinational firms, at least in autos, have
trade suggests that the conventional analysis of how exporters
offset the weakening of the dollar by much more than inter
to the United States have responded to the weak dollar is
national trade prices can demonstrate.
ciation of the dollar reduces their return on assets by 1.5 per
incomplete. Economists have measured the varying extent to
W hile the evidence on automobile trade is com
which foreign exporters respond to a strengthening of their
pelling, a comprehensive industry-by-industry review finds
currencies by permitting higher dollar costs to pass through
that the impact of the dollar’s value on foreign firms’ prof
to higher dollar export prices or, alternatively, by slashing
itability is small and ambiguous. The dollar should have lit
profit margins to price to the U.S. market. These studies have
tle impact on affiliate profits in services, finance, insurance,
found that foreign companies have responded to a weak dollar
real estate, construction, transportation, or food stores, which
by maintaining dollar prices on exports to the United States
together constitute 22 percent of the gross product of direct
to some extent at the expense of their profit margins (Krug-
investment in the United States, because imports and exports
combined amount to less than 5 percent of sales in these seven
industries (Zeile 1994, pp. 173,177). For each of the remain
ing twenty-eight industries (see endnote 41), we regress
Chart 11
return on assets on the logarithm of the trade-weighted U.S.
T h e D o l l a r E x c h a n g e R a te a n d P r o f it a b ili t y In M o t o r
exchange rate as computed by the Federal Reserve Board for
V e h ic le W h o le s a le T ra d e 19 7 7 -9 2
R
the years 1977-92.
e t u r n o n a s s e t s in p e r c e n t
10
^
1985 n ^
Return on Assets = 2.68 + 0.15* (Exchange rate-100)
_
(7.83)
19840/ ^
8 ---------------R2 = 0.81
N = 1 6 ------------------------- X
--------------
1979Q
1988
□
1980 q
1986
1981
□
1977 U „/
1983
12). In four industries, profit showed a statistically signifi
cant (at the .01 level) contemporary or lagged response to the
1982
□
dollar (Table 4). In contrast to automotive wholesale affili
ates, whose profits suffer from a weak dollar, foreign firms in
t—11989
several export-intensive industries—mining, agricultural
1 1991
1990
L__
80
their profit to the dollar’s exchange rate. The regression
results suggest that a weak dollar reduces profits in eleven
industries but boosts profits in seventeen industries (Chart
.✓ '1987
1 9 9 3 ^ 1978
The twenty-eight industries vary in the response of
wholesale trade, and agriculture—show higher profits when
1
90
T
...i.....
I
1
1
1
100
11 0
12 0
13 0
140
1
150
r a d e -w e i g h t e d d o l l a r e x c h a n g e r a t e
Sources: U.S. Department of Commerce, Bureau of Economic Analysis;
Board of Governors of the Federal Reserve System; Federal Reserve Bank
of New York staff estimates.
Notes: The exchange rate used is the Federal Reserve Board's multilateral
trade-weighted dollar index (March 1973 =100). The profitability data also
include manufacturing results for some automotive firms whose primary
activity was in wholesale trade. The t-statistic is in parentheses. The
regression of return on sales on the exchange rate yields an estimated
equation: return on sales =0.85+0.05* (exchange rate-100). The t-statistic is
8.09; the R-squared is 0.82.
Digitized
F R B N Y Q u a r t e r l y R e v ie w / S u m m e r -F a ll 1994
54 for FRASER
the dollar is w eak.17 W hether exchange rate effects are
summed across just the industries that show a significant
relation or across all twenty-eight industries (Table 4), the
net impact of a 10 percent dollar depreciation is well under
$1 billion. Explanations for the $32.1 billion shortfall in
profits must be found elsewhere.
Given that affiliates import substantially more than
they export, the finding that a weak dollar does little to
depress affiliate profits seems surprising. Foreign-owned
wholesalers account for most of the excess of imports over
exports but, as we have seen, their parents share their profit
Chart 12
Ef f e c t o f D o l l a r Ex c h a n g e R a t e o n F o r e ig n
F ir m s ’ P r o f it s
Distribution across Industries
N
compression when the dollar weakens. In U.S. manufactur
u m b e r o f in d u s t r i e s
ing, both exporting firms and import-competing firms tend
to benefit from dollar weakness (Hung 1992-93).18 More
over, compared with the wholesalers, foreign manufacturers
.i 1
■ in
are larger and their profits stronger to begin with, so their
—
Less -0.15 -0.12 -0.09 -0.06 -0.03
0
than
to
to
to
to
to
to
-0.15 -0.12 -0.09 -0.06 -0.03
0
0.03
E s t im a t e d
0.03
to
0.06
0.06
to
0.09
0.09
to
0.12
more weight.
■
i r
improvement in response to the dollar’s weakness carries
0.12 Greater
to
than
0.15 0.15
P r o f it S h if t in g
Public discussion of the low profitability of foreign firms has
centered on assertions that they understate their profits to
c o e f f ic ie n t
Sources: U.S. Department of Commerce, Bureau of Economic Analysis; Board
of Governors of the Federal Reserve System; Federal Reserve Bank of New York
staff estimates.
Notes: Return on assets is regressed on a constant and the natural logarithm of
the trade-weighted dollar. The regression was run for each of twenty-eight
industries for the years 1977-92. The exchange rate used is the Federal Reserve
Board’s multilateral trade-weighted dollar index (March 1973 =100). A
positive coefficient implies that profits rise when the dollar appreciates; a
negative coefficient, that profits fall when the dollar appreciates.
avoid U.S. taxes. A multinational firm can shift profits from
one tax jurisdiction to another in at least two different ways.
A firm’s treasurer can load debt onto its operations in one
country and thereby shelter the income earned there with tax
deductions for interest paid. Or a firm can arrange for its
operations in one tax jurisdiction to pay those in other juris
dictions high prices for goods and services, or outsize royalty
or interest payments.
Table 4
T h e D o l l a r E x c h a n g e R a t e a n d t h e P r o f i t a b i l i t y o f F o r e i g n F i r m s in t h e U n i t e d S t a t e s
Annual Data 19 7 7 —92
Forecasted Impacts
Regression Results
Industry
Contemporaneous
Exchange Rate
Beta
R-squared
Lagged
Exchange Rate
Beta
1 9 9 1 Industry
Assets
(Billions
R -squared
o f Dollars)
Estimated Impact o f a 10 Percent
Depreciation o f the D ollar
(M illions o f Dollars)
Subsequent Year
Same Year
Selected industries
M otor vehicles and equipment wholesale trade
0 . 16 0 **
0 .8 0
0 .0 1 3 3 * *
(0.035)
0 .5 1
58.2
-9 3 1
-7 7 4
0 .6 4
-0 .1 6 5 * *
(0.034)
0.62
22.0
35 6
363
-0 .0 5 3 * *
(0 .0 1 2 )
0 .5 8
-0 .0 5 6 * *
0 .6 0
9-1
48
51
-0 .0 8 7 * *
0 .5 4
0.36
4.2
37
31
Total o f selected industries
-490
Memo: Sum o f estimated impacts for all 28 industries in sample
-6 7 8
-3 2 9
482
(0 .022 )
M ining
-0 .1 6 2 * *
(0.032)
Farm-product raw materials wholesale trade
Agriculture, forestry, and fishing
(0 .02 2 )
(0 .0 1 2 )
- 0 .0 7 4 *
(0.027)
Sources: U.S. Department o f Commerce, Bureau o f Economic Analysis; Board o f Governors o f the Federal Reserve System.
Notes: Return on assets is regressed on a constant and the natural logarithm o f the trade-weighted exchange rate. The indicated regression is run for each o f twenty-eight
industries for the years 1 9 7 7 —92 . Selected industries are those whose contemporaneous or lagged regressions are significant at the 1 percent level. Standard errors are in
parentheses. Estimated intercepts are not reported.
*Significant at 5 percent level.
**Significant at 1 percent level.
F R B N Y Q u a r t e r l y R e v ie w / S u m m e r - F a ll 1994
55
The U.S. tax code tries to prevent both forms o f prof
burden. A scan o f corporate tax rates in major source coun
it shifting. Foreign firm s lose the full tax deductibility o f
tries suggests at first that foreign companies do not have
interest payments if the fraction o f their global consolidated
much to gain by shifting income out o f the United States.
debt in the United States is higher than the fraction o f their
That is, companies based in most foreign countries would pay
assets in the United States .19 Similarly, multinational firms
as much in home country taxes on an extra dollar o f income as
lose deductions for internal, or transfer, prices if they differ
they would pay in combined U.S. and home country taxes if
from prices that would be set in arm’s-length transactions.
they reported the income in the U nited States (Landefeld,
In the remainder o f this section we consider whether
Lawson, and W einberg 19 9 2 , p. 84).21
the low profit reported by foreign-owned firms in the United
Such a comparison does not prove that foreign firms
States stems from profit shifting strategies that allow these
face no immediate tax incentive to shift profits out o f the
firms to avoid U.S. taxes.
United States, however, for at least two reasons.22 First, statu
tory tax rates at home may overstate the effective tax rate .23
E a r n in g s S t r ip p in g t h r o u g h E x cessive
Second, foreign firm s need not shift profit to th eir home
L e v e r ag e
country; they can shift profit to low-tax third countries as
As established above, the U.S. affiliates of foreign firms oper
well.
ate at higher leverage in the U nited States than do U.S. firms.
But the tax code specifies a different standard o f comparison:
R
does the interest-bearing debt o f a U.S. affiliate (including
Shifting income to low-tax countries pays off best for firms
debt to foreign affiliates) in relation to U.S. assets exceed the
from countries, mostly in Continental Europe, that apply the
foreign firm ’s consolidated worldwide ratio o f debt to assets
principle o f territorial taxation to their home firms. Firms
(U.S. Congress, Join t Committee on Taxation 19 8 9 , p. 34)?
headquartered in these countries are exempt from local taxes
That leverage o f foreign firms’ affiliates in the United States
on their foreign profits. W h en these firms transfer income
rose in the 1980 s while leverage was falling in most major
out o f the United States into a low-tax third country, they
source countries increases the likelihood that some compa
pay only the taxes o f that third country. By contrast, in a
nies attempted to reduce their taxes here by burdening their
country that applies the principle o f w orldw ide taxation,
U.S. affiliates w ith excessive debt. Lacking the company-by-
such as Japan or Britain, a firm receives a credit for taxes paid
company data necessary to test for excessive debt, we simply
abroad but m ust pay ad dition al taxes to its home fiscal
note that the evidence does not perm it the inference that for
authorities when it brings home income from a tax haven.
eign firms burden their U.S. operations with more than their
T hu s, firm s fro m c o u n trie s u n iv e rs a lly a p p ly in g th e
fair share o f debt.
territorial principle o f taxation stand to benefit most from
eturns
of
Fo
r e ig n
F ir m
s
by
H
ome
Ta
x
R
e g im e
:
transferring income out o f the United States .24
T r a n sfe r P r ic in g
How do firms from the two kinds o f countries com
The second method o f shifting profits, transfer pricing, may
pare in their U.S. profitability? Broadly following previous
help explain w hy foreign firm s report lower profits than
analysts (Slemrod 19 9 0 ; Auerbach and Hasset 19 93), we look
domestic firms. But it cannot readily explain why the prof
for differences in behavior across firms from the two types of
itability o f foreign firms declined in the 1980 s, a trend better
countries. The U.S. operations o f firms from countries that
explained by acquisition activity. Transfer pricing could only
tax strictly on the territorial principle report lower profitabil
help to account for developments in the 1980s if the U.S. tax
ity (Chart 13 ) than do the U .S. operations o f firm s from
authorities failed to step up the enforcement effort as foreign
countries that tax w orldw ide profits (U nited K ingd om ,
acquisitions accelerated during this period .20
Japan) or tax profits from nontreaty countries (Canada, Ger
Foreign firms m ight want to shift profits out o f the
many ).25 This finding is no more than suggestive, however, in
U nited States if they could thereby lower their global tax
view o f the different m ix and vintage o f industries across
Digitized
56for FRASER
FRBN Y
Q u a r t e r l y R e v i e w /S u m m e r -F a l l
1994
countries. We now consider another approach to the transfer
An analysis of nineteen major manufacturing indus
pricing question that focuses not on country-specific incen
tries for the period 1977-92 shows that industries in which
affiliates import a higher fraction of their sales from their
tives to shift income, but on industry-specific opportunities
to shift income.
parent group report lower returns on sales (Chart 14).26
Reported profits vary inversely with the opportunity to
R eturns
of
F o r e ig n
F ir m s
an d
Extent
of
transfer income.
Trade between the U.S. operations of
This finding is only suggestive. Imports from par
foreign firms and the firms’ affiliated companies abroad has
ents may simply proxy for overall imports. In that case, the
exceeded $100 billion per year since the mid-1980s and in
observed relationship could mean only that a weak dollar
1992 reached about $200 billion. Two-thirds of such trade
crimped the profits of manufacturing industries heavily
takes the form of imports from the foreign parent group.
dependent on imports. This relationship between low profits
In t r a f ir m T r a d e :
Such extensive intrafirm international trade sug
and high imports, however, gains further credibility when it
gests that modest deviations from arm’s-length pricing could
survives in a regression analysis controlling for overall import
succeed in shifting substantial income abroad. Indeed, mer
propensities and exchange rate effects (Appendix II).27
chandise trade issues account for 75 percent of the adjust
How big might profit shifting through the pricing
ments that the Internal Revenue Service recommends (U.S.
of imports from related parties be? The relationship between
Department of Treasury and Internal Revenue Service, 1988,
profitability and imports from parents across manufacturing
Appendix B, p. 1). Accordingly, we investigate whether a
suggests that for every additional dollar of imports from par
larger opportunity to manipulate prices is associated with
ents, returns are 24 cents lower. Since manufacturing affili
weaker reported profits in the United States.
ates of foreign firms imported $33.2 billion from their par
ents in 1990, transfer pricing could reduce profits by as much
as $8.0 billion. By this calculation, transfer pricing in
Chart 13
Chart 14
P r o f i t a b i l i t y o f F o r e i g n M a n u f a c t u r e r s in t h e
U n it e d S t a t e s b y H o m e T a x R e g im e
R
P r o f it a b il i t y a n d Im p o r t s f r o m F o r e ig n P a r e n t s 1 9 7 7 - 9 2
Manufacturing Industry Averages
e t u r n o n s a l e s in p e r c e n t
6 ----------—----------------------------------------
R e t u r n o n s a le s in p e r c e n t
6 ------------------
Credit: Affiliates ultim ately owned by firms in
countries that tax all or some foreign income
and give a credit for taxes paid: Japan,
United Kingdom, Canada, Germany
Exempt: *
-4 L.
1977 78
J__ L
79 80
^
J___L
81 82
83
J___L
84
85
86 87
89
90
91
92
Sources: U.S. Department of Commerce, Bureau o f Economic Analysis;
Organization for Economic Cooperation and Development 1991.
Note: Canada and Germany exempt income from those countries with
which they have tax treaties but tax income from other countries.
, (-3 .62 )
Soaps and
cleaners
r,
Affiliates ultim ately owned by firms in
countries that completely exempt foreign
income from income taxes: Netherlands,
France, Switzerland
Return on sales = 2.89 - 0.24 * imports from parents as
a percentage of sales
□->.—□
O
R = 0.44
□
l~1
Printingand*****’*
publishing
\
□
Stone clay,
and glass
Im p o r t s
Electrical machinery
□
Nonelectrical m ach in eryv\ , s^
■4 1------------------- 1........ ...
5
N = 19
Transportation equipment
_ i -------------------1
1
10
15
20
i
25
fr o m p a r e n t s as a p e r c e n t a g e o f sales
Source: U.S. Department of Commerce, Bureau of Economic Analysis;
Federal Reserve Bank of New York staff estimates.
Note: The t-statistic is in parentheses.
F R B N Y Q u a r t e r l y R e v ie w / S u m m e r - F a ll 1994
57
manufacturing might account for a quarter of the $32 billion
profit gap (Chart 1, bottom panel).
ships and then summarize the results of a multivariate analy
sis that is described in more detail in Appendix II.
Even were this result accepted at face value, it could
only help explain the low level of foreign firms’ profits. The
Our factor-by-factor analysis overexplains the prof
itability gap, reflecting overlap in the factors considered.
puzzle of the declining profitability of foreign firms in the
The acquisition-related factors of leverage and recency are
United States would still remain. As a fraction of sales, inter
most prominent, together accounting for five-sixths of the
national trade with affiliated companies has fallen from 22
gap between the profits of foreign firms in the United States
percent in 1977 to 16 percent in 1991. A declining propor
and those of domestic firms. Possible transfer pricing
tion of affiliate transactions does not accord with a widening
accounts for about a fourth of the gap. The exchange rate
profitability gap.
effect is negligible.
The m ultivariate analysis employs the variable
RECENCY to measure the fraction of assets acquired in the
A s s e s s i n g R e l a t iv e I m p a c t s
We can now estimate how much each factor discussed in this
previous three years. RECENCY captures a variety of influ
article has contributed to the low profit of foreign firms in the
ences: acquisition, selection, pricing, post-acquisition
United States (Table 5). We have already considered the indi
expenses, and eventual attrition. These acquisition-related
vidual relationship between each of these factors and prof
influences are more clearly distinguished from leverage in the
itability. In this section, we return to these bivariate relation-
multivariate analysis than in the bivariate analysis.
The multiple regression analysis confirms the impor
tance of those influences represented by the variable RECEN
CY, yielding results remarkably consistent with the bivariate
7 able 5
E x p l a in in g t h e P r o f it a b il it y G a p B e t w e e n F o r e ig n F ir m s
i n t h e U n i t e d S t a t e s a n d D o m e s t i c F i r m s in 1 9 9 0
age. Possible transfer pricing now explains only a fifth of the gap.
Estimates (Billions o f Dollars)
Based on M ultiple
Regression Analysis
Based on
Bivariate
Analysis
Factor
Return
on Assets
Return
on Sales^
12 .6 *
6 .8 f
10.1
6.5
3 4 .4
6.7*
26.0
20.6
32.1
3 2.1
3 2.1
Recency
1 1 .9
Leverage
14.5
D ollar exchange rate
-
Transfer pricing
8.0
Total
4 .0
Memo: Gap between profits o f
U.S. and foreign firms
analysis. Both regressions sharply downplay the role of lever
* Regression 1 (Table B2) coefficient o f—.0 5 8 m ultiplied by .1 4 0 ( 1 9 9 0 value
o f .222 [Table B l] less U.S. value o f .082) yields .0 0 8 1 o f assets o f $ 1 .5 5 tril
lion, or $ 1 2 .6 billion. U.S. value o f .0 8 2 is estimated on the basis o f the com
parative levels o f acquisition activity from 1 9 8 8 - 9 0 (M errill Lynch 19 9 2 ) as
share o f 1 9 9 0 assets (Hobbs 19 9 3 ) for domestic and foreign firms.
f Regression 1 (Table B2) coefficient o f- .0 8 1 m ultiplied by .0 5 4 ( 1 9 9 0 value
o f .775 less U.S. value o f .7 2 1 , both from Hobbs 19 9 3 ) yields .0 0 4 4 o f assets of
$ 1.5 5 trillion, or $ 6.8 billion. W e use Statistics o f Income data for foreign and
domestic firms because we lack a domestic benchmark for Bureau o f Economic
Analysis data outside o f manufacturing and other selected subsectors.
| Regression 1 (Table B2) benchmark coefficient o f- .0 5 2 m ultiplied by .083
( 1 9 9 0 value o fM P A R (Table B l) less 0) yields .0 0 4 3 o f assets o f $ 1 .5 5 tril
lion, or $6.7 billion. X P A R was not used as it was statistically insignificant;
its inclusion would have raised the impact o f transfer pricing to $ 7 .8 billion.
§ The impacts are calculated in the same manner as in the three prior notes,
except that the coefficients for return on sales regression 7 are used instead:
- . 0 6 1 for RECENCY, - .0 6 3 for LEV, and - .0 6 7 for M PAR. W e then
m ultiply results by 1 9 9 0 sales o f $ 1 .1 8 trillion to arrive at dollar amounts.
Digitized
FRBNY Q u a r t e r l y R e v ie w / S u m m e r -F a ll 1994
58for FRASER
The impact of the dollar was ambiguous in this analysis, so again
we attribute no effect.
Im p l ic a t io n s f o r T a x e s
Observers have calculated how many more billions of dollars
foreign-owned firms would earn if they were as profitable as
comparable U.S. firms. Using the 1990 IRS data on return on
sales by sector, they would arrive at $32.1 billion. They
would then multiply this sum by the 34 percent top corpo
rate tax rate to generate an estimate of potential additional
tax receipts of about $10 billion.28
Were it simply a matter of transforming low-profit
foreign firms in the United States into normally profitable
firms, these calculations would hold. But roughly 60 percent
of foreign firms report losses each year, while only half of
U.S.-owned firms report losses.29 When solidly unprofitable
firms become somewhat less unprofitable, they may not pay
any more income taxes.
That taxes paid in 1990 exceeded foreign firms’
aggregate pretax income underscores the importance of the
distribution of profitable and unprofitable firms. Profitable
foreign firms earned $29 billion while unprofitable ones lost
$25 billion, so the firms earned $4 billion in aggregate. The
$4 billion in aggregate earnings offers no clue to the taxes
financing last year’s deficit adds to this year’s deficit. Owing
to the poor returns of foreign companies in the United States,
the U.S. economy is not yet paying the full cost of its external
deficits.
paid by foreign companies.
It is revealing to compare taxes paid by foreign com
future, the servicing costs so far avoided will begin to come
panies with those paid by U.S. firms. As a fraction of sales,
due and compound. The current account deficit would there
taxes paid by foreign firms in the United States did not differ
fore widen. On the home front, however, higher profits by
much from the taxes paid by U.S.-owned firms in 1983-85
foreign firms would mean higher corporate tax payments and
(Chart 15). Since then, a gap has opened up: if foreign firms
a narrower fiscal deficit. In short, the maturing of foreign
paid as high a fraction of their sales in taxes as U.S. firms, they
affiliates will nudge the “twin” deficits in opposite directions,
would have paid about $2 billion more in taxes in 1990. This
with the external deficit widening by a m ultiple of the
calculation, subject to several caveats,30 points to the conclu
amount that the fiscal deficit narrows.
If foreign firms achieve a more normal profit in the
sion that the shortfall in taxes paid by foreign firms is much
This prospect differs from that held out by analysts
narrower than one might guess from the shortfall in aggre
who interpret the poor profitability of foreign firms as a sign
gate income.
of tax evasion. In their view, if the foreigners can be made to
own up to their success and pay taxes, the fiscal deficit would
narrow. Higher profits would be reported because of smaller
I m p l i c a t i o n s f o r t h e T w i n D e f ic it s
Foreign firms building up their holdings in the United States
helped to finance a decade’s excess of imports over exports. As
foreign firms built up their holdings, rising payments of
profit and interest should have widened the current account
deficit. But the surprisingly low returns on those holdings
short-circuited the compounding effect whereby the cost of
The slowdown o f foreign acquisitions in the
United States in 1991 —93, coupled w ith
ongoing divestitures, points to a rebound in the
profits o f foreign firm s in the years ahead.
Chart 15
T a x e s P a id b y F o r e i g n F ir m s i n t h e U n i t e d S t a t e s
B il l io n s
o f dollars
10
payments to (or larger receipts from) foreign parents. Thus,
this scenario would imply a narrower trade deficit matching
the higher pretax profits of foreign firms here and would leave
the current account deficit initially unchanged. But as for
eign firms paid more taxes on their higher declared income,
the current account deficit would narrow by the same amount
as the fiscal deficit.
1983
84
85
86
87
88
89
90
Sources: Internal Revenue Service, Statistics of Income Bulletin, various issues;
Federal Reserve Bank of New York staff estimates.
Note: Hypothetical taxes represent revenues if foreign firms paid the same
taxes as a proportion of sales as U.S. firms in each of the following sectors:
manufacturing; wholesale and retail trade; finance, insurance, and real estate;
and all other industries.
This interpretation implies a win-win outcome on
the twin deficits. In our interpretation, by contrast, the
prospective improvement in foreign returns over time if for
eign acquisitions remain modest implies a lose-win outcome:
more borrowing from foreigners but also higher tax revenues
from foreign firms.
F R B N Y Q u a r t e r l y R e v ie w / S u m m e r-F a ll 1994
59
This article has shown how the surge in foreign acquisitions
goods, but it leaves services untouched and ultimately justi
fies investment in U.S. manufacturing.
of U.S. companies in the 1980s drove down the aggregate
We find some evidence consistent with profit shift
return on foreign direct investment in this country. Foreign
ing. Foreign firms from countries whose fiscal systems offer
ers acquired U.S. firms that barely turned a profit. These
the greatest reward for shifting profits to tax havens show
firms lost money just after acquisition and then gradually
lower profits in the United States. And firms with greater
recovered their profitability. Strong acquisition activity
opportunities to transfer profits through the pricing of
raised the share of foreign holdings at an early stage in this
imports from their U.S. affiliates show weaker profits.
C o n c l u sio n
process. Foreign firms that sold or liquidated their money-
Our interpretation suggests that the performance of
losing holdings both contributed to the restoration of profits
foreign firms in the United States will improve over the next
and provided concrete evidence of disappointing returns.
several years. The slowdown of foreign acquisitions in the
Other proposed explanations carry some weight, but
United States in 1991-93 (Chart 2), coupled with ongoing
do not bear as much as this. A weak dollar works both ways.
divestitures (Chart 10), points to a rebound in the profits of
It hurts foreign firms principally engaged in selling foreign
foreign firms.
A p p e n d ix
I:
F o r e i g n I n v e s t o r s ’ L o s s e s i n U .S . R e a l E s t a t e
Theodore Fischer and Robert N. McCauley
Much of the publicity attending the surge in foreign direct
billion in economic losses before taxes in 1990-92. The fur
investment in the United States in the 1980s focused on for
ther decline in real estate values in 1993 took cumulative
eign purchases of commercial real estate. Official data show
estimated losses to $27 billion. Thus, an industry that in
that foreign investments in the real estate sector have per
formed as poorly as those in other sectors. The Bureau of Eco
1990 accounted for 9 percent of the investment and 7 percent
of the assets of all foreign direct investment in the United
nomic Analysis (BEA) has reported that foreign-owned real
States has done significantly worse than the reported data
estate companies lost money every year after 1985, culminat
indicate (U.S. Department of Commerce, Bureau of Econom
ing in $ 10.1 billion in pretax losses in 1990-92 (U.S. Depart
ic Analysis 1992, pp. 113-14, and 1993, Table A -l).
ment of Commerce 1984-94).31
Questions have been raised about foreign firms’ use
R e a l E st at e V a l u e s
of excessive debt or transfer pricing to reduce their U.S. oper
Both domestic and foreign-owned real estate companies have
ations’ reported profits. But informed observers would agree
seen their commercial property values crash since 1989- We
that in real estate, reported losses actually understate true
can assess this decline using the Russell-NCREIF index,32 a
economic losses. The profitability of foreign real estate com
measure of real estate value. According to the capital value
panies in the BEA data reflects scheduled depreciation
portion of this index, a building bought at the end of 1985
expenses, while an economic measure of net income must
for $100 million would only have been worth $67.5 million
incorporate changes in the market value of property hold
at the end of 1993. Most of this decline occurred in the years
ings. Our estimates of market value returns confirm this
1990-93, when commercial property values fell by 31 per
hunch: foreign-owned real estate companies racked up $23
cent (Chart A l). Because real estate companies are highly
60
F R B N Y Q u a r t e r l y R e v ie w / S u m m e r -F a ll 1994
A p p e n d i x I: F o r e i g n I n v e s t o r s ’ L o sse s i n U .S . R e a l E s t a t e
(Continued)
leveraged, their return on equity was even worse. We shall
sold or in other special circumstances. As a result, foreign-
assume that the Russell index tracks the price of U.S. prop
owned real estate companies do not generally report unreal
erty held by foreigners. Even if foreign investors did no
ized gains or losses in the value of their commercial property.
worse than U.S. investors buying at the same time,33 the for
Still, the GAAP income of foreign-owned real estate showed
eigners’ timing looks unfortunate in hindsight.
considerable losses as early as 1990 (see table, column 4).
The reported losses in 1990-91 must have arisen in
A c c o u n t in g f o r C a p it a l G a in s a n d L o sse s
large part from continuing operations. W hile realized gains
Generally accepted accounting principles (GAAP) hide the
or losses are included in net income, press accounts and BEA
magnitude of the losses suffered by foreigners holding com
data suggest that foreign investors increased sales markedly
mercial property during the decline in property values from
only as late as 1992. Thus in 1990-91, high vacancies and
1990 to 1993. The GAAP balance sheets collected by the
falling rents combined to push rental income from commer
BEA as part of its annual financial surveys only require com
cial property below interest on debt and (noncash) deprecia
panies to mark commercial real estate to market when it is
tion expenses based on historic cost and GAAP. These depre-
Cbart A 1
F o re ig n O u tla y s f o r
U.S. C o m m e r c i a l R e a l E s t a t e a n d C o m m e r c i a l R e a l E s t a t e P r o p e r t y V a l u e s
I n d e x : 1980= 100
--------------- 14Q
B illio n s o f d o lla r s
12 ----------------------Other outlays
British outlays
130
10
|] Canadian outlays
!
Value o f commercial real estate
Scale
Japanese outlays
120
110
100
1980
1111 m
80
Sources: U.S. Department of Commerce, Bureau of Economic Analysis; Frank Russell Company.
Notes: Investment outlays are the amounts spent by real estate companies to acquire commercial property. Expenditures on hotels and construction are not included.
FRBNY Q u a r t e r l y R e v ie w / S u m m e r-F a ll 1994
61
A p p e n d i x I: F o r e i g n I n v e s t o r s ’ L o s s e s in
U .S.
R e a l E st a t e ( C ontinued)
ciation charges, however, depend on the book value rather
Russell-NCREIF index of the value of property (shown in
than market value of property. As bad as GAAP income was
column 1). The exercise makes the key assumption that this
in 1990-92, economic returns were worse.
index captures the market value of foreign-owned commer
cial real estate: that is., foreigners did no worse than all
investors.
E s t im a t io n o f R e t u r n s
We estimate economic returns for foreign-owned real estate
We trace the value of foreign-owned real estate com
firms, including unrealized capital gains and losses (see
panies’ investments over time. BEA data on plant, property,
table).34 The exercise combines the income and balance sheet
and equipment, of which about 90 percent reflect commer
data on real estate affiliates reported to the BEA with the
cial property, measure the amount spent on ;acquisitions and
•
Es t im a t e d N e t In c o m e a n d R e t u r n o n E q u i t y f o r Fo r e i g n - o w n e d R e a l Est a t e C o m p a n ie s
Russell Index
o f Returns in
Commercial
Real Estate
(Percent)
Total Investment
in PP&E by
Real Estate
Companies
(Billions o f Dollars)
Estimated Gains
or Losses in
Commercial Property
(Billions o f Dollars)
Published
N et Pretax
Income
(Billions o f Dollars)
Estimated
Economic
Net Pretax
Income
(Billions o f Dollars)
Published
Pretax
Return on Equity
(Percent)
Estimated
Economic Pretax
Return on Equity
(Percent)
( 1)
(2)
(3)
(4)
(5)
(6 )
(7)
1977
N .A.
6 .1 0 *
N .A.
- 0 .1 5
19 7 8
6 .8 1
1.6 0
0 .3 8
- 0 .0 8
0.25
-4 .9 0
14 .6 4
1979
19 8 0
10 .8 0
2 .1 8
0 .7 6
- 0 .0 5
2 5 .9 1
7 .1 0
0 .8 3
3 .2 9
8 .4 2
1.22
0 .1 3
0 .1 7
0 .6 3
0.2 4
- 2 .0 4
9 .1 1
8 .3 0
1.4 6
9 .5 9
0 .3 2
- 0 .4 7
2.75
- 5 .7 0
6 .6 3
1 5 .0 7
19 8 2
0 .9 1
- 0 .3 4
-3 .8 2
1983
19 8 4
5.23
5.38
8 .2 9
7 .4 4
1.47
1.87
0 .0 7
1.84
0 .6 7
1 5 .2 0
2.88
2.45
- 0 .6 0
8 .6 3
9 .5 1
0 .9 9
- 0 .2 8
6 .6 0
2 .7 1
17 .5 4
1985
1986
0 .7 6
0 .3 4
- 0 .5 7
1987
-1 .4 7
1 1 .2 0
- 0 .7 8
- 0.66
- 0 .3 6
- 4 .0 5
—4.4 8
- 0 .2 3
- 1 .4 8
19 8 8
- 0.01
9 .2 5
- 0 .0 1
- 0 .6 0
- 0.12
1989
19 9 0
- 0 .4 8
13 .3 3
14 .0 1
- 0 .3 2
- 3 .7 5
- 0.12
- 0.20
-3 .7 1
-0 .6 0
- 0 .4 9
—0.66
-1 .8 7
- 3 .2 7
-1 2 .9 2
-1 1 .9 1
-3 0 .1 8
- 11.66
-9 .9 9
- 8 .9 4
- 4 .0 7
- 9.88
- 7 .7 0
9 .9 2
6 .1 8
- 4 .9 4
- 9.00
- 2 0 .2 5
- 3 2 .1 4
- 5 .8 2
5 .0 0
4 .1 6
-4 .0 0
-4 .0 0
- 1 6 .0 0
-1 6 .3 2
19 8 1
19 9 1
19 9 2
19 93e
- 4 .9 9
-1 2 .3 4
N .A.
1.45
-0 .0 6
Cumulated using only years for which Bureau o f Economic Analysis data are available
- 1 0 .8 0
N .A.
6 .9 1
Average annual retums+
1978-92
15 .6
-1 6 .2 1
-1 1 .1 5
- 1 5 .8 4
- 5 .4 2
19 7 8 -8 8
57.8
6 .7 9
- 0 .9 6
7 .3 1
-0 .8 9
5.41
19 8 9 -9 2
-2 6 .8
- 2 3 .0 0
-1 0 .1 9
- 2 3 .1 5
-1 0 .5 1
- 1 7 .5 2
- 2 0 .3 8
-1 5 .1 5
- 1 9 .8 4
-6 .5 9
6 .7 9
- 2 7 .1 7
- 0 .9 6
7 .3 1
-0 .8 9
- 5 .5 5
5.41
-1 4 .1 9
- 2 7 .1 5
- 11.6 6
-1 7 .3 3
Cum ulated using estimated Bureau o f Economic Analysis data
19 7 8 -9 3
1978-88
8 .9
5 7 .8
198 9-9 3
- 3 1.0
- 4 .6 6
Average annual returns -
Sources: Frank Russell Company; U.S. Department o f Commerce, Bureau o f Economic Analysis; Federal Reserve Bank o f New York staff estimates.
Note: Data for 19 9 3 are all estimates except for the Russell return.
* Includes the book value o f the holdings o f PP&E (plant, property, and equipment) as o f the start o f 19 7 7 .
t W eighted by the book value o f owners' equity for the published return on equity and the market value o f owners' equity for the economic return on equity.
Digitized
62 for FRASER
FRBNY Q u a r t e r l y R e v ie w / S u m m e r-F a ll 1994
A p p e n d i x I: F o r e i g n I n v e s t o r s ’ L o sse s i n U .S . R e a l E s t a t e
(Continued)
construction by foreign-owned real estate companies (col
economic returns make the investment in the late 1980s less
umn 2) from 1977 onward. We assume these purchases occur
anomalous, our calculation leaves foreign investors with a
at market value (and that 1977 book value equals market
$27 billion loss in 1989-93, probably twice the loss that BEA
value, a fairly innocent assumption given the small scale of
will eventually report.38
foreign investment in U.S. real estate then). The value of
These results do not include commercial property
these purchases then changes in accordance with the Russell-
owned by industries other than real estate and so understate
NCREIF index. The change in value (after accounting for
the total impact of the fall in property values on foreign
sales35) is the total mark-to-market gain or loss to the real
investors. Foreign real estate companies only owned 51 per
estate companies (column 3).
cent of all foreign-owned commercial property in the United
These capital gains and losses are added to operating
States in 1991. Foreign-owned hotel firms, classified as ser
income, namely, rental revenues less operating and interest
vice firms, have the next largest share of commercial property,
expense, to calculate a measure of economic income (column
with 11 percent of the total foreign investment in U.S. real
5). Operating income is obtained by excluding depreciation
estate (U.S. Department of Commerce 1994, Table D-10). On
expenses and realized capital gains and revaluations from pre
the basis of a 31 percent decline in the Russell index in 1989-
tax net income.36 We compute the changes in the market
93, we estimate that including hotels would increase the
value of owners’ equity as the sum of increases in external cap
1989-93 losses by an additional $6 billion, to $33 billion.
ital and economic net income.37 A return on equity is then
computed as the ratio of economic income to the cumulated
market value of owners’ equity (column 7).
Chart A 2
N e t In c o m e o f Fo r e ig n -o w n e d R e a l E st a t e C o m p a n ie s
R e su l t s
B il l io n s
o f dollars
Our estimates of economic returns for foreign investors in
Estimated economic income
U.S. real estate suggest that foreign firms have done at least as
badly as they are reported to have done. In 1978-92, BEA
reports a $11.2 billion loss; we compute a $15.8 billion loss
,
*
Reported income
ftV
(columns 4 and 5).
%\
%
ft
Our calculations for the late 1970s and early 1980s
...... ..... ..... ................
help make sense of the foreign buying since then, but our
..... .
i
t
t
f
f
ft
estimates make the results of this recent buying worse. The
1
BEA data show that through the mid-1980s, net income
flu ctu ated around zero, but economic returns were
respectable if varying (Chart A2 and Table A1, columns 4 and
' ' .....
I
1977
...... 1
.........i
80
t
1
i
«
1
1
ft
*
ft
f
•
L . 1 -....1 .-.-. i _ L ___t ----- 1____I - . » 'i.___1___ 1
85
90
93
6 versus 5 and 7). And although the Russell-NCREIF returns
turn negative in 1986, our calculated returns remain better
than the reported returns because the market price declines
remain smaller than GAAP depreciation. While the earlier
Sources: U.S. Department of Commerce, Bureau of Economic Analysis;
authors’ estimates; Federal Reserve Bank of New York staff estimates.
Notes: Economic income is the sum of operating income (rental revenues less
operating and interest expenses) and calculated capital gains and losses. Data
for 1992 are preliminary; data for 1993 are partly estimated.
F R B N Y Q u a r t e r l y R e v ie w / S u m m e r -F a ll
1994
63
A p p e n d i x I: F o r e i g n I n v e s t o r s ’ L o sse s i n U.S. R e a l E s t a t e
(Continued)
Because other industries own the remaining 38 percent of
some foreigners appear to have invested more heavily in loca
commercial property, the total loss could be even higher, in
tions and types of commercial property that suffered the
the neighborhood of $50 billion.
largest declines in value.39 At the same time, despite the scale
of the losses in the United States, we make no claim that for
C o n c l u sio n
eigners’ investments turned out any worse than their invest
In losing $27 billion over 1989—93, foreign-owned real
ments in their home or third markets, since commercial
estate companies have incurred an average annual return on
property values have fallen worldwide (Bank for Internation
equity o f-17 percent. The economic loss over 1989-93 is
al Settlements 1993, pp. 155-81).
likely to be $13 billion worse than the published loss. These
are very conservative estimates.
Both BEA data and market observers indicate that
foreign investors have not liquidated their U.S. real estate
Two important factors left out of our calculation
holdings en masse. Yet in view of the price decline and lever
would only deepen the losses. From the standpoint of the for
age, many foreign investors in U.S. real estate must have lost
eign investors, what matters is the rate of return in home cur
all of their equity. In some cases, loan collateral may have
rency. The substantial leverage associated with real estate
extended beyond U.S. properties to home country property.
investment still typically leaves the equity exposed to
In other cases, banks and other creditors may have chosen to
exchange rate changes. So for investors from the Continent
restructure debt service rather than to foreclose. In the event
and Japan, dollar losses have been compounded by the
of restructurings or liquidations, the losses would have spread
declines in the dollar against the home currency. Our esti
from the equity investors examined here to creditors, includ
mates also assume that foreign-owned commercial property
ing foreign banks.40
performed no worse than the overall U.S. market. But at least
A p p e n d i x II: M u l t ip l e R e g r e s s i o n A n a l y s i s
D avid S. Laster
The analysis in the text focuses on the bivariate relationships
1977 through 1991. Data on U.S. businesses acquired or
between profitability and each of four factors: the recency of
established by foreign investors are for the years 1980
acquisition of U.S. operations, leverage, exchange rates, and
through 1992. The data are aggregates for each of the thirty-
transfer pricing. In this appendix we use multiple regression
five industry categories that together account for all nonbank
analysis to assess the impact of each of these factors while
foreign direct investment.41
holding the others constant.
The analysis uses annual data from the Bureau of
D e f i n i t io n s o f V a r i a b l e s
Economic Analysis that fall into two general categories. Data
To proxy for the m aturity of foreign holdings within an
on the operations of foreign-owned affiliates cover the years
industry, we define RECENCY for a given industry as the
Digitized
64 for FRASER
F R B N Y Q u a r t e r l y R e v ie w / S u m m e r -F a ll 1994
A p p e n d i x II: M u l t i p l e R e g r e s s i o n A n a l y s i s
(Continued)
assets of affiliates acquired or established in the current year
define M*E - (MPAR + MOTH)*E, and X*E = (XPAR +
or previous two years in that industry, divided by assets of all
XOTH)*E, where E is the de-meaned natural logarithm of
affiliates currently in the industry. To measure the effect of
the trade-weighted dollar, as measured by the Board of Gov
leverage, the debt ratio LEV (total liabilities divided by
ernors of the Federal Reserve System. Our expectation that an
assets) is used. Two variables capture the effect of transfer
appreciation of the dollar will benefit importers and harm
pricing. MPAR is the ratio of imports from foreign parent
exporters means that the coefficients of M*E and of X*E
corporation to sales; XPAR is the ratio of exports to foreign
should be positive and negative, respectively.
parent corporation to sales. To control for any impact that
trade activity, per se, has on profitability, we include two
S u m m a r y S t a t ist ic s
additional variables. MOTH is imports from other parties
Table B1 provides sample means for the dependent and
divided by total sales; XOTH is exports to other parties
explanatory variables used in the analysis, in aggregate and
divided by sales.42 While we have no expectations concerning
by major sector.45 In aggregate, the profitability measures
the signs of the coefficients of MOTH and XOTH, we expect
were strongest during the first five years of the sample, 1977-
for reasons discussed above that RECENCY, LEV, MPAR,
81; they were weakest in 1990 and 1991. Note that the aver
and XPAR will all have negative coefficients.
age affiliate debt ratio (LEV), steady from 1977 to 1984,
The exchange rate is the most difficult factor to
increased by 8 full percentage points from 1984 to 1991.
model because it has widely diverse impacts on different
industries. We assume, as a first approximation, that the sen
R e g r e s s io n A n a l y s is
sitivity of an affiliate’s profits to exchange rates is a linear
A series of twelve pooled regressions were run to test the
function of its import and export exposure. In particular, we
impact of each of the factors discussed above on affiliate
Table El
C h a r a c t e r i s t i c s o f F o r e i g n F i r m s in t h e U n i t e d S t a t e s , 1 9 7 7 - 9 1
Sample Means for A ll Industries
Annual Averages
Average
1981 -
19 7 7
19 7 8
ROA (percent) 2 .9 4
2.83
3 .5 0
ROS (percent)
RECENCY
LEV
MOTH
2 .7 9
N.A.
0 .6 5 9
0 .0 2 4
N.A.
19 8 1
19 8 2
19 8 3
19 8 4
1985
19 8 6
19 8 7
19 8 8
19 8 9
2.22
2 .8 0
- 0.02
1.3 1
1.83
0 .9 6
2.33
1.8 1
0 .9 8
2 .6 3
0 .5 1
0 .1 8
1.2 4
2 .2 7
0 .8 1
0.20
N .A.
1.3 1
0 .2 2 4
1.7 9
0 .2 8 0
0 .6 7 9
0.690
0 .0 3 5
19 7 9
1980
3 .1 4
3 .31
N.A.
0 .0 6 8
0 .6 7 8
0 .0 4 1
0 .0 6 6
0 .3 4 3
0 .6 6 5
0 .0 5 4
0 .6 7 2
0 .6 7 6
0 .2 9 9
0 .2 12
0 .121
0 .6 7 3
0 .6 5 5
0 .0 3 4
0 .6 5 6
0 .1 2 9
0 .6 6 7
0 .0 4 1
0 .0 3 7
0 .1 9 2
0 .6 7 7
0 .0 3 6
1990
1991
1.12
0 .16
- 0.66
1.05
1.2 6
- 0 .2 4
-1 .3 4
0 .8 5
0 .2 4 8
0.222
0 .7 3 5
0 .1 5 7
0 .7 3 8
0.22
0 .7 1 0
0 .0 3 6
0 .0 3 5
0.036
0 .0 3 7
0 .0 3 2
0 .0 4 7
0 .0 4 6
0 .0 4 8
0 .085
0 .0 8 3
0.05
0 .0 8 2
0 .0 4
0 .085
0.022
- 0 .16
0.022
0.021
- 0.20
0 .0 2 4
0.02
0.00
XOTH
0.038
0.032
0.036
0 .0 4 4
0 .0 4 7
0 .0 6 9
0 .0 4 2
0 .0 4 1
0 .0 3 8
0 .0 3 3
M PAR
0 .1 2 3
0 .0 7 7
0 .0 9 4
0.060
0 .0 5 6
0 .0 6 9
0 .0 6 7
0 .0 8 4
0 .085
0.0 3
0 .0 9 2
X PA R
0.022
0 .0 2 4
0 .0 2 4
0 .0 2 4
0.022
0 .0 2 3
0.020
0.021
0 .0 1 8
E
- 0 .0 5
- 0 .16
- 0.21
- 0.21
- 0 .0 5
0 .0 7
0 .15
0 .0 2 3
0 .2 4
0 .0 8 9
0 .0 1 7
0.2 8
0 .0 4
- 0 .11
- 0 .0 9
-0 .1 9
19 9 1
0 .6 9
0 .0 4
0 .0 8
Sources: U.S. Department o f Commerce, Bureau o f Economic Analysis; Board o f Governors o f the Federal Reserve System.
Notes: Statistics represent an average o f measures for component industries, weighted by the 19 8 7 gross product o f affiliates. RO A = net income/assets; ROS = net
income/sales; RECENCY = assets o f U.S. affiliates acquired or established in the current year or previous two years/assets o f all U.S. affiliates; LEV = (current liabilities +
long-term debt)/ assets; MOTH = imports excluding those from foreign parent/sales; XOTH = exports excuding those to foreign parents/sales; M PAR = imports from
foreign parent/sales; X PA R = exports to foreign parent/sales; E = de-meaned log o f trade-weighted dollar. Fluctuations in average values o f MOTH and M PAR reflect
changes in the set o f industries for which the variables’ values are available. N. A. = not available.
FRBNY Q
u a r t e r l y R e v ie w / S u m m e r-F a ll
1994
65
A p p e n d i x II: M u l t i p l e R e g r e s s i o n A n a l y s i s
(Continued)
profitability. Two dependent variables were used: return on
Its estimated coefficient in aggregate equation 1, -.0 8 1 ,
assets and return on sales. Each regression was run for the
means that each additional dollar of debt on an affiliate’s
entire sample of thirty-five industries, for the nineteen manu
books reduces its profits by 8.1 cents, consistent with a plau
facturing industries, and for the five wholesale trade indus
sible 8.1 percent rate of interest. The corresponding coeffi
tries.44 The regressions were run using weighted least
cient for manufacturing, —.048, while smaller, is still within
squares. Each observation, representing the performance of
a standard error of a credible value; the coefficient for whole
affiliates in a given industry, had a weight proportional to the
sale trade, -.163, seems too large. Equations 2, 4, and 6 sug
1987 gross product of affiliates in that industry. To control for
gest that the variable is better at explaining differences in
variations in macroeconomic conditions over the sample peri
profitability across industries than at explaining variations in
od, year dummies were employed in each regression. Finally,
the profitability of a given industry over time. The reason
each specification was run with and without industry dum
could be that leverage ratios vary less within a given industry
mies. When industry dummies are omitted, the regression
than across industries.
explains variations in profitability across industries. When
industry dummies are included, the regression explains varia
Ex c h a n g e R ates
tions in profitability within each industry over time.
Because transfer pricing and exchange rate effects are transac-
The regression results are reported in Table B2.
tions-based, the discussion concerning them focuses on the
Because RECENCY and LEV are asset-based measures, their
return on sales regressions 7-12. Five of these six regressions
performance can best be discussed in the context of return on
satisfy our expectation that the coefficients of M*E would be
assets regressions 1-6.
positive and those of X*E negative. X*E is most significant
in the “all industries” regression; M*E is most significant for
R ecen cy of A cq uisitio n of
U.S. O perations
A s predicted, RECENCY has a negative coefficient in all six
wholesale trade.
To interpret the magnitude of the parameter esti
return on assets regressions; in five of these regressions, the
mates, imagine two affiliates—one a “pure exporter,” the
estimated coefficient is significant at the 5 percent level. The
other a “pure importer.” The pure exporter sells all of its out
coefficient of the first equation, —.058, implies that the differ
put abroad; the pure importer has imports equal to sales.
ence in the return on assets of an industry whose affiliates
Were the dollar to depreciate by 10 percent, the pure exporter
have been purchased or established in the past three years and
would benefit. If the exporter held its export prices fixed in
another all of whose affiliates have been operating under cur
foreign currency terms, its profit margin would rise by 10
rent ownership for three or more years would be 5.8 per
percentage points. The estimated coefficient for X*E in
cent.45 While of a similar magnitude for each sector, the esti
equation 7 states that the pure exporter’s profit margin actu
mated effect has greatest sta tistic a l sign ificance for
ally rises by less, by 5.6 percentage points.
manufacturing affiliates.
The pure importer, by contrast, would be harmed by
a 10 percent dollar depreciation because it would raise the
L everage
price of its inputs, all of which are imported. In addition to
In specifications without industry dummies, the leverage
any compression of profit margins by exporters to the United
variable LEV is negative and significant at the 5 percent level.
States, our estimate of M*E in equation 7 implies that the
66
F R B N Y Q u a r t e r l y R e v ie w / S u m m e r -F a ll 1994
A p p e n d i x II: M u l t i p l e R e g r e s s i o n A n a l y s i s
(Continued)
pure importer’s contemporaneous profit m argin would
dummies are not used, the variable MPAR is significantly
decline by 1.2 percent.
negative at the 1 percent level for all industries and for manu
facturing. Thus, reported profits are lowest for industries in
T r a n sf e r P r ic in g
which affiliates have the greatest opportunity to transfer
Of the two proxies for transfer pricing, the variable XPAR
price. Equation 7 associates each additional dollar of imports
fails to be significant in every specification, suggesting that
from the foreign parent with profits that are 6.7 cents lower.
affiliates do not extensively manipulate transfer prices when
This effect is more pronounced in manufacturing (30 cents),
exporting. Imports are a different story. When industry
and virtually nil in wholesale trade.
TabIt B2
P r o f i t a b i l i t y o f F o r e i g n F i r m s in t h e U n it e d S t a t e s b y I n d u s t r y : 1 9 8 1 - 9 1
Regression Results
Return on Assets
A ll Industries
Explanatory
Variables
RECENCY
LEV
X*E
MOTH
XOTH
M PAR
-0 .0 5 8 * *
- 0 .0 3 3 * *
(0.0 0 9 )
(0 .0 0 9 )
- 0 .0 8 1 * *
0 .3 3 1* *
(0.0 7 8 )
Adjusted R-squared
F-statistic
(0 .0 19 )
0 .3 2 4 * *
(0.066)
- 0 .4 5 0 * *
(0 .17 3 )
(0 .15 2 )
All Industries
Manufacturing
0 .1 5 4 * *
- 0 .0 3 9 * *
( 0 .0 1 1 )
-0 .0 4 3 * *
(0 .0 1 2 )
- 0 .0 7 8 *
(0.0 56)
--0 : )6 1 -*
(0 .0 1 0 )
- 0 .0 2 5 *
(0 .0 1 0 )
- 0 .0 3 6 **
(0 .038 )
- 0 .0 4 8 *
0 .0 0 5
- 0 .1 6 3 * *
(0 .0 2 6 )
(0.033)
—0.0 6 3 * *
(0 .017 )
- 0.020
(0 .0 2 1 )
- 0 .1 1 3 *
(0 .04 4)
-0 .0 5 9 * *
(0 .0 2 1 )
- 0 .2 10
(0.268)
0 .0 5 2
(0.257)
0 .5 15 * *
(0.089)
- 0 .0 6 8
- 0 .5 1 2
- 0 .0 0 4
(0.333)
(0.320)
(0 . 12 2 )
0 .2 2 1 **
0 .0 4 2
0 .0 9 7
0 .0 4 4
(0.045)
(0 .0 5 8 )
(0.0 6 3 )
(0.0 7 3 )
(0.055)
- 0 .0 6 4
- 0 .0 9 3
(0 .0 8 6 )
-0 .0 3 3
(0.062)
- 0 .2 5 0
(0 .12 8 )
- 0 .0 4 1
(0.049)
-0 .0 5 2 * *
-0 .0 0 7
- 0 .3 1 2 * *
- 0 .0 5 4
-0 .0 3 5
(0.089)
N um ber o f observations
- 0 .0 3 6
- 0 .3 9 8 *
(0 .0 17 )
XPAR
Return on Sales
Wholesale Trade
Wholesale Trade
No Industry Industry No Industry Industry No Industry Industry No Industry Industry No Industry Industry No Industry Industry
Dummies Dummies Dummies Dummies Dummies Dummies Dummies Dummies Dummies Dummies Dummies Dummies
( 10 )
(2 )
(4)
(5)
(6 )
(7)
(8 )
( 12 )
(3)
(9)
(1 )
(1 1 )
(0 .0 14 )
M*E
Manufacturing
(0.049)
(0.053)
0 .0 5 0
0 .2 2 4
(0 .14 0 )
(0 .17 3 )
(0.0 8 4 )
- 0 .4 3 2
(0.280)
- 0 .0 5 6
0 .5 0 9 * *
(0 .091)
-0 .0 7 7
‘!U 33>
0 .3 0 9 * *
os)
mi.;
(0.063)
-0 .0 1 6
(0.098)
0 .0 1 5
-0 .0 8 7
(0 .0 3 1)
(0.054)
0 .0 9 0
0 .1 5 1
(0.087)
(0 .1 1 3 )
(0 .0 2 2 )
0 .1 1 6
0 .1 3 8
(0.094)
(0.0 73)
io 5
- 0 .5 7 0 * *
(0 .0 1 1 )
- 0 .1 2 8
(0.259)
- 0 .1 0 8
- 0 .0 3 5 * *
(0 .0 1 1 )
- 0 .0 2 3
(0 .0 14 )
-0 .0 1 3
- 0 .0 0 8
- 0 .0 5 1 * *
(0 .0 1 2 )
- 0 .0 3 5 *
(0.025)
0 .1 7 6
(0.2 42)
- 0 .6 5 2 *
0 .1 4 5 * *
(0 .0 3 1)
-0 .0 0 7
(0 .0 19 )
(0 .0 15 )
0 .1 4 4 * *
(0.0 32)
- 0 .0 2 3
(0 .04 6)
|§|jg ‘
(0 .16 9 )
0 .15 3 * *
(0.054)
0 .0 4 3
0 .0 9 0
0 .0 4 0
(0.065)
(0 .0 6 1)
(0.0 69)
(0 .0 19 )
(0 .03 7)
- 0 .1 0 5
(0.096)
0.012
(0.0 59)
- 0 .2 5 8 *
(0 . 12 0 )
- 0.012
(0 .02 2 )
- 0 .0 1 5
(0 .03 4)
- 0 .0 2 7
(0.0 54)
-0 .3 0 0 * *
-0 .0 6 7
(0.0 79)
0 .0 0 7
(0 .0 1 1 )
- 0 .0 2 8
(0 .0 5 1)
0 ,0 4 7
0 .2 4 2
(0 .15 6 )
(0 .16 7 )
0 .0 3 0
(0.059)
- 0 .0 3 6
(0 .10 7 )
(0 .3 2 1)
(0.302)
- 0 .3 8 4
(0.2 64)
(0.0 43)
0 .0 9 6 * *
0 .1 4 1 * *
(0 .0 19 )
0 .0 2 8
0 .0 3 8
(0 .0 3 1)
(0.039)
327
327
202
202
51
'
327
327
202
202
51
51
0.32
0 .6 0
0.3 4
0 .5 8
0 .9 1
0.93
0.23
0 .5 8
0 .3 3
0.60
0.90
0.9 2
15 .1 * *
5.6**
10 .4 * *
2 .4 *
4 4 .5 * *
19.5* *
9 9 **
2.7**
10 .2 **
2.4*
38.0* *
15.5* *
Sources: U.S. Department o f Commmerce, Bureau o f Economic Analysis; Board o f Governors o f the Federal Reserve System.
Notes: Return on assets = net income/assets; return on sales = net income/sales; RECENCY = assets o f U.S. affiliates acquired or established in the current year or
previous two years/assets o f all U.S. affiliates; LEV = total liabilities/assets; M*E = (total imports/sales) *E, where E is the de-meaned log o f the trade-weighted dollar;
X*E = (total exports/sales) *E; MOTH = imports excluding those from foreign parent/sales; XOTH = exports excluding those to foreign parent/sales; M PAR = imports
from foreign parent/sales; X P A R = exports to foreign parent/sales. Observations are weighted by 19 8 7 gross product o f U.S. affiliates. Standard errors are in parentheses.
Constant term, industry dummies, and year dummies are not reported. Banking affiliates are excluded from the data. The F-statistic is a joint test o f the significance of
the eight explanatory variables listed in the table.
*Significant at 5 percent level.
**Significant at 1 percent level.
F R B N Y Q u a r t e r l y R e v ie w / S u m m e r -F a ll 1994
67
A p p e n d i x II: M u l t i p l e R e g r e s s i o n A n a l y s i s
{Continued)
C o n c l u sio n
together with the dollar, while exporters’ profits move
To summarize, the regression results closely conform to
against it. And while exports to foreign parents prove
expectations. Recent acquisition activity and high leverage
insignificant, affiliates importing the most from their parent
are associated with low profits. Importers’ profits move
companies report the lowest profits.
F R B N Y Q u a r t e r l y R e v ie w / S u m m e r -F a ll 1994
68
En dn otes
1. Figures cited in paragraph are from Zeile (1 9 9 4 , p. 154), and U.S.
Note 8 continued
Department of Commerce (1993 Appendix D, Tables 1 6 ,1 7 , 32, 33).
between “foreign-controlled” and “other domestic” firms in the finance,
2. Fahim-Nader 19 9 4 , p. 50. “Acquisitions” and “establishments” in the
within the sector. Second, focusing on the sector in which foreign firms
insurance, and real estate sector, owing to differences in composition
Bureau o f Economic Analysis data do not exactly correspond to purchases
were most profitable in 19 9 0 minimizes the possibility o f mistaking a
o f existing assets and greenfield investment, respectively. Many greenfield
general decline in corporate profits for evidence o f post-acquisition costs.
investments proceed within firms already operating here. The Japanese
Indeed, foreign manufacturers were more profitable in 19 9 0 than in 19 8 6 -
automotive companies, for example, have built up their manufacturing
89, so the estimate o f more than $4 billion for the post-acquisition decline
capacity within extant sales operations. Conversely, establishments can
in manufacturing profits is, if anything, understated. Data on the prof
own preexisting assets. For example, a new partnership can hold an existing
itability o f firms in the year before acquisition are from U.S. Department
office building.
o f Commerce (19 9 3 ) Appendix D, Tables 16, 17, 32, 33. The Internal
Revenue Service data on firms recently incorporated differ slightly from
3. From a regression for 19 7 9 -9 1 that does not control for interest rates or
the Commerce Department figures. The Internal Revenue Service data
economic growth, Klein and Rosengren (1994, p. 382), report a slightly
include newly established firms, but these are small relative to newly
smaller elasticity of 1.56. Using International Trade Administration data
acquired firms. In particular, for the years 19 8 7 -9 0 , foreign firms that
for 19 7 7 -8 6 , Caves (1989) derives similar results for relative equity prices.
were newly established generated in their first year o f operation only about
His measure is significant for only some specifications. Given the strong
a twentieth as many sales as did newly acquired firms in the year before
trend of stock prices and acquisitions from Japan, it is not surprising that
they were bought. Note also that some newly acquired firms do not get re
without Japan, the R2 in our regression falls from .55 to .41. W hile foreign
incorporated.
and domestic equity prices retain their respective signs, the significance of
foreign equity price declines to the .08 level and the significance o f U.S.
9. Manufacturers incorporated 19 8 7 -9 0 reported assets o f $ 1 0 9 billion on
equity prices is lost. The last wave of the British acquisitions in the late
their 19 9 0 tax returns; $ 1 0 9 billion x 10 .9 percent x 8 percent interest rate
1980s is hard to reconcile with the cost of equity explanation (McCauley
yields $0.95 billion.
andEldridge 1990).
10. Grubert, Goodspeed, and Swenson (19 9 3 , p. 2 5 1) reach a different
4. This measure is only indicative since outlays that are financed with debt
to unaffiliated parties do not become part of the ownership stake.
conclusion: “The date of incorporation variables reflect asset revaluations
rather than operating start-up losses.” Curiously, these authors later
(p. 258) embrace a “m aturation” effect as showing improved operating
5. Note that profitability is measured as a return on sales rather than on
results over time. Note that the 19 8 6 Tax Act removed much of the oppor
assets to eliminate the effect o f asset revaluations in an acquisition.
tunity for acquirers o f firms to step up the value of assets for the purpose of
taking larger depreciation expenses.
6. Fahim-Nader (19 9 4 , p. 58) provides return on sales data for foreign
acquisitions in 19 8 7 -9 3 . Chart 6 focuses on 19 8 7 -8 9 to avoid any distor
11. The reporter explained that “development spending for new products
tions owing to recession. The consistency o f the underperformance o f tar
soared partly because Coca-Cola, in anticipation of a sale of the studios, had
gets o f foreign acquisitions in the BEA data makes it odd that a sample of
sharply curtailed production, and the new owners were left with only a
1 1 8 acquisitions showed no difference in profit between acquisition targets
handful of projects.” An unnamed source was cited as saying that “operat
and nonfinancial firms on Compustat (Grubert, Goodspeed, and Swenson
ing profits never exceeded a hundred million dollars,” and that figure did
1993, p. 256). “The inconsistency may be due to differences in sample size
not include the debt incurred in buying the studios for “the official price of
and coverage, to purchases of parts or divisions o f a company, rather than
$3.4 billion,” or “closer to six billion, considering all the collateral costs”
the whole firm, and other differences” (Grubert 1993, p. 93). To the factors
(Stewart 19 94, pp. 48, 51).
cited may be added the possibility that the universe o f Compustat nonfi
nancial firms may not offer an appropriate basis of comparison.
12. Canada was the exception, suggesting that geographic, linguistic, and
cultural distance matters (Lupo, G ilbert, and Liliestedt, 1978). Year of
7. Swenson (1 9 9 3 , pp. 255-84) finds that price-earnings ratios o f foreign
incorporation is a noisy proxy for age because new operations can be
targets are 19 percent higher than those o f domestic targets.
absorbed into, or made a subsidiary of, long-standing operations without a
new incorporation. Long-standing operations can be reorganized and
8. This discussion confines itself to manufacturing for two reasons. First,
freshly incorporated.
doing so avoids the question o f the com parability o f interest expense
N otes
F R B N Y Q u a r t e r l y R e v ie w / S u m m e r -F a ll 1994
69
E n d n o t e s (<Continued)
13- See Grubert, Goodspeed, and Swenson (1993, p. 256). The results are
Note 2 0 continued
not comparable since the firms in the fixed sample that were recently
International staffing increased from approximately two hundred interna
acquired in 19 8 0 would have benefited from the General Utilities step-up
tional examiners in 19 8 0 to almost five hundred positions in 1 9 8 7 ” (State
of assets for tax depreciation.
ments of Rep. David E. Bonier and Patrick G. Heck, Assistant Counsel,
ibid., p. 54.
14. The time that elapses between an acquisition and the sale or liquida
tion that stems from a recognition o f its failure (perhaps after a manage
2 1. Foreign firms might also have other incentives for shifting income
ment change) suggests that the (smaller) number of employees some years
from the United States. Managers’ performance could, for example, be
before the divestment would be a more appropriate denominator. Our
evaluated more on the basis o f home market results than on the perfor
attrition rate is therefore a conservative measure.
mance o f foreign subsidiaries. Or firms might decide that it is in their ulti
15. Note that these data also include manufacturing results for Japanese
Treasury.
mate self-interest to pay taxes to local tax authorities rather than to the U.S.
automotive firms whose primary activity was in wholesale trade.
22. Statements o f Fred T. Goldberg, Commissioner o f Internal Revenue,
16. Knetter (1994) recognizes that these studies overlook the fact that the
and Charles S. Triplett, IRS Deputy Assistant Chief Counsel (U.S. Con
U.S. importer is an affiliate of the foreign exporter. Ragnan and Lawrence
gress, House Committee on Ways and Means, 19 9 0 , pp. 78 and 104).
(1993) represent an exception on the export side; they find that although
dollar export prices respond little to the dollar’s exchange rate, U.S. m ulti
23- In Britain, the integration of corporate and individual taxation allows
nationals’ foreign affiliates do vary margins in response to exchange rate
shareholders a tax credit for corporate income taxes paid to the Inland
changes.
Revenue on income earned in Britain. But many multinationals based in
17. By contrast, Grubert, Goodspeed, and Swenson (1 9 9 3 , pp. 256-7)
They therefore must pay additional advance corporation tax on dividends
force the profitability of all of wholesale trade and all o f manufacturing to
paid.
Britain lack sufficient British earnings and thus British income taxes paid.
respond in the same manner to the dollars value and find a positive relation
for wholesale trade and no relation for manufacturing. See Appendix II for a
24. But see Hufbauer and Van Rooij (1992, p. 132) for the view that major
regression design that tests the interaction o f the dollar’s exchange rate
countries other than the United States de facto tax on the territorial principle.
with each industry’s net imports.
25. The 1992 loss for the credit countries reflects a loss of $3 .4 billion by
18. Offsetting this general relation to some extent is the greater import
Canadian manufacturers in 19 9 2 , compared with a profit of $ 1.5 billion in
propensity of foreign-owned manufacturing firms (Graham and Krugman
19 9 1. This swing is entirely explained by DuPont, in which the Canadian
19 9 1, pp. 67-70).
firm Seagram’s holds a 24 .4 percent stake. DuPont swung from a $ 1 .4 bil
lion profit in 19 9 1 to a $3-9 billion loss in 19 92 owing to $4.8 billion in
19- This test does not preclude the opportunity for foreign firms to be
accounting charges for post-retirement medical benefits and for higher
more leveraged at home, and therefore in the United States, than are U.S.
deferred taxes (Moody’s 19 9 4 , pp. 1 1 2 6 ,4 1 8 5 ).
firms. Moreover, note that if U.S. assets are accounted at closer to market
value than are global assets because they are recently acquired, then even
26. Grubert, Goodspeed, and Swenson (19 9 3 , pp. 252-53) find no relation
this standard permits effectively higher leverage in the United States than
between affiliate profitability and total purchases from other firms (which
in the consolidated global firm.
at best proxies intrafirm transactions only crudely). W hen the relationship
between reported profits and exports to parents was tested, no correlation
20. “IRS efforts in the transfer pricing area are o f relatively recent vintage,
was found.
as they relate to FCCs [foreign-controlled corporations}” (IRS Commis
sioner Fred T. Goldberg, cited in U.S. Congress, Committee on Ways and
27. Recency of acquisition might also play a role. New affiliates are both
Means, 19 90, p. 203). The international staffing at IRS can be interpreted
less profitable and more reliant on intrafirm imports than are old affiliates.
in various ways: “W hile the number of foreign-owned subsidiaries in this
Accordingly, the multivariate regression controls for recency of acquisition
country has soared in the last decade, the number of international examin
as well.
ers at IRS has remained flat, between 4 0 0 and 500, for the last four years.”
Cfi: “The number o f foreign-owned corporate income tax returns filed
28. A similar calculation may have generated the estimate o f the tax rev
increased from twenty thousand in 19 8 0 to forty-five thousand in 1987.
enues to be raised by “preventing] tax avoidance by foreign corporations”:
F R B N Y Q u a r t e r l y R e v ie w / S u m m e r -F a ll 1994
70
N otes
E n d n o t e s (<Continued)
Note 2 8 continued
34. See Theodore Fischer, “Foreign Investors’ Losses in Real Estate:
$9-0 billion in 19 93, $ 1 1 .0 billion in 1994, $ 11.5 billion in 19 9 5 , and
A Methodological N ote,” Federal Reserve Bank o f New York working
$ 13 .5 billion in 19 9 6 (Clinton 19 92, p. 22).
paper, for details on the estimation.
\
29- The comparable figure for other U.S. firms was 47 percent in 19 9 0
3 5. The sales data do not include the property o f companies that are liqui
(Hobbs 19 93, p. 131).
dated or pass out o f foreign ownership, events akin to sales. The value of
property, plant, and equipment of real estate affiliates that ceased to exist is
30. The Internal Revenue Service data on which the calculation is based do
reported in a residual category labeled “restatements.” The value of liqui
not include any adjustments resulting from audits. The comparability of
dated or sold firms’ property could be as high as $2 billion and $5 billion in
the activities o f foreign and domestic firms in wholesale trade has been
19 9 1 and 19 9 2 , respectively, as opposed to the sales o f $4.5 billion and
questioned owing to the high import intensity of, and relatively low value
$2.9 billion, respectively, for which we have accounted. Because such liqui
added by, foreign firms (KM PG Peat Marwick 1994, p. 9). Offsetting this
dations naturally occurred after most of the real estate price decline, includ
bias is the failure of the calculation for manufacturing to account for the
ing them in our estimates would decrease estimated 19 92-9 3 losses by no
long-noted heavy mix o f more profitable, more research-and-development-
more than $0 .6 billion.
intensive industries among foreign firms here.
36. Depreciation is excluded from operating income since the Russell
31. Unless otherwise noted, “real estate” includes foreign affiliates princi
index captures the drop in assessed value if needed capital improvements
pally engaged in development and management of property. It excludes
are not made, or their cost if they are made. Estimated realized capital gains
hotels, which are grouped into services in the foreign direct investment
and revaluations are excluded from operating income as it is used here since
data gathered by the Bureau o f Economic Analysis (BEA). This appendix
they are already accounted for in our measure o f capital gains based on the
also excludes from the analysis commercial property owned by other kinds
Russell index.
of industries such as manufacturers, oil companies, or banks, as well as resi
dential property used for personal purposes. The BEA also computes
37. Because consistent information is not available on the size o f divi
income data in an annual analysis o f the balance of payments (BOP) flows
dends, they are assumed to be zero. External capital infusions are obtained
caused by foreign direct investment. The balance of payments income
by taking the annual change in the BEA published value for owners’ equity
includes that part of the operations net income that is earned by the foreign
and excluding an estimated change in retained earnings o f all affiliates
parent as well as net interest paid on intercompany debt. In 1 9 9 0 -9 2 , the
(including unincorporated ones).
BOP data show losses o f $3 .8 billion (U.S. Department o f Commerce,
1993a, p. 86). This number is smaller than the sum of the income reported
38. W e have projected that next year, BEA w ill report $2 .4 billion for
in operations data because the foreign parents owned only 75 percent of
19 93 depreciation. The gap w ill be wider if this estimate proves too large.
their real estate affiliates and were owed interest on a net debt of $ 17 billion
in 19 9 1. Despite these differences, the general results of this appendix also
39. In its report 19 93 Japanese Disinvestment in U.S. Real Estate, Kenneth
apply to the BOP concept of income.
Leventhal & Company indicates that the Japanese investors put 50 percent
32. The Russell capital index tracks the assessed market value o f unlever
percent of the Russell-NCREIF index (hotels only make up a very small
aged property only, while the total index also includes rental income and
part o f the Russell index). The Russell office index declined by 36.2 per
operating costs. The capital index measures the change in appraised value
cent over 19 9 0 -9 2 , while the overall index declined by only 26.7 percent.
of their nonhotel investments into offices, while offices constitute only 32
less the cost of any capital improvements; it excludes the depreciation of
However, there is no information on the sectoral distribution of all foreign-
book values. Giliberto terms the index “the most widely used performance
owned real estate.
measure for real estate.” See Giliberto 19 94, p. 55, for the formula.
40. Losses on U.S. real estate can appear in odd places. In 19 93, Long Term
33. Because most domestic real estate companies are privately owned,
Credit Bank’s Australian subsidiary reportedly made a A $ 45 million provi
little data are available on their financial performance. Until quite recently,
sion against a loan to the U.S. subsidiary of EIE Limited, a troubled Japan
exchange-traded real estate investment trusts remained a small and proba
ese real estate company that financed a New York hotel (“No Relief from
bly unrepresentative proxy for real estate values. Moreover, like closed-end
Bad Debts in Australia,” Asia Money, July-August 19 9 4 , p. 25).
funds, such trusts trade at values that bear a varying relation to underlying
asset values. A direct comparison between domestic and foreign real estate
4 1. Our thirty-five industries are: petroleum; food and kindred products;
companies is therefore not attempted.
industrial chemicals and synthetics; drugs; soap, cleaners, and toilet goods;
N otes
FRBNY Q u a r t e r l y R e v ie w / S u m m e r-F a ll 1994
71
E n d n o t e s 0 Continued')
Note 4 1 continued
Note 4 2 continued
other chemicals; primary metal industries; fabricated metal products;
M*E and X*E.
machinery, except electrical; electric and electronic equipment; textile
products and apparel; lumber, wood, furniture, and fixtures; paper and
43. To be consistent w ith the regression estimates, these averages are
allied products; printing and publishing; rubber and miscellaneous plas
weighted by the 1987 affiliate gross product of each industry.
tics products; stone, clay, and glass products; transportation equipment;
instruments and related products; other manufacturing; motor vehicles
44. Since six o f the explanatory variables used in the regression are trade-
and equipment wholesale trade; metals and minerals wholesale trade; other
related, and the finance sector is virtually uninvolved in trade, efforts to
durable goods wholesale trade; farm-product raw materials wholesale
apply the analysis to that sector yield few results and are therefore not
trade; other nondurable goods wholesale trade; food stores; other retail
reported.
trade; finance, except banking; insurance; real estate; services; agriculture,
forestry, and fishing; mining; construction; transportation; and communi
45. This estimate is much larger than the 2.2 percent gap implied by IRS
cation and public utilities. The Bureau of Economic Analysis, for reasons of
data. In 19 90, affiliates incorporated within the three previous years earned
confidentiality, suppresses data for some industries in certain years. Thus,
a return on assets o f- 1 .7 percent, while those incorporated more than three
our “all industries” regressions have 327 observations o f a possible 385 for
years earlier earned 0.5 percent. One reason for the discrepancy is that year
the eleven-year sample period. The regressions are run on the observations
o f incorporation is an unreliable indicator o f the true age o f a corporation.
available.
Thus, some newly acquired affiliates are misclassified as more mature ones
and vice versa, downwardly biasing the gap between new and old affiliates.
42. A second reason for including these variables is that they, together
For further discussion, see Hobbs 19 9 3 , pp. 13 2-34 .
with MPAR and XPAR, serve as slope dummies for the interaction terms
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Digitized
N otes for FRASER
FRBNY Q u a r t e r l y R e v ie w / S u m m e r -F a ll 1994
75
The Baby Boom Generation and
Aggregate Savings
Richard Cantor and Andrew Yuengert
uring the 1970s, household and national sav
should rise with age, the impact on the aggregate saving rate
ings rates fe ll sharply. A lth o u g h concern
w ill be mitigated by a continuing high rate o f early retire
about low saving rates remains widespread,
ment and a rising share o f households headed by individuals
many analysts have taken the optimistic po
either over sixty-five or under thirty-five— households that
D
sition that the maturing o f the baby boom generation w ill
restore aggregate savings to their earlier levels. Two argu
ments have been offered in support o f this view:
tend to have relatively low saving rates.
The second argument, which stems from the popu
lar notion o f baby boomer improvidence, is also flawed. Baby
• As baby boomers reach their peak earning and
boomers appear to have accumulated appreciable w ealth,
saving years, aggregate savings w ill increase with
both in comparison to their parents at similar ages and to tar
this large generation’s rising share o f national
get retirement wealth levels suggested by theoretical models
income.
o f optimal lifetime savings. Moreover, even if baby boomers
• Baby boomers who spent freely and saved little as
eventually find themselves behind schedule in saving for
young adults w ill in their middle years find them
their retirem ent (if not because o f their shortsightedness,
selves unprepared for retirem ent. They w ill re
then because o f a large cut in Social Security benefits), they
spond by increasing their saving rates more ag
may react to the shortfall by reducing planned bequests or
gressively than earlier generations at a similar age. 1
taking other steps that do not have the effect o f increasing
This article evaluates each argum ent in turn and
aggregate saving rates. The uncertainty o f the baby boom
finds little reason to expect a large increase in aggregate sav
response to any savings shortfall gives us even less reason to
ings. The demographic effects alleged in the first argument
expect a surge in aggregate savings as the baby boomers
w ill probably be small. W h ile baby boomers’ saving rates
approach retirement.
Digitized76for FRASER
FRBNY Q u a r t e r l y
R e v i e w /S u m m e r -F a l l
1994
L if e - C y c l e S a v i n g s , D e m o g r a p h i c
incomes and saving rates tend to rise with the age of the
T r e n d s, a n d A g g r e g a t e S a v in g s
household head before retirement. The 1983 survey contains
extensive data on the wealth of individual households as of
If baby boomers raise their saving rates in line with increases
observed in earlier generations at similar ages, will the aggre
gate saving rate recover sharply? To answer this question, we
year-end 1982. In 1986, 2822 households from the original
group were surveyed again and asked for detailed information
review the age profile of income and savings found in recent
on year-end 1985 wealth and on annual income in 1983-85.
consumer surveys and the demographic trends projected for
The two Board surveys are particularly useful in analyzing
the next few decades.
average savings because they “oversample” the high-income
households that account for a disproportionately large share
A g e P r o f il e s o f I n c o m e a n d S a v i n g s
of aggregate savings. A detailed explanation of our use of the
Data from the Board of Governors’ Survey of Consumer
survey data to calculate saving rates is contained in the box
Finances allow us to examine the proposition that household
below.
C a l c u l a t in g S a v in g R a t e s f r o m th e S u r v e y o f C o n s u m e r F in a n c e s
We calculate average annual income (in
purchases of new homes. Capital gains on other property (sec
1982 dollars) from total household income data reported in
ondary residences, farmland, undeveloped land, and invest
the 1986 Survey of Consumer Finances for the years 1983,
ment real estate) equal the 1982 value of the property multi
1984, and 1985. We also include in income several other
plied by a price index for the type of property. Capital gains
items reported separately in the survey, such as insurance set
on direct holdings of stock and stock m utual funds are
tlements and cash advances.
assumed to equal the increase in the S&P 500 index over the
A ve r a g e In c o m e .
period multiplied by initial holdings. Because many house
Total savings equals the total change
holds hold IRAs, trusts, and thrift plan assets in stocks, we
in wealth (in 1982 dollars) between year-end 1985 (drawn
calculate capital gains on these assets as the gains in the S&P
from the 1986 survey) and year-end 1982 (drawn from the
500 times the holdings of trusts, IRAs, and thrift plan assets
1983 survey), including capital gains but excluding “wind
falls.” Windfalls account for roughly one-seventh of all sav
times the aggregate share of these assets invested in stocks.
ings in the sample and consist of net inheritances (inheri
S a v in g R ates .
tances received minus inheritances given by a deceased
sonal saving rates. The total saving rate represents the average
spouse), net support from other family members (received
annual change in total wealth, including capital gains,
minus given), and several other items. Like other researchers
between year-end 1982 and year-end 1985, divided by aver
in this area, we exclude windfalls in order to focus on planned
age annual income. The personal saving rate is the average
savings behavior. We also exclude changes in defined benefit
change in wealth excluding capital gains, divided by income.
C h an g e s in W ealth .
We calculate both total saving rates and per
pension wealth because they are not reported in the survey.
E x c l u d e d O b se r v a t io n s .
Even in carefully constructed
The data permit the calculation of capital
household surveys, wealth and savings are inaccurately mea
gains on housing because they include the value of housing
sured, and some household saving rates will be unreasonably
wealth at year-end 1982 and year-end 1985 and sales and
high or low. We therefore exclude from our sample certain
C apital G a in s .
FRBNY Q u a r t e r l y R e v ie w / S u m m e r -F a ll 1994
77
obvious outliers—households with particularly large positive
or negative saving rates. The exclusion rule drops the bottom
fer significantly from ours. Many of the differences are
and top 0.5 period of the distribution of saving rates. House
and the exclusion rules. Bosworth et al. exclude capital gains
holds that experienced a change in marital status between the
on housing, directly held stocks, and stock mutual funds,
1983 and 1986 surveys are also excluded. The final sample
but not capital gains on other real estate IRAs, trusts, and
contains 2494 households.
thrift plans. Instead of excluding both large and small saving
attributable to differences in the definition of capital gains
rate outliers, as we do, they exclude only observations with
Bosworth, Burt-
large saving rates, greater than 1. They also exclude house
less, and Sabelhaus (1991) calculated age-specific personal
holds with significant net worth in unincorporated business
saving rates from the Survey of Consumer Finances that dif
es, which we do not.
D if f e r e n c e s f r o m P r e v io u s R e s e a r c h .
For the households sampled in the 1986 Board sur
1985, present a similar age profile (Chart 2). This measure of
vey, average (mean) income rose, then fell, with advancing
savings includes capital gains on real estate and all financial
age (Chart 1). The highest average income, about $35,000
assets except employer contributions to pension plans, which
per year in 1982 dollars, was earned by both the 35 to 44 and
are not reported in the survey. Total savings rose more steeply
45 to 54 age groups. The distribution of incomes around this
with age than did income, with the peak occurring at $8,200
peak is roughly symmetric, falling below $20,000 for house
in the 55 to 64 age range. Savings in these years are large
holds with heads either below 25 or above 75. The shape of
because income is relatively high, family expenses are rela-
this distribution is determined by variations in wage rates
and labor force participation rates over the life cycle.2
Average total savings, defined as the average annual
change in total wealth between year-end 1982 and year-end
Chart 2
A v e r a g e A n n u a l T o t a l S a v in g s , b y A g e o f
H o u s e h o l d H e a d 19 8 3 -8 5
T
h o u san d s o f
19 8 2
dollars
Chart 1
A v e r a g e A n n u a l H o u s e h o ld In c o m e , b y A g e o f
H o u s e h o l d H e a d 1 9 8 3 -8 5
T
h o u san d s of
1982
dollars
Under 25
Under 25
25-34
35-44
45-5 4
55-64
65-74
75 and
above
Sources: Board of Governors of the Federal Reserve System, Survey of
Consumer Finances, 1983 and 1986; Federal Reserve Bank of New York
staff estimates.
Digitized
FRBNY Q u a r t e r l y R e v ie w / S u m m e r -F a ll 1994
78for FRASER
25-34
35-44
45-54
55-64
65-74
75 and
above
Sources: Board of Governors of the Federal Reserve System, Survey of
Consumer Finances, 1983 and 1986; Federal Reserve Bank of New York
staff estimates.
Note: "Total savings" represents the change in total financial and real estate
wealth, including capital gains.
tively low, and the need for retirement savings is immediate
ly apparent for most workers.
because of the large expenses of child rearing and household
formation.
In addition to total savings, we are also concerned
The age profile of saving rates o f course depends on
with the age profile of households’ personal savings, a narrower
conception of savings that excludes capital gains. Since capi
the changes in both savings and income over the life cycle.
tal gains are often passively earned, unplanned, and illiquid,
Chart 4 depicts the average total saving rates by age. Before
age 45, total saving rates are flat, around 12 percent, because
households may treat them differently than other forms of
income rises at about the same rate as savings until age 45.
savings. In addition, capital gains income has been volatile in
Thereafter, saving rates rise sharply to 20 percent between
the past, and hence difficult to project accurately. Since, at
ages 45 and 54 and peak at 31 percent between ages 55 and
the aggregate level, capital gains do not lead directly to
64. The total saving rate declines only slightly after 65:
increases in national investment, policymakers are generally
although savings levels fall rapidly, income falls almost as
more concerned about aggregate personal savings exclusive of
quickly.
Compared with the age profile of total saving rates,
capital gains (Harris and Steindel 1991).
Personal savings reach their highest level between
the age profile of personal savings is more peaked (Chart 5).
the ages of 45 and 54 (Chart 3). The peak occurs earlier than
Between ages 45 and 64, personal saving rates average about
the peak in total savings because capital gains are quite large
10 percent. Personal saving rates are very low for households
for households with heads aged 55 to 64. Personal savings are
extremely low, near zero, between ages 35 and 44, perhaps
Chart 4
Chart 3
A v e r a g e T o t a l S a v in g R a te , b y A g e o f
H o u s e h o ld H e a d 19 8 3 -8 5
A v e r a g e A n n u a l P e r s o n a l S a v in g s , b y A g e o f
H o u s e h o ld H e a d 19 8 3 -8 5
Percent
T
h o u san d s o f
19 82
35
d ollars
---------------------------------------------------------------------
4
30
25
15
5
-2
Under 25
25-34
35-44
45-54
55-64
65-74
75 and
above
Sources: Board of Governors of the Federal Reserve System, Survey of
Consumer Finances, 1983 and 1986; Federal Reserve Bank of New York
staff estimates.
Note: "Personal savings" represents the change in total financial and real
estate wealth less capital gains.
0
-i
I I
I I I I I I
I I I I I I
:—
Under 25
25-34
i 1 1 1I B
35-44
45-5 4
I 1H1W81 I HHW IWBIP
55-64
65-74
75 and
above
Sources: Board of Governors of the Federal Reserve System, Survey of
Consumer Finances, 1983 and 1986; Federal Reserve Bank of New York
staff estimates.
F R B N Y Q u a r t e r l y R e v ie w / S u m m e r -F a ll
1994
79
headed by individuals between ages 35 and 44, and negative
The actual steepness of mean life cycle saving rates is
for those whose head is between ages 65 and 74.
So far, our analysis has focused on means within age
somewhat obscured in Chart 5 by the presence of early
groups. In keeping with our interest in aggregate savings, the
our sample, the age-savings profile of nonretirees rises more
mean gives appropriate weight to high-income households.
steeply with age and remains higher longer than the age pro
A concern about the saving behavior of a typical household
file for the full sample (Chart 7). This finding need not imply,
would, in contrast, require a focus on median savings. More
however, that early retirement reduces aggregate savings,
over, popular perceptions about life cycle saving rates are
because those that retire early may save more than others in
probably based on observations of “typical” rather than
the years preceding their retirement. (The age-savings pat
“mean” household behavior. We therefore present, in Chart 6,
terns in Chart 7 cannot be interpreted as the saving rate of a
the median personal saving rates by age, also drawn from the
household whose head is expected to retire at age 65, since
survey sample.
many of the households in the sample may be planning to
A comparison of Charts 5 and 6 reveals that (1)
retirees in age groups under 65. If we exclude retirees from
retire earlier or later than 65.)
median saving rates are much lower than mean rates, or alter
natively, that high-income households account for a dispro
D e m o g r a p h ic T r e n d s
portionate share of aggregate savings; and (2) the age profile
Before projecting the effect of baby boomer savings on the
of the medians is less peaked than the age profile of mean
aggregate saving rate, we must first assess the size of the baby
saving rates. The absence of a strong life cycle pattern in
median savings may be explained by the relatively modest
amount of financial savings accumulated by most house
holds and their near total reliance on pensions and Social
Security in retirement.
Chart 6
M e d ia n P e r s o n a l S a v in g R a t e , b y A g e o f
H o u s e h o ld H e a d 19 8 3 -8 5
Percent
Chart 5
A v e r a g e P e r s o n a l S a v in g R a te , b y A g e o f
H o u s e h o ld H e a d 19 8 3 -8 5
Percent
II 1
I
■ I
1
Under 25
25-34
35-44
45-5 4
55-64
65-74
■■■■
i
i i
r:
iI|z
_
...................................
1
1
75 and
above
Sources: Board of Governors of the Federal Reserve System, Survey of
Consumer Finances, 1983 and 1986; Federal Reserve Bank of New York
staff estimates.
Digitized
F R B N Y Q u a r t e r l y R e v ie w / S u m m e r -F a ll 1994
80 for FRASER
i
i
Under 25
i
25-34
i
35-44
i
4 5 -54
i
55-64
i
65-74
i
75 and
above
Sources: Board of Governors of the Federal Reserve System, Survey of
Consumer Finances, 1983 and 1986; Federal Reserve Bank of New York
staff estimates.
boom demographic bulge and consider how its relative size
can be expected to change over time. Chart 8 presents Census
data on the age distribution of household heads for 1970 and
1990 and a forecast of the age distribution in 2010.3 That
part of the age distribution represented by baby boomers is
Chart 8
D ist r ib u t io n o f H o u se h o l d s b y A g e o f H o u se h o l d H e a d
1970, 1990, and Projection for 2 0 10
M i l l io n s
25
19 7 0
shaded in the chart. For simplicity, we have defined baby
boomers as the generation born in the twenty-year period
Baby-boom generation
Other generations
20
after World War II, between 1945 and 1964. (The baby
boom population is normally defined as individuals born
15
between 1946 and 1964.)
In 1970, all baby boomers were less than 25 years
old and headed only 7.6 percent of all households. By 1990,
10
Bem
however, when baby boomers reached the ages of 25 to 44,
.
they headed 41 million households, roughly 44 percent of all
households. In that year, baby boomers headed 50 percent
more households than did members of the preceding genera
tion (individuals between the ages of 25 and 44 in 1970). By
_
1
M
Hi
ill Hi
i l |1|
wm
i|B
:
iililil
IB B b
HHI
1981 ■81
| | f*
l____,.i ___i _____ i ___
19 9 0
the year 2010, when baby boomers will be between 45 and 64
Chart 7
A v e r a g e P e r s o n a l S a v in g R a te , E x c lu d in g R e tir e e s ,
b y A g e o f H o u s e h o ld H e a d 19 8 3 -8 5
P ercent
-10
Under 25
25-34
35-44
45-54
55-64
65-74
75 and
above
Sources: Board of Governors of the Federal Reserve System, Survey of
Consumer Finances, 1983 and 1986; Federal Reserve Bank of New York
staff estimates.
Under 25
25-34
35-44
45-54
55-64
65-74
75 and
above
Source: U.S. Bureau of the Census, Current Population Reports.
F R B N Y Q u a r t e r l y R e v ie w / S u m m e r -F a ll 1994
81
years old, they will head about 46 million households, or
roughly 39 percent of all households.
The decline in the relative size of the baby boom
share and its relative income (shown in Chart 1). The house
hold population shares are assumed to change over time in
keeping with the Census projections. Larger groups and
generation between 1990 and 2010 from 44 percent to 39
groups with higher average household incomes have larger
percent of all households will diminish its potential impact
weights. (For a more exact description of the weighting pro
on the aggregate saving rate. This decline in relative size is
cedure, see Kennickell 1990.)
due in part to the growing importance of two demographic
The projected behavior of the broad saving rate mea
groups whose low saving rates will offset the baby boom’s
sure, inclusive of capital gains, is depicted in Chart 9- The
increased savings. The generation following the baby
demographic trends suggest that the total saving rate should
boomers is expected to head 39 million households in 2010,
have reached its low point at about 18.0 percent in 1990, will
only 2 million fewer households than the baby boomers head
rise to 19-4 percent in 2010, and peak at 19-8 percent in
ed at the same ages. In addition, the share of elderly house
2015. These projected increases are expected to be quite
holds in the population will increase significantly.
gradual, with the first 140 basis point increase extending
over twenty years and the next 40 basis point rise occurring
T h e P r o je c t e d Im p a c t o f D e m o g r a p h ic T r e n d s
on
A g g r e g a t e S a v in g s
over the following five years.
The predicted behavior of the more narrowly defined
Assuming that the age patterns in income and savings from
personal saving rate, which excludes capital gains, is shown
the Survey of Consumer Finances remain stable over time, we
in Chart 10. Here demographic changes imply that the per
can use the Census Bureau population forecasts to project the
sonal saving rate should have reached its low point at about
aggregate saving rate as the baby boom generation matures.
4.1 percent in 1990 and should rise about 80 basis points to
Our aggregate saving rate projections are derived by averag
peak at 4.9 percent near the year 2010. During the twenty
ing household saving rates (shown in Charts 4 and 5),
years between 2010 and 2030, the aggregate personal saving
weighting each age group’s saving rate by its population
rate should decline by about 100 basis points because the
Chart 9
P r o je c t e d T o t a l S a v in g R a t e
P ercent
Sources: Board of Governors of the Federal Reserve System, Survey of Consumer Finances, 1983 and 1986; U.S. Bureau of the Census, Current Population Reports;
Federal Reserve Bank of New York staff estimates.
FRBNY Q u a r t e r l y R e v ie w / S u m m e r -F a ll 1994
82
share of retirees in the population w ill be rising sharply.
S e n s it iv it y A n a l y s is o f t h e A g g r e g a t e S a v in g s
(Recall from Charts 4 and 5 that households headed by indi
P r o je c t io n s
viduals over 65 had low or even negative personal saving rates
at the same time that capital gains kept this group’s total sav
Our projections for aggregate savings are, of course, sensitive
to our assumptions about the future age profiles of the popu
ing rates fairly high.)
lation, relative incomes, and saving rates. Other reasonable
In conclusion, if the life-cycle increase in the saving
rates of the baby boom generation is comparable to the
increases for previous generations, the rise in aggregate sav
ing rates over the next twenty-five years will be modest: 180
basis points (from 18.0 percent to 19-8 percent) in total sav
ing rates and 80 basis points (from 4.1 percent to 4.9 per
cent) in personal saving rates. These projected changes in the
aggregate saving rates are not particularly large relative to
previous fluctuations, reflecting the lim ited predictive
I f the life-cycle increase in the saving rates o f
the baby boom generation is comparable to the
increases fo r previous generations, the rise in
aggregate saving rates over the next twenty-five
years w ill be modest.
power of demographic models of savings. From the early
1980s to the present, the aggregate personal saving rate fell
roughly 300 basis points, as compared with the 80 basis
assumptions, however, do not reverse our basic finding that
point improvement by 2010 implied by our projections.
demographic forces are unlikely to boost the aggregate sav
W hile the broader total saving rate measure of savings fell
ing rate substantially.
less sharply than the personal saving rate, the anticipated
For example, if we shift the assumptions about pop
improvement in savings attrib utab le to demographic
ulation growth from the Census Bureau’s so-called middle
changes cannot be counted on to produce a full recovery in
projection to its high or low projections, we do not get signif
either of these measures.
icantly different results. Using the high population growth
Chart 10
P r o je c t e d P e r s o n a l S a v in g R a t e
Percent
Sources: Board of Governors of the Federal Reserve System, Survey of Consumer Finances, 1983 and 1986; U.S. Bureau of the Census, Current Population Reports:;
Federal Reserve Bank of New York staff estimates.
F R B N Y Q u a r t e r l y R e v ie w / S u m m e r -F a ll 1994
83
projections decreases the projected 2010 aggregate personal
saving rate by 4 basis points; using the low growth projection
raises it by 10 basis points.
Finances saving profile.
Our main conclusion stands up to this sensitivity
analysis: aggregate saving rates are not likely to be pushed up
W e also tested the sensitivity of our projections to
sharply by demographics if future age profiles o f saving rates
changes in the ratio o f population to households (household
are similar to those observed in the recent past. This is not to
composition), which we assumed to be fixed from 1992 for
say, however, that the aggregate saving rate would be insensi
ward. If household size falls in line w ith various Census pro
tive to an unexpectedly large increase in baby boomer saving
jections, our projections o f aggregate personal savings change
rates. If the age profile o f boomer saving rates turns out quite
by no more than 2 or 3 basis points.
different from what we’ve projected, the effect on aggregate
Moreover, our assumptions about the age-income
savings could be large. W e have already noted that in the year
profile are, if anything, biased in favor o f finding a large rise
2 0 1 0 , 39 percent o f households w ill be headed by baby
in aggregate savings over the next twenty years. W e may have
boomers. Those households w ill be in their peak earning
overestimated the baby boom generations’s impact on sav
years and w ill account for 4 4 percent o f aggregate income. If
ings by overestim ating its share o f aggregate income in
the baby boomers’ personal saving rate in middle age exceeds
future years. W e have assumed that boomers between ages 45
that o f previous generations by 2 percentage points (12 per
and 6 4 w ill earn the same amount in relation to other groups
cent, rather than 10 percent), the aggregate saving rate pro
as did 45 to 64 year olds in the Survey o f Consumer Finances.
jection would increase another 90 basis points beyond the 80
Because baby boomers are an unusually large labor cohort,
basis point increase we are already projecting through 20 10 .
their wages may be lower relative to other generations at each
point in the life cycle. W elch (19 7 9 ) has documented that
T he A lleged R etirem en t S a v in g s
baby boomer entry level wages were 10 percent lower than
S hortfall a n d A g g r e g a t e S a v in g s
entry level wages for other cohorts, and Berger (198 5) claims
Is there any reason to expect that the life-cycle increase in
that boomer wages have remained relatively depressed. If
baby boomer saving rates w ill be more pronounced than
baby boomer incomes were assumed to be 10 percent lower
those o f earlier generations? In the view o f some, the baby
than the incomes reported in Chart 1, then our projected 80
boomers differ from earlier generations in the level o f their
basis point increase in the aggregate personal saving rate
retirement savings. The popular image in the 19 80s o f free-
from 1990 to 2010 would be lower by about 20 basis points.
spending baby boomers (“yuppies”), coinciding as it did w ith
The most obvious risk in our forecast comes from
a sharp fall in the aggregate personal saving rate, left the
our assum ptions about the saving rates o f d ifferen t age
impression that baby boomers do not save enough. If baby
groups. Nevertheless, other studies, using other household
boomers are not saving adequately for retirement, they may
surveys and covering other tim e periods, have generally
eventually try to make up the savings shortfall by raising
found less steeply sloped age-saving profiles, also implying
their saving rates more sharply than did previous generations.
weak demographic effects on the aggregate saving rate. (See,
In this section, we examine the available empirical evidence
for example, Summers and Carroll 19 8 7 , Auerbach and Kot-
on the adequacy o f baby boomer savings. W e concentrate on
likoff 19 8 9 , Bosworth, Burtless, and Sabelhaus 1 9 9 1 , Ken-
the older h a lf o f the baby boom (ages 35 to 4 4 in 1 9 8 9 )
nickell 19 9 0 , and Attanasio 19 93.) The most steeply sloped
because younger baby boomers (ages 25 to 34 in 19 89) did
age-saving profile among these studies is calculated from the
not, as of 1989 , need significant retirement savings, so are not
19 7 2 -7 5 Consumer Expenditure Surveys by Bosworth, Burt
yet interesting subjects o f study.
less, and Sabelhaus (19 9 1). This profile, when used in our
Exact statements about savings adequacy require
projections, generates a 32 basis point rise in personal saving
detailed information about the average household’s w illing
rates from 1990 to 20 10 , compared w ith the 8 0 basis point
ness to trade off current for future consumption (preferences
increase projected using the 1 9 8 6 Survey o f Consum er
for saving), the expected path o f future income, and expected
FRBN Y
84
Q u a r t e r l y R e v ie w / S u m m e r - F a ll
1994
future interest rates. Lacking this sort of data, analysts take
tern is evident in the m edian com parisons (M anchester
two approaches to the adequacy o f baby boomer savings.
19 9 3 ). From these rough measures, it appears that baby
The first approach compares the accumulated sav
ings o f the baby boomers to the savings o f previous genera
boomers have managed to accumulate more wealth than their
parents had at the same ages.
tions at the same ages. The second approach uses estimates of
These results may be misleading, however, because
future earnings and interest rates, together w ith assumptions
the 1963 and 198 9 surveys were successful to different
about preferences for savings, to calculate “desirable” or
degrees in measuring household wealth. Detailed compar
“target” levels o f retirem ent savings for baby boomers at
isons o f aggregate wealth as measured by the two surveys and
every age. These savings targets are then compared w ith the
the Federal Reserve’s Flow o f Funds Division suggest that
actual savings o f baby boomers. W e find little compelling
while aggregate wealth from the 1 9 8 9 Survey o f Consumer
evidence o f retirement undersaving under either approach.
Finances matched the Flow o f Funds aggregates closely, the
19 6 3 Survey o f Financial Characteristics o f Consumers cap
C o m p a r iso n s w it h P r e vio u s G en eratio n s
tured only 82 percent o f the Flow o f Funds aggregates .5 The
The logic o f the first approach is simple: if the baby boomers
Flow o f Funds data and the household surveys represent very
have put aside as much as current retirees had at the same ages
different methodologies o f wealth measurement; some dis
and can expect similar levels of Social Security and pension
parity in their findings is to be expected. Nevertheless, if the
benefits in the future, then the baby boom generation is mak
differences are due to mismeasurement in the household sur
ing adequate provision for a comfortable retirement .4
veys, comparisons across the surveys may be flawed.
O ur intergenerational comparisons focus on net
The intergenerational wealth comparisons o f the
w ealth relative to income because we need to adjust for
two lines o f Table 1 are based on the extreme assumption that
improvements in living standards and because we recognize
all o f the differences between the household surveys and the
that retirement savings are typically meant to replace a cer
Flow o f Funds data are attributable to mismeasurement in
tain fraction o f earned income. The first line o f Table 1 com
the latter source. One way to check the sensitivity o f the
pares the average wealth-to-income ratios o f baby boomers at
cross-generational comparisons is to assume instead that all
year-end 1988 w ith those o f their parents at year-end 1962 .
differences between the two types o f survey stem from mis
The second line compares medians. The ratios are calculated
measurement in the household surveys and to benchmark the
from the Board o f Governors’ 19 6 3 Survey o f Financial Char
household surveys to the Flow o f Funds data. Benchmarking
acteristics o f Consumers and the 19 8 9 Survey o f Consumer
increases the 19 6 2 wealth measures by one-fourth. The 19 8 9
Finances. These survey measures o f wealth include housing
household survey aggregates equal 97 percent o f the Flow of
and most other assets except defined benefit and defined con
Funds aggregates, so benchmarking increases 19 8 8 wealth
tribution pension wealth.
by 3 percent.
In 19 8 8 , baby boomers held on average more assets
Table 2 compares mean and median benchmarked
than their life-cycle counterparts held in 19 62. The same pat-
ratios across generations. By both measures, baby boomers
have accumulated more assets than their parents did in 1962 ,
although the differences have shrunk from Table 1. Bench
Table 1
S a v in g s o f the B a b y B o o m e r s a n d the P re ce d in g G en eratio n :
E vid en ce fr o m U n a d ju st e d H o u seh o ld S u r v e y D ata
marking the ratios thus leaves intact the finding o f higher
wealth accumulation among baby boomers.
Household Head
Household Head
35 to 4 4 Years
35 to 4 4 Years
Old in 19 6 2
O ld in 19 8 8
indicate that the baby boom generation is well prepared for
Average wealth-to-income ratios
2 .0 7
2 .7 6
retirement. Unfortunately, simple comparisons o f nonpen
Median wealth-to-income ratios
0 .8 7
1 .1 0
Sources: Survey o f Financial Characteristics o f Consumers, 19 6 3 ; Survey of
Consumer Finances, 1 9 8 9 ; Federal Reserve Bank o f New York staff estimates.
Cross-generational comparisons o f wealth, therefore,
sion wealth ignore other factors that determine the need for
saving: the baby boom generation faces challenges different
F R B N Y Q uarterly R
e v ie w
/S u m m e r -F a l l
1994
85
from those its parents faced, challenges that may increase its
baby boomer’s future earnings. Also built into the model are
need for retirement savings relative to previous generations.
assumptions about future changes in fam ily com position
Three factors in particular point to an increased need
and related expenses, the increased life expectancy o f baby
for retirement savings for baby boomers. First, in spite o f an
boomers, and the structure o f social security and pension
im minent increase in the Social Security retirement age to
benefits.
66 , baby boomers must save for a retirement that may last
These technical assumptions and forecasts probably
longer than that o f their parents. Second, the generation of
affect the generated savings targets in important ways. More
current retirees benefited from the inflation o f the 1970s,
critical, however, are the authors’ assumptions about motives
which sharply reduced its m ortgage liabilities. The baby
for saving and their treatment o f sources o f retirement wealth
boom generation cannot count on a similar windfall. Third,
other than savings accumulated in financial assets. Bernheim
the measures o f household wealth compared across genera
and Scholz assume that people save for one reason only: con
tions in Table 1 do not include the most important compo
sum ption in retirem ent. B ut people also save to protect
nents o f household retirem ent wealth: public and private
pensions and Social Security. Although trends in these pro
grams are uncertain at present, they may decrease the retire
ment resources available to baby boomers.
Cross-generational comparisons of wealth. . .
indicate that the baby boom generation is
well preparedfor retirement.
B ern h eim a n d S c h o l z ’s S im u l at io n S tu d ies of
S a v in g s A d e q u a c y
In contrast to intergenerational comparisons o f wealth, the
simulation studies o f Bernheim and Scholz (199 3) and Bern
themselves against financial emergencies, to pay for their
heim ( 19 9 2 , 19 9 3 , 19 94) attem pt to provide an absolute mea
children’s education, or to leave their children an inheritance.
sure o f savings adequacy that takes into account the particu
Since we cannot separate observed savings into savings for
la r econom ic c ircu m sta n c es faced by th e baby boom
retirement and savings for other reasons, the targets are too
generation. These researchers construct a model o f optimal
low. In addition, the model assumes that baby boomers w ill
savings behavior for baby boomers who would like to main
receive no inheritances, and that they w ill not change hous
tain after retirement roughly the same standard o f living they
ing after they retire, using some portion o f home equity to
enjoy just before their retirement.
finance retirement consumption. If baby boomers expect to
To calculate target retirem ent wealth at each age,
receive inheritances and draw on their home equity, the Bern
Bernheim and Scholz develop forecasts of future economic
heim and Scholz targets are too high. Since these targets may
conditions and assume a path for future interest rates. Con
be either too low or too high, comparisons between the tar
trolling for age and education, they forecast a representative
gets and survey data may either under- or overstate retire
ment preparedness.
The simulation model generates target wealth (accu
Table 2
mulated savings) for the head o f a household at every age. The
S a v in g s o f t h e B a b y B o o m e r s a n d th e P r e c e d in g
G e n e r a t io n : E v id e n c e f r o m H o u se h o l d S u r v e y D a t a
B e n c h m a r k e d t o t h e F l o w o f F u n d s D ata
change in target wealth as the head o f the household ages deter
Household Head
Household Head
35 to 4 4 Years
35 to 4 4 Years
Old in 19 6 2
Old in 19 8 8
Average wealth-to-income ratios
2 .5 2
2.85
Median wealth-to-income ratios
1.0 6
1. 13
Q u a r t e r l y R e v ie w / S u m m e r - F a ll
target savings for households earning more than $ 20,000 per
year w ith the savings observed in M errill Lynch surveys o f
such households. He concludes that in 1 9 9 1 and in 1 9 9 2 ,
Sources: Board o f Governors o f the Federal Reserve System, Flow o f Funds
Accounts; Survey o f Financial Characteristics o f Consumers, 19 6 3 ; Survey of
Consumer Finances, 19 8 9 ; Federal Reserve Bank o f New Y ork staff estimates.
FRBN Y
86
mines annual target savings. Bernheim compares the annual
1994
baby boomers were saving at roughly 34 percent o f the rec
ommended rate o f target (nonhousing) savings. Bernheim
and Scholz obtain similar results by comparing saving rates
that baby boomer saving rates were dangerously low in 1983 -
from the 19 8 6 Survey of Consumer Finances w ith their target
85 and in 1 9 9 1 -9 2 , this generation’s accumulated wealth is
rates, but they reveal that undersaving is concentrated among
nevertheless in line w ith simulated retirement savings tar
individuals w ithout college educations.
gets. M oreover, high-incom e households, who are more
Surprisingly, although these authors find that house
holds’ saving rates fell far short o f the model’s savings targets
im portant in the determ ination o f aggregate saving rates,
seem to be putting aside savings on schedule.
in 1983 - 85 , 1 9 9 1 , and 19 9 2 , their work also implies that
boomers have done a reasonable job o f reaching their retire
S o c ia l S e c u r it y a n d P e n sio n s
ment wealth targets. In a 19 9 3 report, the authors compare
Although we have so far kept to issues that are amenable to
accum u lated w ea lth in the 1 9 8 6 S u rvey o f C onsum er
empirical investigation, we recognize that aggregate savings
Finances w ith target levels and find relatively high median
may be substantially affected by other, more indefinite factors
ratios, especially among college-educated households. Our
such as the future o f the Social Security program, the impact
own examination o f data from the most recent (198 9) Survey
o f changes in pension coverage, and the various adjustments
o f Consumer Finances reveals that the median ratio o f accu
that baby boomers m ight make to retirement savings inade
mulated wealth to the Bernheim-Scholz target level is 0.95
quacy. Baby boomers may receive lower Social Security bene
for 35 to 4 4 year olds .6 That is, nearly h alf o f the sample
fits than their parents as federal fiscal pressures force a choice
report nonhousing assets greater than the authors’ targets.
between increasing taxation and reducing benefits over the
This discrepancy— that w ealth accum ulation ap
pears on target while saving rates appear low— is not easy to
next few decades. Moreover, the future generosity o f private
and public pensions is uncertain.
explain; however, we have somewhat greater confidence in
Auerbach and K o tlik o ff (19 9 4 ) have analyzed the
the wealth results. The inadequacy of saving rates was shown
effects o f hypothetical Social Security restructuring on baby
to hold only over a few years and hence may not be true for
boomer wealth. They project that if social security benefits
other years. Moreover, surveys o f changes in wealth (savings)
are cut sharply in 2 0 0 9 , most baby boomers w ill face a stan
probably suffer from proportionately more m easurement
dard o f living worse than that o f the current generation of
error than do surveys o f accumulated wealth. However, the
results showing that the flow o f savings is too low, if true,
would be quite troubling. If a shortfall in the flow o f savings
This discrepancy— that wealth accumulation
continues, it w ill inevitably lead to a shortfall in the stock of
savings.
appears on target while saving rates appear
The Bernheim and Scholz approach is, however, not
low— is not easy to explain; however, we have
entirely appropriate for our purposes. Their analysis focuses
on the retirem ent preparedness o f the median, or typical,
somewhat greater confidence in the wealth results.
household. Since our interest is in aggregate savings, the
mean ratio is also o f interest. This ratio gives a greater weight
to the savings o f high-income households, which account for
a disproportionately large share o f aggregate savings. The
retirees. To date, potential shortfalls in the Social Security
mean ratio o f wealth to the Bernheim targets in 19 8 8 is 2.07,
and Medicare Trust Funds have been remedied by increases in
suggesting that those households whose savings have the
taxation, w ith few cuts in benefits. Only the increase in the
greatest im pact on aggregate savings are com fortably on
normal retirement age, enacted in 198 3 , and the more recent
track for retirement.
taxation o f the Social Security benefits o f higher income
In summary, although the sim ulation studies o f
Bernheim (199 3) and Bernheim and Scholz (199 3) suggest
recipients can be unambiguously construed as a decrease in
benefits.
F R B N Y Q u a r t e r l y R e v ie w / S u m m e r - F a ll
1994
87
Trends in public and private pensions are more diffi
their retirement funds for any reason, would they rapidly step
cult to evaluate. Although private pension coverage has
increased over the last three decades, the nature of that cover
up their saving rates in response to it? To answer this ques
age has changed. In the last twenty years, the mix of plans has
approaching retirement, discovers the inadequacy of his or
changed: defined benefit coverage has been falling while
her retirement provision.
tion, one must examine the options facing a person who,
defined contribution coverage has been rising (Chart 11). It is
The first option is a large increase in saving rates.
not yet clear which of these plans is the better vehicle for
Such a response will, of course, boost aggregate saving rates as
retirem ent savings, from the perspective of either the
baby boomers approach retirement. The second option is a
employer or the employee. W hile some evidence suggests
large decline in consumption in retirement. This response
that the most popular defined contribution plans stimulate
will also lead to an increase in aggregate savings, as retiring
savings (see, for example, Poterba, Venti, and Wise 1992),
baby boomers dissave (eat into their retirement savings) at a
there is growing concern that employees do not invest
lower rate. (Note, however, that under this scenario, the
defined contribution assets appropriately for retirement.
increase in saving rates will come later, after baby boomers
retire.) A third reaction is to postpone retirement and extend
A d ju s t m e n t s t o S a v in g s S h o r t fa l l s
working life. Both the income and savings of baby boomers
Although there is no conclusive evidence of a baby boomer
w ill rise as they work longer. A fourth possibility is an
savings shortfall, the risks to the social security benefits of
increase in net intergenerational transfers to retirees, either
baby boomers cannot be ignored. The risks are admittedly
from an increase in the generosity of Social Security benefits
speculative—we do not know whether the government will
or from a decrease in inheritances. In light of the looming
move to cut benefits substantially. Nevertheless, the question
shortfalls in Social Security, an increase in the generosity of
arises, if baby boomers were to face a substantial shortfall in
Social Security seems unlikely; a decrease in bequests by baby
boomers will entail a decrease in retiree savings (increases in
dissaving) and an increase in the savings of younger genera
Chart 11
P e n s io n C o v e r a g e , b y P r im a r y P l a n
P e r c e n t o f labo r force
tions, who will expect smaller inheritances. (Empirical work
in Weil 1994 suggests that the expectation of bequests low
ers savings.)
A review of these options suggests that even if there
is a retirement savings shortfall, the baby boom generation
may not increase its savings in response to it. No clear evi
dence on the reaction of households to savings shortfalls cur
rently exists. Should a surge in baby boomer savings occur,
the effect on aggregate savings will very likely be large, but
the surge itself is uncertain.
C o n c l u sio n
Policymakers concerned about low aggregate saving rates
should not rely on the aging of the baby boom generation to
restore aggregate savings to earlier levels. We draw this con
clusion from (1) a review of life-cycle increases in saving rates
and demographic trends and (2) an assessment of the prospect
that baby boomers w ill accelerate their saving rates in
Source: Employee Benefits Research Institute.
88
F R B N Y Q u a r t e r l y R e v ie w / S u m m e r-F a ll 1994
response to a retirement savings shortfall.
First, as baby boomers move more fully into middle
benefits, the evidence that baby boomers are not saving ade
age, the life-cycle increases in their saving rates w ill lead to
quately for retirem ent is unconvincing. To date, boomers
only a modest increase in aggregate saving rates. Survey evi
have generally accumulated more wealth relative to their
dence from the m id- 1980 s suggests that boomers’ own sav
incomes than their parents had by the same ages. Moreover,
ing rates w ill roughly double as they move into middle age.
the stocks o f w ealth that boomers have accum ulated are
Partially offsetting this positive effect on savings, however,
roughly consistent w ith target levels recommended by opti
w ill be a rise in the relative population shares o f low-savings
mal lifetime savings models. These healthy stocks o f savings
groups (people above 75 and below 35) over the next two
are, however, hard to reconcile with the reportedly weak flow
decades. Our projections indicate that demographic trends
o f savings observed in survey data. Nonetheless, even if baby
should push up the aggregate personal saving rate in total
boomers do face a shortfall— perhaps one resulting from a
only about 80 basis points by the year 2010 .
decrease in Social Security benefits— it is not clear that they
Second, barring a major reduction in Social Security
would dramatically increase their savings in response.
FRBNY Q u a r t e r l y
R e v i e w /S u m m e r -F a l l
1994
89
En d n o tes
1. These arguments have been analyzed by a number of authors. Summers
Note 3 continued
and Carroll (1987), Bosworth, Burtless, and Sabelhaus (1991), and Attana-
Bureau in Current Population Reports, Population Projections of the United
sio (1993) examine the role o f demographics in the fall o f the aggregate sav
States, by Age, Sex, Race, and Hispanic Origin: 19 9 2 to 20 50, P2 5 -10 9 2 .
ings rate in the early 1980s. Auerbach and KotlikofF (1989) and Kennickell (1990) examine the effect of baby boomer aging on future saving rates.
4. Several analysts have explored this approach. Easterlin, Schaeffer, and
Auerbach and K otlikoff predict a modest increase in saving rates; Kennick-
Macunovich (1993) compare income and wealth across generations at sim
ell predicts a small increase. Arguments supporting the view that baby
ilar points in the life cycle and find a general improvement across genera
boomers are undersaving are presented in Bernheim (1993) and Bemheim
tions. Manchester (1993) concentrates on wealth and finds that the median
and Scholz (1993); opposing views are presented in Manchester (1993) and
wealth position o f baby boomers is modestly better than that o f earlier
Easterlin, Schaeffer, and Macunovich (1993).
generations.
2. The age-income cross-sectional distribution in Chart 1 is measured at a
5. For comparisons of the 19 63 Survey o f Financial Characteristics of Con
point in time and is not representative o f the age-earnings profile that a
sumers with the Flow o f Funds data, see Avery, Elliehausen, and Kennick-
typical household can expect to earn over time. The latter profile would
ell (1988). W e are indebted to Rochelle Antoniewicz of the Federal Reserve
probably rise more steeply with age, because young workers will typically
Board Flow of Funds Division for pointing out a mistake in the compar
earn more when old than old workers currently earn. (For further discus
isons in this source and for providing preliminary comparisons o f the 19 8 9
sion, see Easterlin, Schaeffer, and Macunovich 1993.) This “bias” in the
Survey of Consumer Finances with the Flow of Funds Accounts.
cross-sectional age-earnings profile is also present in the age-savings pro
file. The age profile of saving rates, however, w ill not necessarily be biased.
6. The analysis was carried out on 35 to 4 4 year olds. Bemheim (1993)
presents targets for individuals who earned $ 3 0 ,0 0 0 or more at age 35. We
3- Historical data on the age distribution o f households are published
use his estimates of age-earnings profiles, combined with his method of
annually by the U.S. Department of Commerce, Bureau of the Census, in
imputing income to spouses, to estimate earnings at age 35 for the 19 8 9
Current Population Reports, “Household and Family Characteristics,”
Survey of Consumer Finances sample. Interpolating where necessary, we
Series P20. Projections of the future age distribution of households were
calculate target savings (excluding household wealth) for each household.
obtained by assuming that (1) within ten-year age bands, the current ratios
Target savings are taken from Table 1 of Bernheim (1993). Estimated age-
o f households to population remain constant over time and (2) population
income profiles are taken from Bemheim (1992).
cohorts grow at the “middle series” estimates published by the Census
R
eferen ces
Attanasio, Orazio P. 1993. “A Cohort Analysis o f Saving Behavior by U.S.
_______ . 1994. “The United States Fiscal and Saving Crises and Their
Households.” National Bureau o f Economic Research W orking Paper
Implications for the Baby Boom Generation.” Merrill Lynch, New York.
no. 4454.
Avery, Robert B., Gregory E. Elliehausen, and Arthur B. Kennickell. 19 8 8 .
Auerbach, Alan J ., and Laurence J . Kotlikoff. 1990. “Demographics, Fiscal
“Measuring Wealth with Survey Data; An Evaluation of the 19 8 3 Sur
Policy, and U.S. Savings in the 19 80s and Beyond.” In Lawrence H.
vey o f Consumer Finances.” R e v ie w
Summers, ed., T a x P o l ic y
ber); 339-69.
a n d the
E c o n o m y . Cambridge, Mass.; MIT
of
I n co m e a n d W ealth (Decem
Press.
Digitized
F R B N Y Q u a r t e r l y R e v ie w / S u m m e r -F a ll 1994
90for FRASER
N otes
R e fe re n c e s
(Continued)
Berger, Mark C. 1985. “The Effect o f Cohort Size on Earnings Growth: A
Harris, Ethan S., and Charles Steindel. 19 91- “The Decline in U.S. Saving
Reexamination o f the Evidence.” JOURNAL OF P o l it ic a l ECONOMY
and Its Implications for Economic Growth.” F ederal R eserve B a n k
(June): 56 1-74 .
N e w Y o r k Q u ar t e r ly R e v ie w (Winter): 1-19.
Bernheim, B. Douglas. 19 92. “Is the Baby Boom Generation Preparing Ade
quately for Retirement? Technical Report.” Merrill Lynch, New York.
_______. 1993- “Is the Baby Boom Generation Preparing Adequately for
Retirement? Summary Report.” Merrill Lynch, New York.
of
Kennickell, Arthur B. 19 9 0 . “Demographics and Household Savings.”
Board of Governors of the Federal Reserve System, draft.
Manchester, Joyce. 1993. "Baby Boomers in Retirement: An Early Perspec
tive.” Washington, D.C.: Congressional Budget Office.
_______ . 1 9 9 4 . “The M errill Lynch Baby Boom Retirem ent Index.”
Merrill Lynch, New York.
Poterba, James M., Steven F. Venti, and David A. Wise. 19 92. “401(k) Plans
and Tax Deferred Saving.” National Bureau of Economic Research
Working Paper no. 4 1 8 1 .
Bernheim, B. Douglas, andJohn KarlScholz. 1993. “Private Saving and Pub
lic Policy.” In James M. Poterba, ed., T a x P o licy
a n d the
Ec o n o m y .
Cambridge, Mass.: MIT Press.
Bosworth, Barry, Gary Burtless, and John Sabelhaus. 1991- “The Decline in
Saving: Some Microeconomic Evidence.” B r o o k in g s P ape r s ON ECO
Summers, Laurence, and Chris Carroll. 1987. “W h y is U.S. National Savings
So Low?” B r o o k in g s P a pe r s
on
Ec o n o m ic A c t iv it y 2 :6 0 7 -3 5 .
Weil, David N. 1994. “The Saving of the Elderly in Micro and Macro Data.”
Q u arterly J o u r n a l of Ec o n o m ic s (February): 55-82.
NOMIC ACTIVITY 1: 18 3 -2 4 1.
Welch, Finis. 19 7 9 . “The Effects o f Cohort Size on Earnings: The Baby
Easterlin, Richard A., Christine M. Schaeffer, and Diane J . Macunovich. 1993.
“W ill the Baby Boomers Be Less W ell O ff Than Their Parents? Income,
Boom Babies’ Financial B u st.” J o u r n a l OF P o l it ic a l E c o n o m y
(October, pt.2): s65-s98.
Wealth, and Family Circumstances Over the Life Cycle.” University of
Southern California and Williams College, draft.
Digitized
N otesfor FRASER
FRBNY Q u a r t e r l y R e v ie w / S u m m e r -F a ll 1994
91
Mortgage Security Hedging and the Yield Curve
J u lia D. Fernald, Frank Keane, and Patricia C. Mosser
steepening of the yield curve in response to tighter
Treasury yield curve did not flatten after policy was tight
monetary policy this past spring puzzled many market ana
ened: the 125 basis point increase in the federal funds rate
lysts and economists. Most of the explanations of this phe
from February through May of 1994 was accompanied by a
nomenon have focused on macroeconomic issues such as mar
133 basis point increase in the ten-year Treasury rate. Third,
ket expectations of higher inflation or higher future interest
after the change in policy direction in February, the yield
rates. This article offers an additional, markets-based expla
curve became more hump-shaped: the two-year Treasury
nation that examines hedging activity—particularly the
yield rose 175 basis points, but the thirty-year yield increased
hedging of mortgage-backed securities—and its effect on the
only 96 basis points.
1 rih
Although the steepening after February was extreme
short-run dynamics of the yield curve.
When interest rates rise, both the duration and the
by historical standards, Cohen and Wenninger (1994) have
expected m aturity of a mortgage-backed security (MBS)
increase. If market participants seek to counteract the
increased price risk in MBSs by taking short positions in sim
Chart 1
ilar duration Treasury securities, the increase in MBS dura
T r e a s u r y Y ie l d C u r v e s
tion should cause participants to move their short Treasury
Percent
positions out the yield curve, effectively increasing the “sup
g --------------------------------------------------------------------- ---
ply” of long duration Treasuries.
Thus the hedging of mortgage securities in the Trea
April 20 ,19 9 4
sury market may—in the short run—magnify any increases
in long-term rates that accompany policy tightening. To the
extent that such hedging activity has become a standard fea
ture of the marketplace in the last few years, it may have per
manently altered the short-run dynamics of the yield curve
and thus changed the transmission of monetary policy.
R e c e n t M o v e m e n t s in t h e T r e a s u r y
Y ie l d C u r v e
Chart 1 highlights several significant movements in the yield
2 I__ I_I__ I______ I____________________________ I
FF* 2 3
5
curve since the fall of 1993- First, long rates began to rise in
October 1993, well before monetary policy tightened. Sec
ond, despite little or no observable inflation pressure, the
Digitized
FRBNY Q u a r t e r l y R e v ie w / S u m m e r -F a ll 1994
92 for FRASER
10
30
Maturity in years
Source: Bloomberg L.P.
*FF is federal funds rate.
I n B rief
noted that since the mid-1980s, the short-run responsiveness
How MBS
of long rates to changes in the federal funds rate has increased
S te e p e n t h e Y ie ld C u rv e
sharply. A 100 basis point increase in the funds rate caused
When long-term interest rates rise (because of policy tight
(on average) only a 15 basis point increase in the ten-year
yield in the early 1980s, but a 40 basis point or more increase
in the ten-year yield more recently (Chart 2).1In other words,
ening or other factors such as higher expected inflation),
households, in aggregate, refinance and prepay their mort
gages more slowly. For a typical mortgage pool, slower pre
when monetary policy is tightened, the yield curve now flat
payments mean that the future mortgage principal will be
tens less. Indeed, in the latest episode, it did not flatten at all.
repaid more slowly, thus extending the expected maturity of
Interestingly, the change in yield curve dynamics
the MBS and increasing its duration. This is extension risk:
coincided with large-scale structural changes in financial
slower prepayments increase the sensitivity of MBS prices to
markets, in particular the development of new financial
rising yields (see the box below).
H e d g in g U s in g T r e a s u r ie s C o u ld
instruments and the widespread securitization of home mort
Dealers in MBSs and collateralized mortgage oblig
gages.2 In 1983, less than 20 percent of the stock of residen
ations (CMOs) hold inventories of these securities, which
tial mortgage debt was securitized; by 1993, nearly 50 per
they attempt to hedge against such extension risk. One com
cent was securitized. Increased securitization has led to
mon hedging strategy used by dealers is to offset long MBS
increased use of mark-to-market accounting of mortgage
positions by taking short positions in combinations of Trea
debt, making owners of mortgage assets more sensitive to
suries that approximate the mortgage security’s duration.4
short-run rate movements.3 To the extent that mortgage
Thus as rates rise and prepayments fall, dealers must increase
securitization caused quicker adjustments of mortgage port
the duration of their Treasury hedges to roughly match the
folios to changing market conditions and thus brought closer
increasing duration of their MBS portfolios. For example, a
links between mortgage and Treasury markets, it may have
dealer hedging its MBS portfolio with short positions in two-
contributed to the change in yield curve dynamics.
to five-year Treasuries might change to a combination of five-
Chart 2
S e n s i t i v i t y o f T e n - Y e a r T r e a s u r y Y i e l d s t o C h a n g e s in t h e F e d e r a l F u n d s R a t e
R e g r e s s io n c o e f f ic ie n t
1968
70
72
74
76
78
80
82
84
86
88
90
92
94
Source: Cohen and Wenninger 1994.
Note: Chart plots coefficients from five-year rolling regressions o f monthly changes in ten-year Treasury yields on monthly changes in the federal funds rate, that is,
|3 from AlOyr = a + pAFF. Shaded areas indicate periods designated recessions by the National Bureau of Economic Research.
I n B rief
FRBNY Q u a r t e r l y R e v ie w / S u m m e r -F a ll 1994
93
to seven-year Treasuries; a short position in five- to seven-year
Treasuries might be changed to a short position in seven- to
ten-year securities. (Thirty-year bonds are not generally used
to hedge MBSs.)
sury hedges. Thus MBS hedging could cause positive feed
back or a “multiplier” effect that would further steepen the
yield curve.5
Just as dealers may use Treasury securities to hedge
As durations rise and market participants attempt to
their MBS positions, portfolio managers who hold mortgage
change their hedges simultaneously, the increase in short
securities often use the government securities market to
positions of long m aturity Treasuries should cause their
adjust their portfolios in an attempt to maintain a target
yields to rise by more than the yields of shorter maturity
duration. From a market dynamics standpoint, such portfolio
bonds, and the yield curve should steepen. The higher long
rebalancing is analogous to dealer hedging of mortgage
term yields could, in turn, reduce refinancing and prepay
inventories: as interest rates rise and mortgage securities
ment rates even further, again increasing MBS duration (and
extend, the portfolio’s duration increases. Longer duration in
its price sensitivity) and causing additional changes in Trea
turn prompts managers to sell longer maturity Treasuries to
M o r t g a g e S e c u r it y S t r u c t u r e : C all a n d E x t e n sio n R isk
Fixed rate mortgages give homeowners the option to prepay
lengthen, then the MBS is subject to “extension risk.” Slower
part or all of the mortgage loan, at any time and for any rea
prepayments mean mortgage principal is repaid later, thus
son, before the final maturity date. The prepayment option
extending the expected maturity of the MBS. Longer maturi
can dramatically affect the price sensitivity of the mortgage
ty also means that the security’s price becomes more sensitive
security because the tim ing and amount of prepayments
to rising yields. As the mortgage extends with the rising rates
change the actual life of the security.
and slower prepayments, its price falls more than it would have
Although the underlying mortgage loans often have
thirty-year terms, an MBS is never viewed as a thirty-year
had the prepayment speed remained constant (see Chart 3).
Both mortgage pass-throughs and collateralized
instrument. Mortgage market participants constantly fore
mortgage obligations (CMOs) are subject to call and exten
sion risk. By construction, however, some CMO tranches are
cast future prepayments to predict the security’s expected
life. If fast prepayments (usually due to a decline in interest
rates) cause the maturity (or duration) of an MBS or CMO to
substantially more sensitive to such risks than the underlying
pass-through, and other tranches are less sensitive. This split
shorten substantially relative to expectations, that security is
may have increased aggregate hedging related to mortgage
subject to “call risk.”
securitization.
Call risk is analogous to the risk to an owner of a
In a nutshell, call risk forces investors to reinvest in
callable bond: as interest rates fall and the price of the bond
fallin g rate environm ents, and extension risk exposes
rises, the issuer (here a household) can exercise its option and
investors to escalating price risk in rising rate environments.
call the bond at par. While there is no loss of principal in this
Hedging activity is probably greater with extension risk
case, the owner of the security must reinvest the proceeds at
because rising price risk and outright losses require a quicker
lower market interest rates.
adjustment of hedge positions than does the opportunity cost
If, on the other hand, slow mortgage prepayments
of lower reinvestment returns.
(due to rising interest rates) cause the duration of an MBS to
94 for FRASER
F R B N Y Q u a r t e r l y R e v ie w / S u m m e r -F a ll 1994
Digitized
I n B rief
regain their portfolio’s target duration. If many portfolio
1.92 percent. More realistically, the increase in rates could
managers attempt such duration adjustments simultaneous
slow prepayments from 15 percent to 10 percent per year—a
ly, the excess supply of longer maturity Treasuries will steep
en the yield curve.
move from point A to point C—and cause a larger 3-75 per
M o r t g a g e P r e p a y m e n t s a n d t h e S h if t i n
cent price decline. Alternatively, a fundamental change in the
direction of future rates could produce a large drop in prepay
ments to, say, 5 percent per year—a move from point A to
M o n e t a r y P o l ic y
point D—and a large drop in the MBS price.6
Although long rates began rising in late 1993, MBS dealers
With slower prepayments, the duration of the MBS
were slow to lower their forecasts of MBS prepayment rates
is longer as well. In Chart 3, the duration of the MBS depends
(see table below). After the change in policy direction in Feb
on the slope of the line connecting point A to one of the three
ruary, however, estimates of expected future prepayment rates
other points—whichever reflects the expected prepayment
dropped sharply, presumably because the policy change sig
speed. The effect of prepayment assumptions on duration is
naled that further declines in interest rates were unlikely. In
sizable, even for relatively small interest rate changes. A 50
fact, in 1992 and 1993, mortgage prepayment rates had been
basis point increase in rates with no change in prepayments
much higher than most dealers had anticipated, and so the
(point B) will give this MBS a duration of 3.28, or approxi
policy shift may have caused a particularly large drop in
mately that of a four-year Treasury. If the same 50 basis point
assumed prepayment speeds.
increase in rates is accompanied by a drop in prepayment
Chart 3 illustrates how critical prepayment expecta
tions are for mortgage security prices and durations. In the
speed from 15 percent to 5 percent (point D), duration
increases to 5.36, roughly that of a seven-year Treasury.
chart, we consider the relationships among price, yield, and
The table above shows that actual declines in pre
prepayment speed for an 8 percent coupon thirty-year con
payment speeds and increases in effective duration during
ventional MBS currently yielding 9Vi percent at a prepay
early 1994 were indeed quite large—of the same order of
ment speed of 15 percent (point A). As interest rates change,
different assumptions about prepayment response to the
change in yield determine both the price and the duration of
Chart 3
an MBS. For example, a 50 basis point increase in yield that
P r ic e - Y ie l d - P r e p a y m e n t S u r f a c e f o r a T y p ic a l
does not affect the speed of mortgage prepayments would
M o r t g a g e - b a c k e d S e c u r it y
lead to a move from point A to point B and a price decline of
D e a l e r P r e p a y m e n t F o r e c a s t s a n d E f f e c t iv e D u r a t i o n s
FNMA 7.5 Percent Coupon Thirty-Year Conventional MBS
“Effective”
Duration
(Years)
Prepayment
Forecast
(Percent)
Ten-Year
Yield
(Percent)
Fed Funds
Rate
(Percent)
3 .4 0
5.71
3.00
3.00
February 9 , 1 9 9 4
21.8
20.8
20.8
5 .17
3.49
3.52
5.91
3.25
March 2 3 ,1 9 9 4
4 .81
1 1 .9
6 .4 9
3.50
A pril 2 0 ,1 9 9 4
5.27
9.5
3.75
May 1 7 , 1 9 9 4
5.41
9.0
7.03
7.04
Date
October 1 5 ,1 9 9 3
January 26, 19 9 4
4.25
Source: Bloomberg L.P.
Notes: Prepayment forecasts are dealer medians quoted in PSA and converted
to conditional prepayment rates in percent. Effective durations are calculated
with dealer median prepayment forecasts using Bloomberg analytics. Dealers
include First Boston Corporation, DLJ, UBS Securities, Paine W ebber, Bear
Stearns, Sm ith Barney, Prudential Securities, M errill Lynch, Lehman Brothers,
and Salomon Brothers.
I n B rief
Note: Example is 8 percent coupon thirty-year conventional
mortgage-backed security.
FRBNY Q u a r t e r l y R e v ie w / S u m m e r -F a ll 1994
95
magnitude as those in Chart 3. Duration (for a FNMA IV2
flattening o f the long end o f the yield curve would result,
percent coupon MBS) was basically unchanged from October
however, if relatively more ten-year securities were being sold
to February, rem aining at about 3 lA years, and then rose
to hedge mortgage securities.
sharply after the policy change in February to nearly 5 Vi years
In contrast, m ortgage security hedging does not
by mid-May. Hedging this particular MBS would call for a
explain the bulge in the Treasury curve from two to five years
short position in four-year Treasuries in February but a short
over the same period. Indeed, MBS hedging should have put
position in seven- to eight-year Treasuries by May. However,
downward pressure on two-year Treasury yields in particular.
because most hedging is done w ith new-issue Treasuries, in
It seems likely that widely cited macroeconomic factors such
practice such an MBS would be hedged with three- to five-
as expectations o f higher inflation and higher future interest
year Treasuries in February and five- to ten-year Treasuries by
rates dominated movements at the short end o f the yield
May. (Issuance o f seven-year Treasury debt was discontinued
curve.
after A pril 19 9 3 , making it a less likely hedging vehicle.)
A lthough the yield curve evidence is ambiguous,
W h ile this example o f a particular MBS illustrates
daily price correlations between MBSs and Treasuries show
the duration and hedging issues, in practice, market partici
consistently stronger relationships between MBSs and longer
pants hedge entire portfolios o f MBSs and CMOs, not indi
m aturity Treasuries in early 19 9 4 . A m inimum condition for
vidual mortgage securities. Unfortunately, we have no infor
mortgage hedging to have affected the yield curve is that
m ation on the com position o f these p o rtfo lio s, so it is
MBSs should have behaved more like ten-year securities and
impossible to say exactly how durations and hedges o f MBS
less like shorter term securities from October to May. In fact,
portfolios may have actually changed in late 1993 and early
price correlations between different m aturity Treasuries and
1 9 9 4 .7 Thus we turn to more indirect evidence to try to iden
the IV2 percent FNMA in Chart 4 show just such a pattern.
tify links between the mortgage and Treasury markets.
W hen long rates began to rise in October and November, the
correlations between prices o f two-year Treasuries and m ort
E m p ir ic a l E vid ence
gage securities fell, while the correlations between the MBS
Some market participants have estimated that from October
and five-year Treasuries rose slightly.
19 9 3 to A p ril 19 9 4 , aggregate dynamic hedging o f m ort
After the policy tightening in February, correlations
gage extension risk by dealers, portfolios managers, and other
between the MBS and two-year Treasuries dropped again,
investors resulted in Treasury market sales of more than $ 3 0 0
and correlations between the MBS and the five-year Treasury
billion in ten-year Treasury equivalents. A lthough this figure
dipped slightly. In contrast, the ten-year Treasury/MBS cor
is impossible to verify, we can provide some circumstantial
relations were stable or rising in February and March. Fur
evidence that mortgage security hedging using Treasuries
ther, the tim ing o f the changes in price correlations corre
had a significant, although probably not dominant, eflfect on
sponded quite closely to that o f the increases in MBS duration
the Treasury yield movements in late 19 9 3 and early 19 94.
in the table on page 95. In late 19 9 3 , this MBS behaved like a
Because mortgages are usually hedged w ith Trea
five-year lather than a two-year Treasury. By March and A pril
suries up to ten years in maturity, but not with thirty-year
1 9 9 4 , its duration increased enough that the MBS price
Treasuries, the flattening o f the Treasury curve between ten
behaved more like that o f a ten-year than a five-year Treasury.
and thirty years seen in Chart 1 provides some evidence sup
W h ile the price correlations are consistent w ith a
porting a link between MBS hedging and the Treasury yield
relationship between MBS hedging and Treasury prices, they
curve. In particular, the spread between the ten- and thirty-
cannot tell us if such activity was actually occurring. One
year securities fell from nearly 6 0 basis points in early Febru
obvious question is whether MBS activity was really large
ary 19 9 4 to less than 2 0 basis points by early May, a flattening
enough to affect Treasury prices. Chart 5 suggests that it was.
that is very hard to explain by expectations o f higher inflation
New five- to ten-year Treasury supplies (lower right), which
or higher short-term rates over the next year or two. Such a
are most likely to be used for hedging purposes, were about
Digitized
96 for FRASER
FRBN Y
Q u a r t e r l y R e v ie w / S u m m e r - F a ll
1994
I n B rief
$45 billion a quarter during 1993, while dealer inventories of
MBSs, both pass-throughs and CMOs, were $50 billion or
lateral market for a particular Treasury issue because the
holder of the collateral pays the repo rate.
more in late 1993 and early 1994.8
Comparing the outstanding amounts of Treasury
and mortgage securities at year-end 1993 provides further
Chart 5
evidence that the mortgage market was large enough to affect
the Treasury market. In fact, private holdings of Treasury
D e a l e r P o s i t io n s in M o r t g a g e - b a c k e d S e c u r it i e s a n d
C o l l a t e r a l iz e d M o r t g a g e O b l ig a t io n s
marketable debt maturing in two to ten years were smaller
($964 billion) than outstanding securitized agency mortgage
B i l l io n s o f d o l l a r s
70
MBS Pass-throughs
debt ($1,350 billion).
CMOs
Perhaps the most direct information on the demand
for Treasury securities for hedging purposes comes from the
repurchase agreement market for Treasury collateral—the
“repo” market. The holder of Treasury collateral pays the repo
rate to the party seeking to borrow the collateral (often for
delivery against short sales in the cash market). A short seller
Quarterly Issuance of Treasury Debt
(Approximate)
usually borrows a specific Treasury issue to meet its cash mar
ket delivery obligations.
Two-year
Three-year
Five-year
Ten-year
The repo rate for general collateral (that is, any
maturity Treasury) is similar to other overnight interest rates.
$51
$17
$33
$ 12
billion
billion
billion
billion
m in im u m
However, imbalances between supply and demand for specif
M
ic Treasury issues are reflected in issue-specific repo rates.9
1993
For example, low repo rates reflect excess demand in the col
Source: DRI/McGraw-Hill.
M
1994
Chart 4
P r ic e C o r r e l a t io n s : M o r t g a g e - b a c k e d S e c u r it ie s a n d T r e a s u r ie s
FNMA 7.5 Percent Coupon w ith Two-, Five-, and Ten-Year Treasury Securities
C o r r e l a t io n
1993
1994
Source: DRI/McGraw-Hill.
Note: Chart plots twenty-day lagged rolling price correlations.
I n B rief
F R B N Y Q u a r t e r l y R e v ie w / S u m m e r -F a ll
1994
97
Repo rates for particular maturities are commonly
presented as spreads relative to the rate for general collateral.
A high repo spread (that is, low repo rate) can be interpreted
as the financing premium that a short seller must pay in order
to borrow a particular maturity Treasury security overnight.
(Chart 8) but no clear pattern that can be related to MBS
hedging. Furthermore, it is difficult to extract information
about hedging activity from movements in the open interest
for the thirty-year bond contract because daily trading vol
ume is particularly high relative to open interest.14 The high
Repo spreads for the most recently issued or “onthe-run” Treasuries are shown in Chart 6.10 Spreads for the
first four months of 1994 are consistent with high demand for
Chart 7
progressively longer dated Treasuries, presumably stemming
U .S . T r e a s u r y F i v e - a n d T e n - Y e a r N o t e F u t u r e s
Open Interest
from efforts to counteract mortgage security extension risk.
Spreads widen first for five- and seven-year maturities and
T h o u sa n d s o f c o n t r a c t s
350
,'V~' \
then for the ten-year maturities.11
Further evidence of increased hedging activity can
/
300
/. I
be seen in Chart 7, which shows open interest in the five- and
Ten-year
ten-year Treasury futures market from the beginning of
1994.12 These data support the repo data: open interest
V
250
\
•K>
\ S * V.
\
/V'
<w
-N.
increased first for the five-year contract and then for the tenyear contract as rates continued to rise.13 Moreover, the
200
Five-year
increase in open interest for the ten-year contract corre
sponded closely to the high and sustained financing premium
150 L
M
in the ten-year repo market through April.
M
19 94
In contrast, open interest for thirty-year bond
futures shows a m ild upward trend during the period
Sources: Chicago Board of Trade; DRI/McGraw-Hill.
Notes: Each contract has a $ 100,0 00 face value.
Chart 6 .
S e l e c t e d T r e a s u r y “R e p o ” S p r e a d s
B a s is p o in t s
350
1994
Source: Federal Reserve Bank of New York.
Note: Chart shows the general repurchase agreement rate minus the rate on each specific maturity.
98
F R B N Y Q u a r t e r l y R e v ie w / S u m m e r -F a ll 1994
I n B rief
Chart 8
in mortgage security hedges and realignments of portfolios in
U.S. T r e a s u r y
response to longer MBS durations had a significant effect on
T h ir t y - Y e a r B o n d Fu t u r e s
Volume and Open Interest
T h o u san d s o f c o n tr a c ts
800 ---------------------------------------------------
the Treasury yield curve, particularly after the change in
monetary policy direction in February 1994. Although MBS
hedging certainly cannot explain all the shifts in the yield
curve in early 1994, some macroeconomic evidence does sup
port the relationship: the flattening of the ten- to thirty-year
spread in early 1994 and the increased (short-run) sensitivity
of long rates to changes in short rates. In addition, estimates
of mortgage prepayments and durations, evidence on MBS
and Treasury prices and volumes, and information from the
repo and futures markets all suggest that the hedging of
mortgage security extension risk was widespread and had a
significant impact on the short-run movements of the Trea
1994
sury market, particularly the ten-year market.
Sources: Chicago Board of Trade; DRI/McGraw-Hill.
Although there is no evidence that hedging activity
Notes: Each contract has a $ 10 0 ,0 0 0 face value.
has affected the long-run relationship between long-term and
volume reflects a high level of intraday trading and hedging,
short-term interest rates, this latest episode is further evi
which is unlikely to be related to the MBS market.
dence that the short-run dynamics of the yield curve have
changed over the last decade. As a result, the transmission of
Sum m ary
monetary policy from short-term interest rates to the real
The circumstantial evidence presented above, as well as wide
economy via long-term interest rates has probably changed
spread reports from market participants, suggests that shifts
as well.
I n B rief
F R B N Y Q u a r t e r l y R e v ie w /S u m m e r -F a ll 1994
99
1. In addition to using the simple regression evidence presented in Chart 2,
Note 5 continued
Cohen and Wenninger (1994) estimate more complicated time series mod
duration bonds, putting more downward pressure on long-term yields in
els of the term structure to show an increase in the short-run sensitivity of
the short run.
long rates to short rates.
6. The slowing in prepayments exacerbates the effect that rising rates have
2. The m id -1980s change in yield curve dynamics may also have been a
on the price of the MBS because the repayment o f mortgage principal
delayed reaction to the 19 7 9 change in Federal Reserve policy regime
occurs over a longer period.
toward a stronger anti-inflation stance.
7. In addition, some CMO tranches, by construction, contain substantial
3. Mortgage securitization may have contributed to the greater sensitivity
ly more extension risk than MBS pass-throughs and involve more compli
o f long-term interest rates to short-term interest rates by moving residen
cated relationships between yield changes, prepayments, and duration than
tial housing finance away from financial intermediaries and directly into
is suggested by Chart 3- For such securities, Chart 3 and the table on page
financial markets. Before mortgage securitization, a rise in short-term rates
95 may underestimate changes in durations and thus changes in hedges.
hurt the cash flows o f financial intermediaries who held mortgages. But
because mortgages were not marked to market, intermediaries were proba
8. We focus on dealer inventories of mortgage securities because they are
bly slow to adjust their asset portfolios to reflect the decline in mortgage
the most likely to be dynamically hedged.
values. This slow portfolio adjustment meant that any feed-through to
long-term interest rates tended to be indirect and slow. W ith the advent of
9. W hen the repo rate for a specific Treasury issue diverges from the repo
mortgage securitization, however, the majority of mortgages are no longer
rate for general collateral, it is said to be “on special” or “special-”
held on bank balance sheets but in MBSs, which are marked-to-market
daily and, in many cases, dynamically hedged. Further, portfolios contain
10. On-the-run Treasuries provide the best liquidity for hedgers.
ing mortgages are adjusted more quickly, and as a result, the adjustment of
long rates to short rates is probably quicker as well.
11. Because the last seven-year Treasury was issued in A pril 19 9 3 , the
“seven-year Treasury” in Chart 6 is actually a six-year security during this
4. Dealers who attempt to hedge MBSs using offsetting Treasury positions
period.
are, by definition, using imperfect hedges. Because o f the implicit pathdependent optionality and negative convexity of MBSs, hedges must be
12. Open interest is the net number of outstanding futures contracts.
adjusted dynamically as market conditions change. See the box on page 94.
13. Increases in open interest suggest that market participants have estab
5. This process is probably somewhat symmetric. W hen interest rates
lished more permanent positions, and thus these increases may be inter
fall, durations and maturities of MBSs shorten and MBSs are subject to
preted as evidence o f greater hedging activity within the futures market.
call, or refinancing, risk (see the box on page 94). To hedge such call risk,
market participants could sell shorter duration Treasuries and buy longer
14. For the five- and ten-year futures, daily volume is one-third to one-half
o f open interest.
Cohen, GeraldD., andJohn Wenninger. 1994. “The Relationship between the
Federal Funds Rate and Economic Activity.” Federal Reserve Bank of
New York Research Paper no. 9406.
Digitized
F R B N Y Q u a r t e r l y R e v ie w / S u m m e r -F a ll 1994
100 for FRASER
N o tes
Has Excess Capacity Abroad Reduced U.S.
Inflationary Pressures ?
James A . Orr
W 7 t ttt r?
W tllL Z
U.S. manufacturing capacity utilization has
U.S. demand, used their available capacity to expand produc
been rising in recent years, capacity utilization in the manu
tion w ithout increasing their prices significantly.1 Import
facturing sectors o f the major foreign industrial economies
prices that remained flat or rose more slowly than the prices of
has declined. Falling utilization rates abroad have given for
domestically produced goods would slow U.S. inflation in
eign firms the potential to expand production without incur
two ways: directly, as the imports entered into U.S. consump
ring significant cost increases. This article investigates
tion, and indirectly, as the imports siphoned off increases in
whether sizable slack abroad, which has helped to slow for
U.S. demand and thus restrained price increases by compet
eign inflation, could also have eased U.S. inflationary pres
ing U.S. firms.2
A significant amount o f excess capacity exists in the
sures by preventing the prices o f imports from rising as fast as
the prices o f U.S.-produced goods.
manufacturing sectors o f Japan, Canada, Germany, France,
The analysis shows th at grow ing foreign excess
Italy, and the U nited K ingdom , countries that together
capacity has provided only a lim ited amount o f protection
account for more than one-half o f all U.S. imports. Although
against domestic inflationary pressures. Although inflation
aggregate foreign manufacturing capacity utilization in these
abroad has been lower than U.S. inflation, exchange rate
economies increased slightly in the first half o f this year, it
changes have exceeded the inflation differentials and exerted
declined more than 10 percent between the end o f 19 9 0 and
significant and varied influences on import prices. For exam
the beginning o f 1 9 9 4 (Chart 1). In two previous downturns,
ple, dollar depreciation against the yen has erased the depres
capacity utilization abroad reached even lower levels, but the
sing effects on prices o f significant excess capacity in Japan,
decline for the past several years is p a rticu larly notable
w hile dollar appreciation against the Canadian dollar has
because it occurred as U.S. capacity utilization was rising
greatly enhanced the effects o f moderate excess capacity in
sharply.
Canada. Aggregated across all sources, import price growth
The available evidence shows that growing excess
has roughly kept pace with U.S. inflation. Moreover, in U.S.
m anufacturing capacity abroad, among other factors, has
manufacturing industries nearing full capacity, imports have
exerted downward pressure on the prices o f foreign manufac
not seized an increasing share o f the market, a development
tured products expressed in local currency.3 Foreign producer
that one would expect if foreign excess capacity were going to
prices have risen more slowly than U.S. prices. In fact, pro
influence U.S. pricing decisions significantly. Consequently,
ducer prices in Canada and W estern Europe have lagged
the analysis concludes that the mere presence of excess capacity
growth in U.S. producer prices by roughly 2 percent since the
abroad has not greatly restrained U.S. inflationary pressures.
end o f 1 9 9 0 (Chart 2). During the same period, Japanese
prices have lagged U.S. price growth by almost 10 percent.4
S l a c k C a p a c it y A b r o a d a n d I m po r t P rices
Nevertheless, although excess capacity abroad has
Excess capacity abroad would relieve inflationary pressures in
helped to lower the local currency prices o f foreign manufac
the U.S. economy if foreign suppliers, responding to growing
tured goods relative to U.S. prices, other factors affect the
I n B rie f
F R B N Y Q u a r t e r l y R e v i e w /S u m m e r -F a l l
1994
101
U.S. dollar price of imports—specifically, changes in the
exchange rate and the extent to which these changes are
passed through by foreign suppliers to U.S. consumers.5
ments (Chart 3). Even with only part of the change in nomi
nal exchange rates being passed through into import prices,
exchange rate movements largely undercut the potential ben
Movements in the nominal value of the dollar against the cur
efits of relatively lower inflation rates abroad. From 1990
rencies of key industrial countries have far exceeded the mod
through the second quarter of 1994, dollar prices of U.S.
erate slowing in their producer prices relative to U.S. pro
manufactured imports from Japan rose roughly 6 percent
ducer prices. Since the end of 1990, the dollar has appreciated
compared with the prices of U.S. manufactured goods. This
more than 15 percent against the Canadian dollar and 16 per
rise was consistent with the combination of a 10 percent fall
cent against an average of Western European currencies,
in Japanese local currency prices relative to U.S. prices and a
while depreciating 25 percent against the Japanese yen.6
20 percent nominal appreciation of the yen. The exchange
Dollar appreciation against the Western European and Cana
rate movement thus overwhelmed the potential benefits of
dian currencies has thus augmented their modestly lower
Japan’s excess capacity for U.S. inflation. The dollar prices of
inflation rates; by contrast, dollar depreciation against the
manufactured imports from Western Europe and Canada fell
yen has more than offset Japan’s sizable decline in producer
roughly 7 percent against the prices of U.S. manufactured
prices relative to U.S. producer prices.
goods, a decline that was much more than the relative fall in
Direct evidence on the prices of manufactured
imports from industrial countries compared with U.S. pro
their local currency producer prices but consistent with their
nominal currency depreciations of more than 10 percent.
ducer prices between the end of 1990 and m id-1994 bears
Overall, prices of imports from industrialized coun
out the significance of exchange rates for import price move
tries grew only 1 percent less than U.S. prices between 1990
Chart 1
M a n u f a c t u r in g C a p a c it y U t il iz a t io n
In d e x : 1 9 9 0 = 10 0
P
ercent
Notes: The index of capacity in foreign industrialized economies is an import-weighted average of the utilization rates in Japan, Germany, France, the
United Kingdom, Canada, and Italy. The 1994 utilization rates for France and Italy are estimates.
102
F R B N Y Q u a r t e r l y R e v ie w / S u m m e r -F a ll 1994
I n B r ie f
and m id-1994.7 Slack capacity alone, without any changes in
slack capacity abroad is easing inflationary pressures where
exchange rates, would likely have caused import prices to fall'
U.S. capacity strains are most concentrated. It is in these
perhaps 5 percent more than U.S. prices— a difference that
industries that we would expect to see import price growth
was roughly equal to the gap between foreign and U.S. pro
lagging U.S. price growth even if it did not show up in aggre
ducer price inflation. However, largely because of exchange
gate import prices.
rate changes, the rise in the relative dollar price of imports
The results of the import price comparisons for these
from Japan offset a large part of the decline in the dollar price
industries are mixed. Prices of imported primary metals and
of imports from Western Europe and Canada and hence lim
industrial machinery have not risen as fast as U.S. producer
ited overall relative import price declines.
prices in these industries (Chart 4). The steady decline in the
relative price of imported primary metals since early 1992 is
I m p o r t P r ic e s
in
S e l e c t e d In d u s t r ie s
broadly consistent with the continued expansion of excess
Several U.S. manufacturing industries that reached or were
capacity abroad and the increased utilization of U.S. manu
nearing previous peak capacity utilization rates during the
facturing capacity. However, unlike primary metals, indus
second quarter of 1994 have also had a large share of imports
trial machinery imports exhibited a sharp decline in relative
from industrialized countries. These industries include auto
price in the first half of 1991, when significant foreign excess
m obiles, prim ary m etals, and electrical and industrial
capacity was only beginning to appear and U.S. capacity uti
machinery.8 Import prices that have been flat or falling rela
lization was not particularly tight. Since the end of 1991, the
tive to U.S. prices in these industries would indicate that
price of imported industrial machinery has kept pace with
Chart 2
T rends
in
R e l a t iv e P r ic e s
I n d e x 1990: Q 4 = io o
and
D o lla r E x c h a n g e R a tes
I n d e x 1990: Q 4 = io o
r........................ .....................
N ominal Dollar Ex :hange Rates
^
Japan
A
w
\
A
•
1
r m
*
v \
V
Canada
V.
_
\-
/
........ L
1990
i
91
i
*»''
L
i - J ___
92
-
>
-
Western
Europe
\
\.
_
1
93
1
1
94
Notes: The left panel plots the ratios of foreign wholesale price indexes (the producer price index for Japan) to the U.S. producer price index for finished goods. The
right panel plots the indexes of the foreign currency price of the U.S. dollar: a rise signifies dollar depreciation. The index of relative prices and exchange rates for
Western Europe is an import-weighted average of relative prices and exchange rates in Germany, France, Italy, and the United Kingdom.
I n B r ief
F R B N Y Q u a r t e r l y R e v ie w / S u m m e r - F a ll 1994
103
the price of domestically produced industrial machinery, sug
inflationary pressures by enabling imports to capture an
gesting that growing foreign excess capacity has not eased
increasing share of growing U.S. domestic demand. Import
inflationary pressures in this industry.
market shares in autos have remained constant or declined
No significant declines have occurred in the prices of
slightly since 1990 (Chart 5). The same pattern holds for pri
imported road vehicles, largely autos, or electrical machinery
mary metals, despite the steady fall in the relative prices of
compared with U.S. prices to date. In fact, in these industries,
these imports. Although import market shares in both cate
import prices have risen slightly more than U.S. domestic
gories of machinery have increased since 1990, neither the
prices since 1990. Japan is an important supplier of both
timing nor the magnitude of the rise in import market share
products, and the failure to observe any relative price declines
appears linked to the growth in excess capacity in foreign
could be related to the yen’s appreciation since 1990.
industrialized economies since 1990. Rather, the rise in the
These same four industries offer little broad-based
past several years essentially continues the trend increase in
evidence that foreign excess capacity has held down U.S.
import penetration in these industries that appeared before
1990. This longer term rise in import penetration, particu
larly in the electrical machinery industry, in part represents
the steady expansion of capacity in developing economies.
Chart 3
R a t io
of
Im p o r t P r ic e s
to
Therefore, despite the relative importance of imports in
U .S . P r i c e s
domestic consumption in these four sectors, the data do not
I n d e x 1990: Q 4 = 100
106
•••
•
•
104
show that growing excess capacity abroad has caused a signif
Japan
icant increase in the penetration of the U.S. market by foreign
•
•
•
•
•
102
100
•
rA
+•
%
Growing excess capacity in industrialized countries since
*
»
98
•
suppliers in the past several years.
1 ♦
A t ••
•M \A
tW
V
96
Foreign
industrialized —
economies
\
94
from inflationary pressures in the U.S. economy. The price of
U.S. imports from industrialized countries relative to U.S.
Western
Europe
' v '"
1990 has provided at best a limited amount of protection
prices has declined only modestly as lower inflation abroad
V,
has been offset by exchange rate changes. Dollar depreciation
in the case of Japan has rendered excess capacity there basi
92
Canada
1
90
1990
1
91
1
1
1
92
1
1
1
cally ineffective against U.S. inflationary pressures.
1
93
1
1
1
1
94
Source: U.S. Department of Labor, Bureau of Labor Statistics.
Notes: Chart plots the ratios of import price indexes to the U.S. producer
price index for manufactured goods. The index for the group of foreign
industrialized economies is the average, weighted by U.S. imports, of the
individual indexes for the European Community nations plus Japan, Canada,
Australia, New Zealand, and South Africa. The Western Europe index
includes the twelve economies of the European Community.
104
F R B N Y Q u a r t e r l y R e v ie w / S u m m e r - F a l l 1994
In the years ahead, the strengthening expansions in
the United Kingdom and Canada as well as the beginnings of
recovery in continental Europe and Japan will increase the
utilization of foreign manufacturing capacity. Consequently,
the likelihood that excess capacity abroad will offer future
inflation relief appears limited.
I n B r ie f
Chart 4
R
Im p o r t P r i c e s : S e l e c t e d I n d u s t r i e s
e l a t iv e
I n d e x 1990: Q 4 = i o o
I n d e x 1990: Q 4 = io o
104
A
A
*
i
/
^ -v k /
---- v / l / '
K «
\
102
\
/ 1
00
f t
t
j
I
\
\
\>
Road
vehicles
/
J
--J•J
%
1/ / I
4.... /
1
\
\
\
\
. _____ i ____
98
.......
96
1
1
1
1
1
............i
\
Primary
metals
/
y
94
_ Jl
j ___ 1
1991
_
:
L
I -i
92
> :£ ll
!
j
93
1
94
I
1
Notes: Chart plots the ratio of import prices to the U.S. producer price index for each industry.
Chart 5
Im p o r t M a r k e t S h a r e : S e l e c t e d In d u s t r ie s
P ercen t
Percen t
35
30
\
1
V
25
20
15
\
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V
/St...
V
10
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%
Road
vehicles
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1986
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Primary me tals
1 1 1 1 111
87
89
_ L J J !..i L i ’-': *112. Li. l..J_ I I I
92
94
93
90
91
Notes: Chart plots the ratio of imports to domestic demand. Domestic demand is defined as shipments plus imports less exports.
I n B r ie f
F R B N Y Q u a r t e r l y R e v ie w / S u m m e r - F a ll 1994
105
E
ndno tes
1. The threat of a surge in imports could also cause workers to hold back
wage demands or firms to hold off price increases.
Note 5 continued
10 percent dollar depreciation would raise import prices by roughly 6 to 7
percent.
2. Imported consumer goods account for roughly 8 percent of U.S. con
sumption expenditures.
6. Between the end of 1990 and m id-1994, the dollar appreciated 12 percent
against the deutsche mark, 10 percent against the French franc, and more
3. Phillips curve models of inflation use measures of the level or change in
than 20 percent against the currencies o f Italy and the United Kingdom.
the degree of resource utilization as one factor explaining price movements;
other factors include changes in energy and raw materials prices.
7. Assuming imports account for roughly 8 percent o f total consumption
expenditures, this 1 percent decline in the growth of import prices relative
4. Producer price inflation in Italy and the United Kingdom has exceeded
to the growth of domestic prices since 1990 would have had a negligible
U.S. producer price inflation since the end of 1990, while producer price
impact on U.S. inflation, slowing price growth by less than 0.1 percentage
inflation in France and Germany has trailed U.S. inflation over the same
point over 1990-94.
period.
8. Capacity utilization rates in these industries were below 1975-80 peak
5. Most model estimates show that a change in foreign producer prices
rates but near or above 1983-90 peaks. Slower auto output in second-quar-
changes the prices of U.S. imports by roughly an equal amount; that is, a
ter 1994 did reduce capacity utilization 9 percentage points from its high
10 percent drop in prices abroad would cause a 10 percent decline in U.S.
first-quarter rate, but the rate is still within 2 percentage points of its
import prices. However, only about 60 to 70 percent of a change in nomi
1983—90 peak. Foreign capacity utilization rates for these industries are
nal exchange rates is estimated to be passed through to import prices, so a
not available.
Digitized1 for
0 6 FRASER
F R B N Y Q u a r t e r l y R e v i e w / S u m m e r - F a ll 1994
N otes
Recent Trends in the Profitability of
Credit Card Banks
Andrea Meyercord
card lending has traditionally been a highly
average annual return on assets. Chart 1 traces the weighted
profitable line of business for banks. Increased competitive
average return on assets over the years 1989 to 1994 for all
pressures in recent years, however, have prompted many card
credit card banks with total assets of $200 million or more.2
issuers to reduce interest rates, lower or waive annual mem
The data through 1993 measure the returns as of year-end;
bership fees, provide program enhancements, and offer rebate
the 1994 return is estimated by annualizing first-quarter fig
programs to make their plans more attractive. Despite these
ures. The chart shows that the average return on assets for
developments, the profitability of “credit card banks,” or
credit card banks has been relatively high over the years
banks specializing in credit card operations,1 not only
examined. As a point of contrast, whereas the average return
remains high relative to the rest of the banking industry but
for credit card banks ranged from 1.9 percent to 3.4 percent
also continues to grow.
during the 1989-93 period, all other U.S. commercial banks
This article analyzes recent trends in credit card
within the same asset size category had an average return on
bank profitability and the factors underlying them. Evaluat
assets ranging from 0.4 percent to 1.1 percent in the same
ing the trends only in the aggregate, however, would ignore
period.
some interesting differences in profitability between two dis
Chart 1 also reveals that the average return on assets
tinct groups of institutions. The first group consists of credit
for credit card banks has been steadily increasing since 1991.
card banks owned by bank holding companies (BHCs), a rel
This rising trend in profitability is particularly notable given
atively well-established market segment. The second group
that the spread between card issuers’ lending rates and their
comprises credit card banks owned by nonbank firms, a more
funding costs has been shrinking since early 1992. Compar
recent and fast-growing component of the credit card market.
ing the average credit card rate of U.S. card issuers3 with the
The article finds that despite growing competition
one-year Treasury note rate— a conservative benchmark for
from nonbank-owned credit card issuers, the return on assets
issuers’ cost of funds— indicates that, overall, issuers’ mar
of the more “traditional” issuers— those owned by BHCs—
gins decreased from 14.1 percent in February 1992 to 12.7
increased significantly over 1992-93 and continues to exceed
percent in February 1994. Although both lending rates and
that of nonbank-owned credit card banks. BHC-owned insti
funding costs fell over this period, the decline in lending
tutions have proved more profitable than their nonbank-
rates exceeded the decline in funding costs, resulting in a
owned counterparts largely because better asset quality
contraction in the overall funding margin.
trends in recent years have enabled them to maintain a lower
level of provisions for loan losses.
P r o f it a b il it y a t B H C - o w n e d a n d
N o n b a n k - o w n e d C r e d it C a r d b a n k s
A g g r e g a t e P r o f it a b il it y T r e n d s o f
The aggregate trends presented in Chart 1 conceal some
C r e d it C a r d B a n k s
notable differences between the levels of profitability exhib
The profitability of credit card banks can be measured as an
ited by BHC-owned credit card banks and those observed for
Digitized
I n B rfor
ie f FRASER
FRBNY Q u a r t e r l y R e v ie w / S u m m e r - F a ll 1994
107
nonbank-owned credit card banks. Such differences are of
credit card issuers (ranked on the basis of total credit card
particular interest since these two groups are direct competi
loans outstanding at the credit card subsidiaries of BHCs,
tors in the credit card business.
thrifts, and nonbank diversified financial services companies),
Increased competition from nonbank-owned issuers
the share of outstandings held by nonbank-owned issuers
is a recent and important development in the credit card mar
grew from approximately 24 percent in 1991 to 37 percent in
ket. Although the Bank Holding Company Act of 1956 pro
1993 (Chart 2). In part, this trend reflects the recent entry
hibited nonbank companies from owning banks, in the early
into the credit card market of firms like AT&T, General Elec
1980s several nonfinancial firms found that they could con
tric Capital Corporation, First USA, ADVANTA Corpora
duct credit card business by acquiring so-called nonbank
tion, and Ford Motor Company. The number of such non
banks. Since nonbank banks limit their operations to either
bank-owned institutions figuring among the twenty-five
deposit taking or lending, they did not legally meet the Bank
largest issuers rose significantly around this time, increasing
Holding Company Act’s definition of a “bank” as an institu
from five in 1990 to ten in 1993. In addition to making
tion that engages in both activities, and thus were not subject
entry-related gains, nonbank-owned issuers have also cap
to the act’s restrictions on bank ownership. The Competitive
tured market share through increased lending, both by origi
Equality Banking Act of 1987 addressed this exception by
nating credit card loans themselves and by acquiring the
amending the definition of a “bank” and banning new non
credit card portfolios of other issuers.
bank bank charters. However, the 1987 act exempted credit
Decomposing the data for all credit card banks
card banks and a few other special purpose banks from the
reveals a difference in the general level of profitability of the
new definition of a “bank.” Thus, since 1987, the number of
BHC-owned and nonbank-owned subsets. Chart 3 adds to
nonbank-owned commercial banks that specialize in credit
the aggregate trend shown in Chart 1 two more series depict
card lending has surged.4
ing the profitability trends of these subsets of the credit card
Over the past few years, nonbank-owned issuers
bank population.5 Despite the competitive challenges posed
have gained substantial market share at the expense of more
by nonbank-owned issuers, the average return on assets for
traditional BHC-owned issuers. Among the top twenty-five
Chart 2
M a rket Share
Chart 1
A ggregate T
r e n d s in
C r e d it C a r d B a n k P r o f it a b il it y
Per c en t
of
N
o nbank
C r e d it C a r d Is s u e r s
o f o u t s t a n d in g s
40 ----------------------------------------------------------------------------------Per c en t
5 -----------------------------------------------------------------------------------
i
i_________ ! _______ i__________________i---------------------------- 1----------------------------1---------------------------- 1---------------------------
1989
90
91
92
93
94e
Source: Federal Financial Institutions Examination Council,
Reports of Condition and Income.
Notes: Chart shows the weighted average return on assets for all credit card
banks with total assets of $200 million or more. The data through 1993
measure the returns as of year-end; the 1994 return is estimated by
annualizing first-quarter figures.
Digitized108
for FRASER
F R B N Y Q u a r t e r l y R e v ie w / S u m m e r - F a ll 1994
1988
89
90
91
92
93
Source: American Banker.
Notes: Market share figures are based on the total credit card loans out
standing at the commercial bank and thrift subsidiaries of the top twentyfive credit card issuers. The data for 1991-93 include securitized credit card
loan figures derived from the Reports of Condition and Income. Banks began
reporting securitization figures in the September 1991 Call Reports.
I n B r ief
BHC-owned credit card banks was 4.1 percent in 1993,
the average return on assets of the nonbank-owned subset in
almost double the level reported by nonbank-owned credit
1994 drops from 4.1 percent to 2.9 percent.
card banks. Moreover, the returns of BHC-owned institu
The primary factor driving the higher level of pro
tions grew by 1.3 percentage points from 1992 to 1993, a
fitability exhibited by the BHC-owned segment has been a
larger rise than the increase exhibited by nonbank-owned
significantly lower level of provisions for loan losses relative
issuers. First-quarter 1994 results suggest that the average
to the nonbank-owned subset. Chart 4 tracks provisions as a
return on assets for BHC-owned credit card banks remains
percent of total loans from 1989 to 1994 for both BHC-
higher than that for nonbank-owned institutions.
owned credit card banks and nonbank-owned credit card
Chart 3 includes a fourth series describing the
banks. Although the ratio of provisions to loans has followed
returns of all nonbank-owned credit card banks except the
a similar trend at both subsets, peaking in 1992 and subse
Greenwood Trust Company, a sizable institution that largely
quently falling, this ratio has consistently been higher at the
drives the results of this subset. This series demonstrates that
nonbank-owned subset in the time period examined. In
although the average returns of nonbank-owned credit card
1993, the provisions ratios of BHC-owned credit card banks
banks appear to have increased substantially from the end of
and of their nonbank-owned counterparts were 2.9 percent
1993 (and by more than the increase exhibited by BHC-
and 5.5 percent, respectively. First-quarter data for 1994
owned credit card banks), most of this trend is actually
indicate that provisioning remains significantly higher at the
attributable to a marked increase in the returns of Greenwood
nonbank-owned subset.
Underlying the provisioning behavior of BH C-
Trust Company.6 If Greenwood Trust Company is excluded,
owned credit card banks in recent years are more favorable
loan quality and loan loss trends. The BHC-owned subset has
faced a smaller percentage of past-due loans and net chargeChart 3
offs relative to total loans than have nonbank-owned credit
S u bsa m ple T
r e n d s in
C r e d it C a r d B a n k P r o f it a b il it y
card banks since 1991 (see table on next page). One possible
Percen t
4.5
BHC-owned
Chart 4
P r o v is io n s
as a
Percen tage
C r e d it C a r d B a n k s
and at
of
N
T o ta l Lo an s
o n b a n k -o w n e d
at
B H C -o w n ed
C r e d it
C ard B a n k s
P ercen t
8
1.0
I_____________ I_____________ I_____________ 1_____________ I_____________ I_____________ I
1989
90
91
92
93
94e
Source: Federal Financial Institutions Examination Council, Reports of
Condition and Income.
Notes: Chart shows the weighted average return on assets for all credit card
banks with total assets of $200 million or more. The data through 1993
measure the returns as of year-end; the 1994 return is estimated by
annualizing first-quarter figures. Most of the increase in returns exhibited by
nonbank-owned credit card banks from 1993 to 1994 was driven by
Greenwood Trust Company, the second largest institution within this subset
in terms of assets. A series has been added to show the return on assets for
nonbank-owned credit card banks excluding Greenwood Trust Company.
I n B r ief
2 i____________ i____________ l____________ 1____________ I____________ I____________ I
1989
90
91
92
93
94e
Source: Federal Financial Institutions Examination Council,
Reports of Condition and Income.
Notes: The data through 1993 measure provisions as of year-end; the 1994
value is estimated by annualizing first-quarter figures.
F R B N Y Q u a r t e r l y R e v ie w / S u m m e r - F a ll 1994
109
reason for the more severe credit quality problems of the non
“bank issuers are continuing to lose share to nonbank players
bank-owned issuers is that in pursuit of market share, these
[because] many banks continue to lack a differentiated con
institutions may have marketed their credit card accounts
sumer status with their cards”; in contrast, nonbank issuers
more aggressively by, for example, offering better terms.
such as ADVANTA, American Express, and Dean Witter,
Consequently, they may be attracting a greater proportion of
Discover and Company have “aggressive pricing/balance
high-credit-risk customers than are BHC-owned issuers.
transfer/credit line product offerings.” Other research (Can-
Although an analysis of customer risk characteristics
ner and Luckett 1992) suggests that “nonbank firms have
at BHC-owned and nonbank-owned credit card banks is
garnered significant market shares, in part by differentiating
beyond the scope of this article, some anecdotal evidence sup
their plans by forgoing annual fees or by offering rebates on
ports the idea that nonbank-owned issuers may be pursuing a
purchases or discounts on selected services.” Finally, a recent
more aggressive strategy to attract customers. For example,
Report to Congressional Requesters by the U.S. General
one set of market analysts (Liss and Rhei 1994) argues that
Accounting Office (1994) contends that “nonbank entrants
may be more comfortable than depository institutions with
P a st - D u e L o a n s
T otal Lo a n s
at
and
N
et
C h a r g e -o f f s
1993
1994
Percen tage
of
C r e d it C a r d B a n k s
Past-Due Loans
NonbankBHCowned
owned
(Percent)
(Percent)
1989
1990
1991
1992
as a
4.78
5.25
6.19
5.17
4.29
4.18
7.42
6.68
5.14
4.23
3.56
3.34
lower interest rates and earnings because their primary reason
for issuing credit cards was to increase volume in their tradi
Net Char#e-offs
NonbankBHCowned
owned
(Percent)
(Percent)
2.93
4.42
5.08
6.05
3.89
3.49
3.27
3.60
4.20
4.47
3.19
3.40
Source: Federal Financial Institutions Examination Council, R eports o f
Condition and Incom e.
Note: The 1994 past-due loan values are first-quarter figures. The 1994
net charge-off values are estim ated by annualizing first-quarter figures.
110
F R B N Y Q u a r t e r l y R e v i e w / S u m m e r - F a ll 1994
tional lines of business.”
In sum, notable differences in the levels of profitabil
ity at credit card banks exist on the basis of ownership struc
ture. A comparison along these lines suggests that growing
competition from nonbank-owned issuers has not yet signifi
cantly curtailed the profitability of BHC-owned credit card
banks, which has continued to rise over the past two years. As
nonbank issuers evolve into more mature, established players
in the credit card market, they may pose a more serious com
petitive threat to BHC-owned institutions.
I n B r ie f
E
ndno tes
1. This analysis defines a “credit card bank” as an institution allocating 90
Note 4 continued
percent or more of its total loan portfolio to credit card loans. Because the
After the act was passed, the number of nonbank-owned credit card banks
Federal Financial Institutions Examination Council s Reports of Condition
(commercial banks) roughly doubled, to twenty-six banks.
and Income do not break out all expenses and revenues by specific product
lines, this definition allows one to use the reports to assess the profitability
5. The BHC-owned subset ranges in size from thirteen to seventeen insti
of banks established primarily to issue and service credit card accounts.
tutions from 1989 to 1994. The nonbank-owned subset ranges in size from
nine to seventeen institutions over the same period and includes both non
2. The returns are calculated using on-balance-sheet assets. The sample
bank banks and commercial banks.
ranges in size from tw enty-four to thirty credit card banks over the
1989-94 period.
6. Greenwood Trust Company is a $6.7 billion nonbank bank that issues
3. The average rate is reported in Federal Reserve Statistical Release G. 19,
accounts for roughly a quarter o f the total loans held by the nonbank-
a quarterly survey of the most common rates charged by a sample of com
owned credit card bank subset. The increase in Greenwood Trust Compa
the Discover Card for Dean Witter, Discover and Company and that alone
mercial banks during the first week of each midquarter month.
ny’s return on assets from the end o f 1993 to the first quarter o f 1994
stemmed from a 72.6 percent rise in net income (driven primarily by an
4. Before the passage o f the Com petitive Equality Banking Act, only
increase in noninterest income) and a 24.2 percent drop in total assets
twelve credit card banks (nonbank banks) were owned by nonbank firms.
(reflecting a high volume of loans sold in the first quarter of 1994).
R
eferen ces
Canner, Glenn B., and Charles A. Luckett. 1992. “Developments in the Pric
U.S. General Accounting Office. 1994. U .S . C r e d it C a r d I n d u s t r y : C o m
ing of Credit Card Services.” F e d e r a l R e ser v e B u l l e t in 78 (Septem
p e t it iv e
ber): 652-66.
C ongressional R equesters G A O /G G D -9 4 -2 3 . W ashington, D .C .:
D e v e l o p m e n t s N e e d t o B e C lo se ly M o n i t o r e d . Report to
GPO, April.
Liss, Samuel G., and Mary A. Rhei. 1994. “Credit Card Issuers - Compara
tive Look at the Public Proxies.” U n it e d S t a te s E q u i t y R e s e a r c h .
Salomon Brothers, Financial Services, January 4.
N o tes
FRBNY Q u a r t e r l y R e v ie w / S u m m e r - F a ll 1994
111
Regional Employment Trends
in the Second District
Charles Steindel and Lois Banks
It is well known that growth in the Northeast, including
manufacturing employment in each. Taken as a whole, aggre
the Second Federal Reserve District, has trailed that in the
gate payroll em ploym ent in these m etropolitan areas
nation as a whole over the last several years. What is less often
accounts for more than 90 percent of that in the District as a
recognized is that while some parts of the Northeast continue
whole.
to lag the nation, other parts, including sections of the Sec
In general, job growth in the District has not kept
ond District, are now growing close to or in line with the
pace with national trends,1 and in some important regions
national average. This tendency to overlook movements in
such as Rochester and Long Island, employment has recently
smaller areas is perhaps especially marked in the Second Dis
faltered. Some signs of progress have emerged, however:
trict, where discussions of the regional economy frequently
employment has risen throughout most of the District, and in
emphasize New York City. Although New York City com
northern New Jersey and Albany, the gaps with the national
mands attention as the major employment and population
data have been either small or narrowing.
center of the Second District, the economy of the District is
far more than the city writ large.
N e w Y o r k C it y
This article attempts a more balanced assessment of
The city’s economy has improved somewhat over the last
economic developments in the District by considering New
year. Employment finally bottomed out in m id-1993, and
York City alongside three other important regions. We focus
year-to-year gains in jobs moved up to the neighborhood of
on job growth, giving particular attention to the factors that
0.5 percent in early 1994 (Chart 1). Recent job growth, how
have given rise to diverse employment trends within the Dis
ever, falls far short of that in the nation as a whole and only
trict. Our analysis draws on the Bureau of Labor Statistics’
begins to counter the city’s losses since 1989- In June 1994,
nonfarm payroll employment series, a source notable for
for instance, payroll employment in the city was 3.3 m il
comprehensive and timely data at the local level.
lion— 8 percent less than its 1989 high.
In addition to New York City, the large regions
The unemployment rate in New York City has
examined are 1) the environs of New York City, consisting of
recently declined more rapidly than in the nation as a whole.
Long Island, the northern metropolitan area, and northern
The city’s rate fell from 11.4 percent in the first quarter of 1993
New Jersey; 2) midstate New York— the large region stretch
to 9 percent in the second quarter of 1994, while the national
ing north from the city suburbs to the Canadian border and
rate dropped from 6.9 percent to 6.2 percent over the same
west past Syracuse; and 3) Western New York (Figure 1).
period. A shrinking labor force, however, has contributed sig
Since developments in the agricultural sector contribute only
nificantly to the city’s declining unemployment rate.
modestly to overall employment trends in the heavily urban
The city’s recent employment gains have also been
ized Second District, we focus on the major metropolitan
unevenly distributed across industries. M anufacturing
areas in the four regions. The table lists these areas and gives
employment, which still accounts for about 9 percent of the
the 1993 size of aggregate nonfarm payroll employment and
city’s job total, has continued falling at a moderate pace
112
F R B N Y Q u a r t e r l y R e v i e w / S u m m e r - F a ll 1994
I n B r ie f
(Chart 2). Encouragingly, however, changes in manufactur
Figure 1
ing employment in the city over the last year more closely
R
e g io n s o f t h e
Seco nd D
is t r ic t
matched national developments rather than trailing them
badly, as had been the case for a number of years. Thus, the
manufacturing sector is currently not a source of weakness for
the city relative to the nation. (See Moss 1994 for a discussion
of recent developments in the city’s manufacturing sector.) A
large portion of the recent payroll growth in the city can be
traced to the securities sector and to health, social, and busi
ness services. But with the city’s employment recovery just
starting to take root and advance beyond Wall Street, reports
that some early 1994 trading losses were leading securities
firms to reevaluate expansion plans or cut staff (Raghavan
1994) suggest that the city is still some distance from a fullfledged expansion.
N e w Y o r k C ity E n v ir o n s 2
The region surrounding New York City can be subdivided
into three segments: Long Island; the northern metropolitan
C o m p o s it io n
of
Pa yro ll E m plo y m en t , 1 9 9 3
T h o u sa n d s
United States
New York City
New York City Environs
Northern Metropolitan Area*
Nassau-Suffolk MSA
(Long Island)
Northern New Jerseyf
Total
Manufacturing
Percentage of
Total Jobs in
Manufacturing
110521
18005
16
3275
290
9
672
90
13
1054
2287
122
388
12
17
Chart 1
T r e n d s in N e w Y o r k C it y P a y r o l l E m p l o y m e n t
Twelve-Month Percent Changes
Percen t
United States
S
Midstate New York
Dutchess County MSA
(Poughkeepsie)
Binghamton MSA
Utica-Rome MSA
Syracuse MSA
Albany-Schenectady-Troy MSA
104
113
124
330
426
18
27
21
50
44
18
24
17
15
10
Western New York
Rochester MSA
Buffalo-Niagara Falls MSA
515
528
130
90
25
17
Note: MSAs are m etropolitan statistical areas.
*C om prises Putnam , Rockland, and W estchester counties and the
Stam ford-Norw alk m etropolitan statistical area.
tC om prises the N ew ark, Bergen-Passaic, Middlesex-Som erset-Hunterdon, and Jersey City m etropolitan statistical areas.
In B
r ie f
f
4
New York City
1
/- V
'~ s
J
11 II 1 1 1 1 1 1 1 ........................M l
1991
_L1 1 i 1 1 1 ! ! 1 1 ...............
92
93
94
Sources: U.S. Department of Labor, Bureau of Labor Statistics; state
employment security agencies.
Note: Chart shows data through June 1994.
F R B N Y Q u a r t e r l y R e v ie w / S u m m e r - F a ll 1994
113
area of Rockland, Westchester, Orange, and Putnam counties
ation by smaller firms has largely offset cutbacks by large
in New York and Fairfield County in Connecticut; and the
corporations.
twelve counties of northern New Jersey included in the Sec
Retail employment has risen markedly in most parts
ond District (Figure 2). Taken as a whole, the environs of
of the region. Much of this increase stems, of course, from
New York City have a considerably larger population and
even employ more people than the city proper. In fact, the
region contains four metropolitan statistical areas (MSAs)
Figure 2
E n v ir o n s
with 1990 populations above 1 million.3
of
N
ew
Y o r k C it y
Recent employment trends have diverged across the
three segments of this region. In the spring of 1994, overall
job growth on Long Island and in the northern metropolitan
area actually turned negative on a year-to-year basis, while
northern New Jersey growth maintained a pace only moder
ately below the national norm (Chart 3)- These differences in
part reflect differences in the manufacturing sector. Jo b
cuts— some attributable to corporate restructuring, others
to layoffs at defense contractors— continue to be significant
at Long Island and northern metropolitan manufacturers
(Chart 4). Northern New Jersey, by contrast, has experienced
fewer manufacturing job losses, apparently because job creChart 3
Chart 2
T
T
r e n d s in
N
ew
Y
ork
r e n d s in
Pa yro ll E m plo y m en t
in
N
ew
Y o r k C it y
E n v ir o n s
Twelve-Month Percent Changes
C it y M a n u f a c t u r in g
Pa yro ll E m plo y m en t
Twelve-Month Percent Changes
Percen t
Percen t
Northern
New Jersey
Uni ted States
r '- *
/
,—'
^
Nrw York City —
r
/
/
✓—
/
v
i
t
1
1
—s'
111111111111
i
/
A
r
i
1 M M ... ...............
1991
Northern
metropolitan
area
*/ s-jfjr
*» C *-+ Long Island
/
A f '
*
United States
1991
11111111111
11111111111
92
93
i i i i i i i i i i i
i i i i i i i i i i i
92
93
111111
94
Sources: U.S. Department of Labor, Bureau of Labor Statistics; state
employment security agencies.
1 1 .1.1 1 J
94
Sources: U.S. Department of Labor, Bureau of Labor Statistics; state
employment security agencies.
Note: Chart shows data through June 1994.
Digitized
114for FRASER
F R B N Y Q u a r t e r l y R e v ie w / S u m m e r - F a ll 1994
Note: Northern New Jersey comprises the Newark, Bergen-Passaic,
Middlesex-Somerset-Hunterdon, and Jersey City metropolitan statistical
areas. Long Island refers to the Nassau-Suffolk metropolitan statistical area.
The northern metropolitan area comprises Putnam, Rockland, and Westchester
counties and the Stamford-Norwalk metropolitan statistical area. Chart shows
data through June 1994.
I n B r ief
economic recovery and increased household spending. In
those in other parts of the District. In 1990, the largest mid
addition, several parts of the region have recently seen the
state MSA, Albany-Schenectady-Troy, had a population of
introduction of large “warehouse” retail outlets of national
only 861,000, placing it ninth among the District MSAs.
chains. Although this restructuring of the retail sector may
The employment picture has varied sharply around
have no permanent positive effect on employment, the con
the region. The Dutchess County MSA (Poughkeepsie),
struction and staffing of the new stores have generated jobs
exemplifying the mid-Hudson Valley area, and the more
over the short term.
westerly Binghamton MSA are faring quite poorly (Chart 5),
largely because corporate restructuring moves have depressed
M
N
id s t a t e
Y
ew
manufacturing employment (Chart 6).5 The pace of job loss
o rk
This large region (Figure 3), dominated by the Catskills and
in the Poughkeepsie area, however, did moderate somewhat
Adirondacks, resists generalization.4 The metropolitan areas
in the spring of 1994. The area along the Mohawk River west
in the region are dispersed along the lakes and rivers sur
to Lake Ontario— here illustrated by data for the Syracuse
rounding the mountains. Nevertheless, discussing this
and Utica-Rome MSAs— shows somewhat more strength.
region as a unit rather than treating each MSA separately
Syracuse employment has been flat, while Utica job growth
makes some sense given the small size of the MSAs relative to
has recently moved in line with the national trend. Scheduled
job cuts at a major military installation in the Utica-Rome
MSA, however, will hurt that labor market. Manufacturing
Chart 4
employment, though not rising, has held up better in Syra
T rends
in
M a n u f a c t u r in g P a y r o l l E m p l o y m e n t
in
cuse and Utica than in the more southerly parts of the region,
N e w Y o r k C it y E n v ir o n s
Twelve-Month Percent Changes
Percent
Figure 3
Unit ed States
M
Northern
New Jersey
\
\
I
V
A
id st a t e
N
ew
Y ork
<
t
» •*
t r*
*
/" 1
4 I
Northern
metropolitan
area
Long Island
j
f
V
y
! J ' 'f ! 1 i : ! i !
1 1 1 1 1 II 1 1 1 1
1991
92
. .. . . . . . .
1 1 1 1 II
j.1
93
94
Sources: U.S. Department of Labor, Bureau of Labor Statistics; state
employment security agencies.
Note: Northern New Jersey comprises the Newark, Bergen-Passaic, Middlesex Somerset-Hunterdon, and Jersey City metropolitan statistical areas. Long Island
refers to the Nassau-Suffolk metropolitan statistical area. The northern metro
politan area comprises Putnam, Rockland, and Westchester counties and the
Stamford-Norwalk metropolitan statistical area. Chart shows data through
June 1994.
I n B r ie f
F R B N Y Q u a r t e r l y R e v ie w / S u m m e r - F a ll 1994
115
and some service industries, such as wholesale and retail
area have been recent increases in employment by both the
trade, have been growing.
state and the local government.
The strongest portion of the midstate region, how
ever, is probably the Albany MSA. O f all the major parts of
W
the Second District, Albany alone consistently experienced
We define Western New York as the fourteen counties in the
job growth ahead of the national pace from early 1993
Buffalo Branch area of the Second District (Figure 4). The
through April 1994. The apparent slippage in Albany’s year-
economy of Western New York is dominated by the large
to-year job gains in May and June of 1994 may simply reflect
Buffalo and Rochester MSAs. The two areas have fared some
comparisons with unusually strong months in 1993, rather
what differently in recent years, and their economies tend to
than a recent deterioration in that area. M anufacturing
belie their popular reputations. Buffalo, like many other
employment in the Albany area has proven more resilient
large cities along the Great Lakes, has gradually transformed
than in some other parts of the midstate area, such as Bing
its economy from one based on durable goods manufacturing
hamton and Dutchess County, although manufacturing is
to a more diversified, service-centered one, though manufac
clearly not an important source of job growth in Albany.
turing remains an important sector (the early stages of this
Employment growth in the Albany area has been centered in
transformation were described in Doolittle 1985-86). A spe
health care, retailing (with most months in early 1994 seeing
cial factor aiding Buffalo in this transition was the U.S.-
ester n
N
ew
Y
o rk
job gains in this sector in the 3 to 5 percent range on a yearto-year basis), and the diversified service sector. The develop
ment of new large retail outlets has been especially pro
nounced in the Albany MSA. Adding to the growth of this
Chart 6
T
r e n d s in
M
id s t a t e
N
ew
Y o r k M a n u f a c t u r in g
Payro ll Em plo ym en t
Twelve-Month Percent Changes
Percen t
Chart 5
T r e n d s in M id s t a t e N
Twelve-Month Percent Changes
ew
Y o rk Pa yro ll E m plo y m en t
Percen t
0
-2
-4
Poughkeepsie
................Ml
93
Sources: U.S. Department of Labor, Bureau of Labor Statistics; state
employment security agencies.
Sources: U.S. Department of Labor, Bureau of Labor Statistics; state
employment security agencies.
Note: Chart shows data through June 1994.
Note: Chart shows data through June 1994.
F R B N Y Q u a r t e r l y R e v ie w / S u m m e r - F a ll 1994
116
I n B r ief
Canada Free Trade Agreement of 1989, which encouraged
Figure 4
Canadian firms to locate operations in the relatively low-cost
W
ester n
N
ew
Y ork
Buffalo area and Canadian shoppers to patronize the area’s
stores. Subsequently, Buffalo had a slow exit from the
national recession (Chart 7), partly because the decline of the
Canadian dollar starting in the second half of 1991 weak
ened the incentives for Canadians to shop and set up business
in the Buffalo area. More recently, a leveling-off in manufac
turing employment (Chart 8) and the stimulus provided by
new retail outlets have helped job growth to resume in the
Buffalo MSA, though retail sales to Canadian buyers still
appear to be weak (Linstedt 1994).
Buffalo is today primarily service-oriented, but it is
still perceived as a blue-collar town. In contrast, Rochester,
often considered a white-collar city, has an extraordinary 25
percent of its MSA payroll employment in manufacturing!
O f course, many of these m anufacturing jobs are highincome ones in the headquarters and research and develop
ment units of m ajor high-tech corporations. Recently,
responding in part to intensified foreign competition, several
of these firms have undertaken sizable restructuring opera
tions and have been reducing their employment in the
Rochester area. The deterioration in manufacturing employ
Chart 8
ment has contributed to an erosion in overall job growth in
T
r e n d s in
W
ester n
N
ew
Y o r k M a n u f a c t u r in g
Payro ll Em plo y m en t
Twelve-Month Percent Changes
P ercen t
Chart 7
T r e n d s in W e s t e r n N
Twelve-Month Percent Changes
ew
Y o rk Payro ll Em plo y m en t
1
«
1
1
I
1
4
1
United States
Rochester
2
\
0
'J
-4
^
D
1
1
/—
* ^
Buffalo
X.
o
1 1 I I 1 1 1 i
1 i
1
1 1 1 1 1 1 1 1 1 i
1
92
i
i
i
i
i
i
i
/ V
!| y
/ V
1991
/
> I
J
i
i
i
i
93
i
i
i
94
i
i
...................M U
1991
4
1 1 1 1 1 M M1 1
92
1 1 1 1 II 1 1 1 1 1
93
Sources: U.S. Department of Labor, Bureau of Labor Statistics; state
employment security agencies.
Sources: U.S. Department of Labor, Bureau of Labor Statistics; state
employment security agencies.
Note: Chart shows data through June 1994.
Note: Chart shows data through June 1994.
I n B r ief
Buffalo
/ \ /
\
f\
* j
A \
Q ' / v
f \ < W\ S
\'
n
f c r ° ~ l »
f —* \
/
rf\
ff b
/\
\
-2
V
1
1
United
States
4
Percen t
F R B N Y Q u a r t e r l y R e v ie w / S u m m e r - F a ll 1994
111111
94
117
Rochester; by the middle of 1994, the growth rate was barely
A second factor that has contributed to the differential experi
positive. To date, segments of Rochester’s service sector such
ence of areas within the District is the performance of the ser
as business, health, and retailing have expanded sufficiently
vice sector. New York City’s financial sector dominates the
to offset the increased drag from manufacturing.
District’s service economy, and job gains in this industry have
been a particular spur to the city’s economy. Service employ
C o n c l u s io n
ment in other areas, most notably the outskirts of New York
Employment trends have differed across regions and metro
City and the Albany MSA, has benefited from new large-scale
politan areas in the Second District. The Binghamton and
operations in retailing. Because the warehouse-type chains
Poughkeepsie areas continue to experience significant job
have been relatively late coming to the Northeast, hiring by
losses, and growth has faltered on Long Island, in the north
these outlets will probably continue to be stronger in the Dis
ern metropolitan area, and in the Rochester and Syracuse
trict than in other parts of the nation.
MS As. New York City and the Buffalo MSA, by contrast, are
Despite the regional differences detailed in this arti
seeing modest but real job growth, and the job gains in
cle, the Second District as a whole shows some signs of recov
northern New Jersey and the Albany and Utica areas have
ery (Rosen and Wenninger 1994). Although job growth in
been quite respectable.
the District continued to trail national trends through the
Developments in manufacturing to some extent
middle of 1994, aggregate employment has been expanding.
explain these differing employment patterns. Areas that con
The areas in the District that are lagging are mainly those
tinue to face substantial cutbacks in manufacturing employ
feeling the effects of corporate restructuring and defense cuts.
m ent— Long Island, the northern m etropolitan area,
While these ills will continue to be felt in the short run, over
Binghamton, Poughkeepsie, and Rochester— have tended to
the medium and longer term they should abate, setting the
trail much of the rest of the District and the nation as a whole.
stage for healthier growth.
118
F R B N Y Q u a r t e r l y R e v i e w / S u m m e r - F a ll 1994
I n B r ie f
Endno tes
1. Comparing District and national trends is complicated by the inclusion
Note 2 continued
of an explicit “bias adjustment” in the national data for the period since
on Long Island— have little to do with short- or medium-term develop
March 1993- This adjustment, designed to account for job growth at new
ments in New York City.
firms not yet included in the monthly payroll employment survey, current
ly adds about one percentage point to the national payroll annual growth
3. The MSAs are Newark, Bergen-Passaic, and Middlesex-Somerset-Hun-
rate. Since the data from New York and New Jersey do not include such
terdon— all in New Jersey— and Nassau-Suffolk in New York. These areas
explicit bias adjustments, it is conceivable that recent D istrict employ
plus the Monmouth-Ocean MSA in New Jersey and the bulk of the north
ment trends are being understated (assuming the national bias adjustment
ern metropolitan area are included in the “New York Consolidated M SA.”
is roughly correct, as is usually the case). Nevertheless, District employ
ment data are modified to reflect some information about hiring at new
4. It also lacks an accepted name. The obvious term “upstate” includes
firms and job counts from ongoing unemployment insurance tax reports, so
Western New York, a region treated separately in this article. Another log
the understatement is probably small.
ical choice is “central New York,” but this term is used by the New York
State Labor Department to refer more narrowly to the area around Syracuse.
2. We use the term “environs” rather than “suburbs” to denote this region
both because significant parts of it— for instance, Newark, New Jersey, the
5. The Census Bureau includes Dutchess County in the large New York
north fork o f Long Island, and the Delaware Water Gap— are hardly “sub
Consolidated MSA. The significance of the sharp drop in manufacturing
urban” in appearance in any ordinary sense o f the word, and, more funda
employment for the Hudson Valley would be obscured, however, if we were
mentally, because certain key sectors of the region’s economy— for exam
to consider Dutchess County a part of the northern New York City suburbs.
ple, the pharmaceutical industry in New Jersey and the aerospace industry
R
eferen ces
Doolittle, FredC. 1985-86. “A djustm ents in Buffalo’s Labor M arket.”
F e d e r a l R e s e r v e B a n k o f N e w Y o r k Q u a r t e r l y R e v i e w 10
Raghavan, Anita. 1994. “Bear Market Ax Again Hits Wall Street.” W a ll
S t r e e t J o u r n a l , August 9-
(Winter): 28-37.
Rosen, Rae, andJohn Wenninger. 1994. “Second District Update: A Moderate
Linstedt, Sharon. 1994. “Canadian Shoppers Are Staying Home.” BUFFALO
N e w s , Ju ly 17.
Recovery is in Progress.” F e d e r a l R e ser v e B a n k
terly
of
N ew Y o r k Q u a r
R e v ie w 19 (Spring): 45-53.
Moss,-Mitchell L. 1994. “Made in New York: The Future o f Manufacturing
in New York City.” U rban Research Center, N ew York U niversity
(August).
N o tes
F R B N Y Q u a r t e r l y R e v ie w / S u m m e r - F a ll 1994
119
Fu rth er R
R ecent
e a d in g
FRBNY
U n p u b lis h e d R e s e a r c h P a p e r s
9331. Malz, Allan M.
9412. De Kock, Gabriel, a n d Thomas DeLeire.
N ew V a r ie t ie s o f F o r e ig n C u r r e n c y O p t io n s .
T h e R o le o f t h e E x c h a n g e R a te in t h e M o n e t a r y
December 1993.
T r a n s m is s io n M e c h a n is m : A T im e -S e r ie s A n a l y s is .
9407. Akhtar, M.A.
M o n e t a r y P o l ic y E f fe c t s o n L o n g - T e r m I n t e r e s t
A u g u st 1994.
9413. Femald, Ju lia , Frank Keane, an d M artin Mair.
R a t e s : A C r it ic a l S u r v e y o f t h e E m p ir ic a l
T h e M a r k e t f o r C o l l a t e r a l iz e d M o r t g a g e
L it e r a t u r e . July 1994.
O b l ig a t io n s (C M O s ). S e p te m b e r 1994.
9408. Cohen, G eraldD ., an dJoh n Wenninger.
9414. Chang, P.H. Kevin, a n d Carol Osier.
T h e R e l a t io n s h ip b e t w e e n t h e S p r e a d a n d t h e
E v a l u a t in g C h a r t - B a se d T e c h n ic a l A n a l y s is :
F u n d s R a t e . July 1994.
T h e H e a d -a n d - S h o u l d e r Pa t t e r n in F o r e ig n
9409- Steindel, Charles.
A s s e s s in g R e c e n t T r e n d s in M a n u f a c t u r in g . J u l y
1994.
9410. Blomberg, S. Brock, an d G eraldD . Cohen.
S c o r in g P o l it ic a l E c o n o m y M o d e l s : A M u l t ipl e
E q u il ib r ia A p p r o a c h . July 1994.
9411. Femald, Ju lia , Frank Keane, an d Patricia C. Mosser.
E x c h a n g e M a r k e t s . S e p te m b e r 1994.
9415. Estrella, Arturo, D arryll Hendricks, J o h n Kambhu, Soo
Shin, an d Stefan Walter.
O p t io n s P o s it io n s : R is k M e a s u r e m e n t a n d
C a pita l R e q u ir e m e n t s . S e p te m b e r 1994.
9416. Clark, John.
T he Str u ctu re, G ro w th , and R ecent P erfo r
L a t in A m e r ic a n B o n d M a r k e t .
M o r t g a g e S e c u r it y H e d g in g a n d t h e Y ie l d
m ance of the
C u r v e . August 1994.
S e p te m b e r 1994.
FRBNY Q u a r t e r l y R e v ie w / S u m m e r - F a l l 1994
120
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New York, N.Y., 10045.
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