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Detroit back from the brink? Auto industry crisis and
restructuring, 2008–11
Thomas H. Klier and James Rubenstein

Introduction and summary
The Great Recession of 2008–09 took a severe toll on
the U.S. auto industry. Faced with a combination of
declining sales, high structural costs, and high levels of
debt, Chrysler LLC and General Motors Corporation
(GM)—two of the three Detroit-based carmakers—
approached the federal government for help. The third
Detroit-based carmaker, Ford Motor Company, did not
seek government assistance. In late December 2008
and early January 2009, Chrysler and GM, as well as
their former financing captives,1 received a first wave
of financial support from the U.S. government. After
several attempts to restructure their operations failed,
the two companies filed for bankruptcy in the spring
of 2009, an action that only a few months earlier GM
chief executive officer (CEO) Rick Wagoner had
declared to a U.S. Senate Committee was “not an
option” (Economist, 2009).
In this article, we review the crisis experienced
by the U.S. auto industry during 2008 and 2009, as
well as the unprecedented government intervention
prompted by a constellation of events that might be
called a “perfect storm.” We then analyze how the auto
industry has changed in some very significant ways as
a result of the crisis. This article continues a narrative
begun in an earlier article (Klier, 2009), which documented the challenges facing the Detroit Three carmakers
through 2007, first from foreign imports and then from
North American-based production by foreign-headquartered producers.
Declining fortunes of the Detroit Three
As part of the severe recession of 2008–09, the
United States experienced its sharpest decline in production and sales of motor vehicles since World War
II. Sales of light vehicles (cars and light trucks) in the
United States dropped from 16.2 million in 2007 to
13.5 million in 2008, and then to 10.1 million in 2009

Federal Reserve Bank of Chicago

(figure 1). In addition to rising unemployment, tightening credit markets contributed significantly to the sales
decline, as 90 percent of consumers finance automobile purchases through loans, either directly from the
financing arms of the vehicle manufacturers or through
third-party financial institutions. Both types of lenders
experienced difficulty in raising capital to finance loans
at the time.2 “By midsummer of 2008, the nightmare
scenario was coming to life—soaring fuel prices, a miserable economy, no credit for consumers.” As the market was deteriorating by the day, “[m]ore than fifteen
Thomas H. Klier is a senior economist in the Economic Research
Department at the Federal Reserve Bank of Chicago. James
Rubenstein is a professor in the Department of Geography
at Miami University, Ohio. The authors would like to thank
Dick Porter, as well as an anonymous referee, for helpful
comments. Taft Foster provided excellent research assistance.
© 2012 Federal Reserve Bank of Chicago
Economic Perspectives is published by the Economic Research
Department of the Federal Reserve Bank of Chicago. The views
expressed are the authors’ and do not necessarily reflect the views
of the Federal Reserve Bank of Chicago or the Federal Reserve
System.
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President and Director of Research; Spencer Krane, Senior Vice
President and Economic Advisor; David Marshall, Senior Vice
President, financial markets group; Daniel Aaronson, Vice President,
microeconomic policy research; Jonas D. M. Fisher, Vice President,
macroeconomic policy research; Richard Heckinger, Vice President,
markets team; Anna L. Paulson, Vice President, finance team;
William A. Testa, Vice President, regional programs; Richard D.
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ISSN 0164-0682

35

depended critically on selling large
volumes of light trucks—minivans,
U.S. light vehicle sales and Detroit market share
sport utility vehicles (SUVs), and
pickups—a segment of the market
percent
million units, SAAR
that declined relatively rapidly
20
80
Light vehicle sales
during the recession.
18
(right-hand scale)
75
Foreign-headquartered carmak16
ers had entered the U.S. market
70
during the 1950s with fuel-efficient
14
vehicles and began producing cars
65
here in 1978. The Detroit Three
12
reacted to the loss of much of their
10
60
share of the passenger car market
8
during the 1980s and early 1990s
Market share
55
(left-hand scale)
by focusing on the profitable light
6
truck segment, which expanded
50
from one-third to one-half of the
4
overall light vehicle market during
45
2
the last two decades of the twentieth
0
40
century. But when growth of the light
1980 ’83
’86
’89
’92
’95
’98 2001 ’04
’07
’10
truck market slowed in the early
2000s, the Detroit Three began to
Note: SAAR indicates seasonally adjusted annual rate.
Source: Ward’s Auto Group, Auto Infobank, online database.
lose market share to international
competitors at a faster rate. A sharp
spike in gas prices to $4.00 a gallon
during the first half of 2008 further depressed light truck
Big Three assembly plants were either idling or opersales, especially for the Detroit Three (Klier, 2009).
ating on reduced shifts. Twenty-five thousand UAW
In response to plunging sales, carmakers drastiworkers went on indefinite layoff, as Detroit frantically
cally cut back production in the United States, reducing
tried to cut production faster than sales fell. … The
output by 46 percent in the course of just two years,
American auto industry was collapsing like a tent in a
from 10.4 million light vehicles in 2007 to 8.4 million
hurricane” (Vlasic, 2011, p. 284).The steep decline in
in 2008 and 5.6 million in 2009. This rapid decline in
sales during 2008 and 2009 was particularly disruptive
production resulted in massive job cuts: Between
for carmakers because it ended nearly a decade of stable
2007 and 2009, employment declined from 185,800
sales at record-high levels of 16–17 million units per
to 123,400 in assembly plants and from 607,700 to
year. During the second half of the twentieth century,
413,500 in parts plants. The U.S. auto industry had
sales had soared from 6 million units in 1950 to 17
already been shedding jobs before the onset of the
million in 2000, yet short-term cyclical changes with
2008–09 recession—from a peak of 237,400 assembly
double-digit annual percentage changes were typical
and 839,500 parts jobs in 2000—due to productivity
until 1991, with sales fluctuating by more than 10 percent
increases as well as ongoing market share loss by the
during ten of the previous 24 years. In contrast, between
Detroit producers.5
1992 and 2007 annual sales figures rarely fluctuated by
3
The Detroit carmakers had struggled to address
more than 3 percent per year. After two decades of
the growing problem of legacy costs—principally
remarkable stability, carmakers had come to rely on
generous retiree health care obligations—earlier in
high volumes of vehicle sales and had made their inthe decade (Vlasic, 2011; Klier 2009). By 2006, both
vestment decisions accordingly.
Ford’s and GM’s bond ratings had fallen below inThe sales decline was more severe for the Detroit
vestment grade and the companies’ problems were in
Three carmakers than for their foreign-headquartered
the news.6 As a first step, Ford and GM negotiated a
competitors. Combined U.S. sales for Chrysler, Ford,
special agreement with the United Automobile Workers
and GM fell from 8.1 million in 2007 to 4.6 million
(UAW) union on sharing some of the health care costs
in 2009. Their combined market share declined from
in 2006.7 The Detroit carmakers also started reducing
50 percent to 44 percent during these two years.4
their work force through buyouts and early retirement
The Detroit Three carmakers were vulnerable during
the severe recession in part because their viability
figure 1

36

2Q/2012, Economic Perspectives

offers.8 Ford, which by many accounts was in worse
shape than its two Detroit competitors at the time (see
Vlasic, 2011), for the first time in its history hired a
CEO from outside the company—Alan Mullaly, who
joined the company in September 2006 from Boeing.
In December of the same year, Ford secured a line of
credit in the amount of $23.5 billion by pledging virtually
all of its assets as collateral. At the end of the summer
of 2007, shortly before the onset of the recession, the
Detroit carmakers reached a new labor agreement
with the UAW. All three companies had negotiated a
transfer of health care liabilities for retired blue-collar
workers to a newly formed trust, a so-called voluntary
employee benefits association, or VEBA.9 The new
labor contract also introduced a second-tier wage level
for new hires, paying substantially less. All three carmakers subsequently announced large buyout programs
to improve their competitiveness. Yet these efforts turned
out to be too little and too late to allow them to withstand the impact of the rapidly declining economy.
Government rescue efforts
The principal steps in the government rescue of
Chrysler and GM took place relatively quickly between
December 2008 and July 2009. The key developments
in order included: 1) Congress’s inability to agree on
a remedy regarding a request for assistance from the
Detroit Three; 2) the issuance of a short-term loan by
the outgoing Bush administration; 3) the creation of a
presidential task force shortly after the inauguration
of President Obama; 4) the rejection of restructuring
plans drawn up by the carmakers; 5) the managed
bankruptcy of Chrysler; 6) the managed bankruptcy
of GM; and 7) several post-bankruptcy initiatives.
Congressional inaction
Prompted by the rapidly declining fortunes of the
Detroit Three carmakers, their CEOs and the president
of the UAW pleaded their case for emergency aid before the Senate Committee on Banking, Housing, and
Urban Affairs on November 18, 2008,10 and before
the House Committee on Financial Services the next
day (Cooney et al., 2009). Ford’s CEO accompanied
his colleagues from GM and Chrysler, even though
ultimately Ford decided not to request government
money.11 Ford’s leadership realized that a default by
one of the other Detroit carmakers could have serious
repercussions for Ford through linkages with shared
parts suppliers, which would also be negatively affected.
The committee hearings did not go well. The CEOs
failed to make a compelling case and so their request
for financial help was not received sympathetically
by a broad audience on Capitol Hill.12 Detroit’s role

Federal Reserve Bank of Chicago

had changed considerably since the 1950s, when
Charles E. Wilson, head of GM at the peak of its market power, stated during his confirmation hearings as
Secretary of Defense that what was good for the country was good for General Motors and vice versa. By
2008, the footprint of Detroit’s carmakers had shrunk
substantially. The political debate reflected that fact.
Senator Carl Levin, who represents Michigan, home
state of the Detroit Three, argued that the condition of
the Detroit carmakers was “a national problem first of
all, without any question.” On the other hand, Senator
Richard Shelby, who represents the southern state of
Alabama, at the time home to three assembly plants
of foreign-headquartered producers, opposed a government rescue, saying: “I don’t say it’s a national problem. … But it could be a national problem, a big one
if we keep putting money [in]” (MSNBC, 2008, cited
in Klier and Rubenstein, 2011, p. 198).
Less than three weeks later, on December 4 and 5,
a second, more urgent request by the Chrysler and
GM CEOs before the same two congressional committees resulted in the introduction of a bill in the
House on December 10, 2008. Legislation authorizing
loans to the carmakers passed the same day by a vote
of 237–170 (Cooney et al., 2009). At the suggestion
of the Bush administration, this legislation authorized
the use of a direct loan program, previously authorized
by the Energy Independence and Security Act of 2008
and already appropriated for the Department of Energy
to support alternative fuel and low-emissions technologies (EISA, P.L. 110–140, funded under P.L. 110–329,
§129). In the Senate, a move on December 11 to close
debate for the purpose of achieving a final vote on the
House-passed bill failed by an insufficient majority of
52–35.13 After considering other funding mechanisms,
the Senate abandoned further action on the issue and
the bill died (Cooney et al., 2009).
Short-term rescue
By the beginning of December 2008, GM and
Chrysler could no longer secure the credit they needed
to conduct their day-to-day operations (Congressional
Oversight Panel, 2011b). GM posted a near-record
loss of $30 billion in 2008 and entered 2009 with a
cash supply of only $14 billion.14 “General Motors had
weeks—maybe days—before it defaulted on billions
of dollars in payments to its suppliers” (Vlasic, 2011,
p. 329). The company announced it would idle 20 of
its factories across North America. Privately held
Chrysler, acquired by Cerberus Capital Management
from DaimlerChrysler in 2007, also had a dangerously
low supply of cash to meet day-to-day obligations.
Chrysler announced it would close all its plants for a

37

month. Ford posted a record $14.6
Table 1
billion loss in 2008 but did not
TARP assistance to U.S. motor vehicle industry
face the immediate cash shortage
		
General	 GMAC/	Chrysler
of the other two Detroit-based car	
Chrysler	
Motors 	
Allya	Financial
makers, because it had borrowed a
	
( - - - - - - - - - - - billions of dollars - - - - - - - - - - )
substantial sum in 2006 (Cooney
Financial
et al., 2009).
Total TARP assistance	
$10.9	
$50.2	
$17.2	
$1.5
Bush administration	
4.0	
13.4	
6.0	
1.5
Faced with the imminent
Obama administration	
6.9	
36.8	
11.2	
0.0
collapse of Chrysler and GM one
Recouped	
9.6	 24.0	 5.1	1.502
month before he was to leave
Repayment of principalb	 7.9	 23.1	2.5	1.5
Incomec	
1.7	 0.9	 2.6	0.02
office, President George W. Bush
Outstanding	
0.0	 22.6	14.6	 0.0
issued an executive order on
Loss on principal	
(2.9)	
(4.4)b	0.0b	0.0
December 19, 2008, permitting
Net profit/loss	
(1.3)	
TBD	
TBD	
0.02
the Treasury Department to utilize
GM’s financing arm, General Motors Acceptance Corporation, was renamed Ally Bank
the Troubled Asset Relief Program
in 2009.
As of August 17, 2011.
(TARP) under the Emergency EcoIncome/revenue received from TARP assistance.
nomic Stabilization Act (EESA) of
Notes: TARP indicates Troubled Asset Relief Program. TBD indicates to be determined.
Source: Canis and Webel, 2011.
2008 to support the two carmakers.15,16 Treasury established the Automotive Industry Financing
Program (AIFP)—the vehicle with which funding
The term sheets spelled out a number of conceswould be provided—under TARP on December 19.17
sions for the stakeholders:
President Bush stated that “government has a responn	 Management—Restrictions were placed on execsibility not to undermine the private enterprise system ...
utive compensation and privileges, including pay,
[but if] we were to allow the free market to take its
bonuses, golden parachutes, incentives, and benecourse now, it would almost certainly lead to disorderly
fits. Executives were also restricted from compenbankruptcy and liquidation for the automakers”
sation agreements that would encourage them to
(Cooney et al., 2009, p. 8). The White House fact
take “unnecessary and excessive risks” or to masheet that accompanied the announcement stated that
nipulate earnings (Cooney et al., 2009, pp. 42–43).
“the direct costs of American automakers failing and
n	 Unions—Compensation was to be reduced by
laying off their workers in the near term would result
December 31, 2009, and work rules were to be modin a more than 1 percent reduction in real GDP growth
ified, to be equivalent to those of foreign-headand about 1.1 million workers losing their jobs, inquartered assembly plants in the United States. Half
cluding workers for automotive suppliers and dealers”
of the future contributions to the planned VEBA
(White House, 2008).
were to be made with company stock holdings.
Through the Bush Administration’s TARP comn
	
Investors—Unsecured public claims were reduced
mitments, GM and GMAC received $13.4 billion and
18
by at least two-thirds and no dividends were to be
$6 billion, respectively, on December 29 and 31, 2008.
dispersed while government loans were unpaid.
Chrysler received a $4 billion loan on January 2, 2009.
The Bush administration also loaned $1.5 billion to
n	 Dealers and suppliers—New agreements were to
Chrysler Financial. TARP loans made it possible for
be signed to lower costs and capacity.
Chrysler and GM to stay afloat during the transition to
n	 Treasury—Warrants were issued to purchase
the Obama administration (Cooney et al., 2009). Incommon stock (Cooney et al., 2009).
cluding the Obama administration’s assistance, GM
The carmakers were required to produce restrucultimately received $50.2 billion through TARP, Chrysler
turing plans for financial viability by February 17, 2009.
$10.9 billion, and GMAC $17.2 billion (table 1).
The Bush administration made the TARP loans
Presidential task force
available with a number of conditions, derived from
On February 16, 2009, barely a month after he
terms in the legislation passed by the House.19 “The
took office, President Barack Obama appointed a
overriding condition is that each firm must become
presidential task force on the auto industry to devise
‘financially viable’; that is, it must have a ‘positive
a strategy for dealing with Chrysler and GM. Several
net value, taking into account all current and future
cabinet members and other top government officials
costs, and can fully repay the government loan’”
served on the task force, which was co-chaired by
(Cooney et al. 2009, pp. 8–9, emphasis in original).
a

b
c

38

2Q/2012, Economic Perspectives

Treasury Secretary Timothy Geithner and National
Economic Council Director Larry Summers. Steven
Rattner, co-founder of the hedge fund Quadrangle
Group, was named as its first lead advisor. Replacing
him later in 2009 was another advisor to the task force,
former investment banker and United Steelworkers
union negotiator Ron Bloom, who was at the time
also named senior advisor for manufacturing policy.
The composition of the task force was notable for
not including any individuals with close ties to the auto
industry. Instead, membership was drawn primarily
from the financial and legal sectors, focusing on people
with experience in restructuring troubled companies.
The task force adopted metrics for evaluation and
processes for decision-making from other industries,
rather than relying on those long in use in Detroit
Three accounting offices.20
According to Bloom, the task force considered
three policy options: 1) no further government assistance
beyond TARP loans; 2) additional loans with no strings
attached; or 3) additional financial resources tied to
restructuring.
Rattner explained that option 1 was rejected because, without government intervention, both Chrysler
and GM “would have unquestionably run out of cash
quickly, slid into [Chapter 7] bankruptcy, closed their
doors and liquidated” (Rattner, 2010b, p. 2). Rattner
considered bankruptcy to be “scary,” because customers
might be unwilling to buy from bankrupt carmakers,
especially if the proceedings dragged on for a long
time (Rattner, 2010b, pp. 2–3). “The consequences of
allowing General Motors to go into an uncontrolled
Chapter 7 liquidation would’ve been devastating,”
according to Bloom. “The ‘D’ word I’d use would be
‘devastating’” (Lassa, 2010).
Especially influential in the task force’s decision
to reject option 1 was an estimate by the Center for
Automotive Research (CAR) that nearly 3 million
jobs would be lost in 2009 if all three of the Detroitbased carmakers ceased U.S. production; CAR’s estimate was based on current employment of 239,341 at
the Detroit plants, almost 4 million indirect and supplier jobs, and over 1.7 million spin-off jobs (Cole,
McAlinden, Dziczek, and Menk, 2008).21 Regarding
option 2, Bloom argued that “[t]he costs of that would
have been in the many multiples of what we spent”
(Lassa, 2010). The task force selected option 3
(Lassa, 2010).
Rejected plans
As a condition for receiving TARP loans in
December 2008, Chrysler and GM were required to
submit restructuring plans to the Treasury Department
by February 17, 2009, in order to qualify for further

Federal Reserve Bank of Chicago

federal assistance. The task force took on the responsibility of reviewing the viability plans submitted by
Chrysler and GM. Before completing its review, the
task force created the Auto Supplier Support Program
on March 19, 2009. The purpose of the program was
to ensure that Chrysler and GM could continue to pay
their parts makers during a period of uncertainty and
tight credit.
Under normal conditions, automotive suppliers
ship parts to auto manufacturers and receive payment
45–60 days later. Suppliers typically sell or borrow
against the carmaker’s payment commitments, also
known as receivables. In early 2009, the downturn in
the economy and uncertainty regarding the future of
GM and Chrysler resulted in tightening credit for
auto suppliers. Banks then stopped providing credit
against supplier receivables (Congressional Oversight
Panel 2011b).
To implement the supplier support program, GM
Supplier Receivables LLC and Chrysler Receivables
SPV LLC were created. The Treasury committed $3.5
billion to GM and $1.5 billion to Chrysler. Those funds
were to be allocated by each carmaker to specific suppliers. Ultimately, only $290 million was loaned to GM
suppliers and $123 million to Chrysler suppliers.22 The
program was terminated in April 2010 (Congressional
Oversight Panel 2011b). All loans were fully repaid.
On March 30, 2009, President Obama announced
the results of the task force’s review. It concluded that
neither GM’s nor Chrysler’s plan had established a
credible path to viability. The task force found that
Chrysler’s plan to close plants and dealerships, reduce
labor costs, and change operations did not go far enough
(Canis and Webel, 2011). GM’s plan was found not to
be viable primarily because of “overly optimistic assumptions about prospects for the macroeconomy and
GM’s ability to generate sales” (Congressional Oversight Panel, 2011a, p. 97).
The President’s announcement offered the following lifelines to the two companies: Chrysler could obtain working capital for an additional 30 days in order
to devise a more thorough restructuring plan that would
be supported by its major stakeholders, such as labor
unions, dealers, creditors, suppliers, and bondholders
(Canis and Webel, 2011). GM was provided with 60
days of working capital in order to submit a substantially more aggressive plan (Congressional Oversight
Panel, 2011a). However, if the companies could not
meet those requirements, bankruptcy would be the
only alternative available. The task force emphasized
that while Chrysler and GM presented different issues
and problems, in each case “their best chance of success may well require utilizing the bankruptcy code

39

in a quick and surgical way” (White House, 2009b).
“In the Administration’s vision, this would not entail
liquidation or a traditional, long, drawn-out bankruptcy,
but rather a structured bankruptcy as a tool to make it
easier…to clear away old liabilities” (Congressional
Oversight Panel, 2009, p. 13).23
To assuage consumers’ concerns about Chrysler
or GM not being able to honor their product warranties,
Treasury created a program to backstop the two carmakers’ new vehicle warranties. That program was also
announced March 30, 2009. It applied to any new GM
or Chrysler car purchased during the restructuring
period (Congressional Oversight Panel, 2009).24
Chrysler restructuring
The task force seriously questioned whether
Chrysler could become a viable entity. According to
Rattner, “from a highly theoretical point of view, the
correct decision could be to let Chrysler go” (Rattner,
2010b, p. 4). If Chrysler were liquidated, buyers of its
most attractive vehicles—Jeeps, minivans and trucks—
were likely to turn to Ford and GM. “Thus, the substitution effect [of Chrysler customers switching to
Ford and GM products] would eventually reduce the
net job losses substantially. ... We intuited that the
substitution analysis was more right than wrong...”
(Rattner, 2010b, pp. 3–4). Ultimately, the task force
determined that allowing Chrysler to liquidate during
a severe recession would cause an unacceptably high
loss of jobs. However, it concluded that Chrysler was
not viable outside of a partnership with another automotive company. That partner turned out to be the
Italian carmaker Fiat.25
Bloom later claimed the task force was not very
close to letting Chrysler go under. “Rather, it was a
bargaining chip to bring in line all the parties, including
Chrysler, Fiat, Cerberus,26 the banks, the United Auto
Workers’ Voluntary Employee Beneficiary Association,
even Daimler.27... ‘Everybody needed to know there
was a very bad alternative that awaited them if they
didn’t come to the table’” (Lassa, 2010).
During April 2009, Chrysler worked with its stakeholders to devise a restructuring plan that could meet
the requirements of the task force and avert bankruptcy.
The company reached tentative agreements with most
stakeholders. Among Chrysler’s creditors, the larger
banks agreed to write down their debt by more than
two-thirds. However, some mutual funds and hedge
funds, representing about 30 percent of the company’s
debt, would not agree to the proposal. Chrysler could
only avoid bankruptcy if all of its creditors approved
the settlement, so the disagreement prompted its filing
for bankruptcy on April 30, 2009 (Webel and Canis,

40

2011). Bankruptcy “dramatically changed the nature
of the discussions that we were having with the stakeholders,” especially the debt holders (Rattner, 2010b,
p. 5).
During bankruptcy proceedings, the government
provided Chrysler with $1.9 billion of debtor-in-possession (DIP) financing, effectively a loan to a bankrupt firm allowing it to continue operating while in
Chapter 11. During bankruptcy, a DIP loan is senior
to the other claims on the firm (Congressional Oversight Panel, 2011b). “[B]ecause of the extraordinary
conditions in the credit markets [at the time],” the
task force concluded, “bankruptcy with reorganization
of the two auto companies using private DIP financing
did not appear to be an option by late fall 2008, leaving
liquidation of the firms as the more likely course of
action absent a government rescue” (Congressional
Oversight Panel, 2011b, p. 7).
To facilitate a rapid exit from bankruptcy, the
task force utilized an obscure and rarely used section
of the U.S. Bankruptcy Code known as Section 363(b)
of Chapter 11.28 “Under that section, a newly formed
company would buy the desirable assets from the
bankrupt entity and immediately begin operating as a
solvent corporation” (Rattner, 2010b, p. 3). “Section 363
allows a bankrupt company to act quickly to transfer
intact, valuable business units to a new owner. (The
conventional bankruptcy process restructures a corporation as a whole.) Once exotic and obscure, 363 had
provided the only bright spot in the cataclysmic implosion of Lehman Brothers. It was used to salvage
Lehman’s money-management and Asian businesses”
(Rattner, 2010a, p. 60).29
Through Section 363(b), Chrysler’s viable assets—
that is, the properties, contracts, personnel, and other
assets necessary for Chrysler to move forward as a viable operation—were allocated to the “new” Chrysler.
The “old” Chrysler kept the “toxic” assets destined
for liquidation or write-off permitted under bankruptcy
laws. A similar plan was later used for GM on its
journey through bankruptcy.
Chrysler had filed for bankruptcy on April 30,
2009. A mere 31 days later, on May 31, the bankruptcy
judge, Arthur J. Gonzalez, cleared the sale of all viable assets to the “new” Chrysler. Three Indiana state
pension plans that together held about 8 percent of
the company’s secured debt appealed the judge’s decision to the Second Circuit Court of Appeals in New
York, which affirmed the sale on June 5, 2009. Holders
of 92 percent of the secured debt had agreed to an
exchange of debt at a value of 29 cents on the dollar.
The Indiana funds had obtained their bonds a year
before the bankruptcy filing at 43 cents per dollar of

2Q/2012, Economic Perspectives

face value; they argued in court
Table 2
that they should have been repaid
Chrysler ownership since 2009 bankruptcy
at that value. The funds appealed
	
June	January	April	 May	 July	December
the ruling to the U.S. Supreme
Owner	
2009	2011	2011	2011	
2011	 2011
Court.
	
( - - - - - - - - - - - - - - - - - percent - - - - - - - - - - - - - - - - - - )
On June 9, the U.S. Supreme
VEBA Trust	
67.69	
63.5	
59.2	
45.9	
46.5	
41.5
Court allowed the sale of Chrysler
Fiat	
20.00	 25.0	 30.0	 46.0	53.5	 58.5
to go ahead, ending the legal
U.S. government	
9.85	
9.2	
8.6	
6.5	
0.0	
0.0
proceedings. Chrysler’s secured
Canada/Ontario
governments	
2.46	
2.3	
2.2	
1.6	
0.0	
0.0
creditors were forced to accept
30
the original offer of $2 billion.
Sources: Webel and Canis, 2011, through April 2011, and PRN Newswire (2012).
Daimler, the minority owner of
Chrysler at the time of the filing,
agreed to waive its share of
it began production of its MultiAir engine at a
Chrysler’s $2 billion second lien debt, give up its
Chrysler plant in Dundee, Michigan.
19 percent equity interest in Chrysler, and settle its
pension guaranty obligation by agreeing to pay $600
n	 A distribution event—based on Chrysler reaching
million to Chrysler’s pension funds. The private equicertain revenue targets and export market goals. In
ty firm Cerberus, the majority owner at the time of
April 2011, Fiat met this commitment when it exportfiling, also agreed to waive its second lien debt and
ed $1.5 billion of Chrysler vehicles from North
forfeit its equity stake (Congressional Oversight
America while also opening up its European and
Panel, 2009). Upon exiting from Chapter 11, the new
Latin American dealer networks to Chrysler vehicles.
Chrysler received a final TARP installment from the
n	 An ecological event—reached when regulators
federal government of $4.6 billion in working capital
approved and U.S. production began of a new
and exit financing to assist in its transformation to a
vehicle with fuel efficiency of at least 40 miles per
new, smaller automaker (Webel and Canis, 2011).
gallon. Fiat announced in December 2011 that it
The largest equity owner in new Chrysler was
would meet this commitment by assembling at its
initially the United Auto Workers’ health care retireBelvidere, Illinois, plant the Dodge Dart, a new
ment trust, a VEBA with an ownership share of 67.69
Fiat-based small car with a fuel efficiency of 40
percent. The union’s VEBA trust was accorded a large
miles per gallon (Webel and Canis, 2011).
piece of new Chrysler because old Chrysler’s retiree
On May 24, 2011, Chrysler refinanced and paid
health care liability of $8.8 billion could not be met,
back
its U.S. and Canadian government loans in full.
as originally stipulated in the 2007 agreement, with a
Fiat
exercised
a call option to increase its ownership
cash contribution. Half of that claim was converted
interest
by
an
incremental
16 percent, on a fully diluted
into a 55 percent ownership stake. In exchange for
basis.
On
July
21,
Fiat
reported
it had paid $500 million
the other half, the UAW VEBA received a $4.6 billion
to
purchase
the
remaining
6
percent
ownership interest
unsecured note from the new Chrysler (Webel and
31
by
the
U.S.
Treasury
and
$125
million
for the remaining
Canis, 2011).
1.5
percent
ownership
held
by
the
Canadian
governFiat initially obtained 20 percent of Chrysler’s
ment.
By
the
end
of
2011,
Fiat’s
stake
in
Chrysler
had
equity without making any direct financial contribureached
58.5
percent.
Going
forward,
“Fiat’s
share
could
tion (table 2). The justification was that Fiat was to
rise to more than 70 percent if it exercises the rights it
manage Chrysler and to develop competitive prodholds to purchase some of the UAW VEBA Trust stake.
ucts, especially small, fuel-efficient vehicles (Webel
32
Fiat purchased these rights from the U.S. Treasury for
and Canis, 2011).
$60 million” (Webel and Canis, 2011, p. 8).
The bankruptcy court’s decision outlined steps
In offering a final accounting of the Chrysler
that Fiat could take to raise its equity stake in Chrysler
bailout,
the Congressional Research Service estimated
by a total of 15 percent of additional equity by meeting
a
$1.3
billion
gap between the funds loaned to Chrysler
three performance benchmarks:
and the funds recouped (see table 1). TARP had pron	 A technology event—when it obtained regulatory
vided $10.9 billion in loans to support the company.
approval and began U.S. production of a fuelIn return for this $10.9 billion, the government earned
efficient engine based on Fiat engine designs.
approximately $1.7 billion in interest and other fees
Fiat met this commitment in January 2011 when
and recouped approximately $7.9 billion in principal

Federal Reserve Bank of Chicago

41

($5.5 billion in loan repayments, $1.9 billion recouped
from the bankruptcy process of the old Chrysler, and
$560 million paid by Fiat for the U.S. government’s
new Chrysler common equity and rights), resulting in
a $1.3 billion loss (Webel and Canis, 2011).33
GM restructuring
By the end of March 2009, the task force had
concluded that GM’s situation was different from that
of Chrysler: GM was too big to fail. “We soon could
not imagine this country without an automaker of the
scale and scope of General Motors. The task became
not whether to save GM but how to save GM” (Rattner,
2010b, p. 3). To that end, the task force decided that
GM could not survive under its existing leadership.34
Consequently, GM CEO Rick Wagoner stepped down
at the request of the task force at the end of March
2009.35
Like Chrysler, GM could not reach agreement
with all of its stakeholders outside of bankruptcy. The
company followed the path established by Chrysler and
filed for bankruptcy on June 1. In just over five weeks,
on July 10, 2009, a new GM emerged from protection.
During the bankruptcy proceedings, the government
provided a final TARP installment of $30.1 billion as
DIP financing, bringing total U.S. government loans
to GM to $50.2 billion (see table 1).36
The U.S. government was the majority owner of
the new GM that emerged from the bankruptcy process,
as most of the TARP loans made to GM were converted
into an initial 60.8 percent ownership stake (Canis and
Webel, 2011). In addition, the governments of Canada
and Ontario together held 11.7 percent, the VEBA held
17.5 percent, and unsecured bondholders and creditors
of the old GM held 10 percent (table 3).37
Sixteen months after emerging from Chapter 11
bankruptcy, GM launched an initial public offering
(IPO) on November 18, 2010. The IPO sold shares
worth $23.1 billion, making it at the time the largest
IPO in U.S. history, and was widely considered a success. GM initially had set a target price in the range
of $25–$26 per share. In the days prior to the offering,
market interest seemed strong, and the offering price
was raised to $33 a share. In addition, more shares
were sold than originally intended due to the strength
of investor demand. As a result, the U.S. Treasury was
able to sell more of its shares than had been anticipated,
although it realized losses (Congressional Oversight
Panel, 2011b; Canis and Webel, 2011). Both the VEBA
and the Canadian government sold shares as well.38
Following the IPO, the U.S. government’s stake in
GM dropped to around 32 percent or approximately
500 million shares. In order for the government’s

42

Table 3

GM ownership since 2009 bankruptcy
				
	
July	December
Owner	
2009	2011
	( - - - - percent - - - - )
U.S. government	
Canada/Ontario governments	
VEBA trust	
Unsecured bondholders	
Common shareholders	
Pension plan	

60.8	
11.7	
17.5	
10.0	
—	
—	

32.0
9.0
10.3
9.6
35.2
3.9

Sources: Canis and Webel, 2011, and Schwartz, 2011b.

remaining 32 percent of the company to be worth
$26.2 billion, representing all of the government’s
remaining unrecovered investment, GM’s market
capitalization would have to be approximately $81.9
billion (SIGTARP, 2012). To achieve this market capitalization, the price of GM stock would have to exceed
$52 per share, or more than twice its price in April 2012.
The new GM differed from the old GM in a
number of important ways:
n	 Lower labor costs—GM’s North American bill
for hourly labor declined from $16 billion in 2005
to $5 billion in 2010 (Congressional Oversight
Panel, 2011b).
n	 Lower level of employment—Old GM had 111,000
hourly employees in 2005 and 91,000 in 2008.
New GM had 75,000 immediately after bankruptcy
in 2009 and 50,000 in 2010 (Congressional Oversight Panel, 2011b).
n	 Fewer plants—GM had closed 13 of the 47 U.S.
assembly and parts plants it operated in 2008. Most
of the closed plants and machinery remained with
old GM.
n	 Fewer brands—GM’s Pontiac, Saturn, and Hummer
brands were terminated, and Saab was sold. GM
retained four nameplates in North America:
Chevrolet, its mass-market brand; Cadillac, its
premium brand; Buick; and GMC. GM retained
Buick primarily because of the brand’s strength in
China and GMC because of its strength as a higherpriced truck nameplate. GM also reduced its dealer
network by about 25 percent.39
n	 Retiree health care costs—The GM restructuring
agreement gave the VEBA a significant ownership
stake in GM because at the time the company did
not have the financial resources to provide cash.
Bankruptcy also removed expensive liabilities
from GM’s balance sheet.40 Left with old GM were

2Q/2012, Economic Perspectives

environmental liabilities estimated at $350 million for
polluted properties, including Superfund sites; certain
tort liability claims, including those for some product
defects and asbestos; and contracts with suppliers with
whom the restructured GM would not be doing business (Canis and Webel, 2011).41
New GM not only emerged with much-reduced
debt, it also had a much lower break-even point—the
volume of cars at which the company’s revenues equal
its costs. “In 2007, GM needed a 25 percent market
share, or roughly 3.88 million vehicles sold out of a
market of 15.5 million, in order to break even. Today
[2011], GM needs a market share of less than 19 percent, or approximately 2.09 million vehicles sold out
of a market of 11 million. In sum, GM is now able to
break even with a smaller share of a smaller market. …
This improvement has been driven in part by the reduction in labor costs, in addition to improvements
in vehicle pricing” (Congressional Oversight Panel,
2011b, p. 32).
Government post-bankruptcy initiatives42
As the presidential task force on the auto industry
neared completion of its restructuring efforts, President
Obama signed Executive Order 13509 on June 23, 2009,
creating the White House Council for Automotive
Communities (renamed in 2010 to the White House
Council on Automotive Communities and Workers).
The function of the Council was “to establish a coordinated federal response to issues that particularly impact
automotive communities and workers and to ensure
that federal programs and policies address and take
into account these concerns” (see the Federal Register
document at www.gpo.gov/fdsys/pkg/FR-2009-0626/pdf/E9-15368.pdf).
The first executive director of the council was Ed
Montgomery, a University of Maryland economist.43
The principal activity of the Auto Communities Office
has been to identify appropriate federal funding sources
to assist communities negatively impacted by the auto
industry restructuring, especially in the Great Lakes
states. Examples include funds from Treasury, the U.S.
Environmental Protection Agency (EPA), and the
U.S. Department of Justice to clean up sites of closed
plants, as well as the Department of Energy’s $2.4 billion
initiative to accelerate the manufacturing and deployment of the next generation of batteries and electric
vehicles (see Klier and Rubenstein, 2011).44
To stimulate sales of new vehicles, the federal
government sponsored the Car Allowance Rebate
System (CARS) during the summer of 2009. The program, originally announced in the President’s March
30 speech and more commonly known as “cash for

Federal Reserve Bank of Chicago

clunkers,” provided consumers with a credit of
$3,500–$4,500 toward the purchase of a new vehicle
if they scrapped an older vehicle (see, for example,
Mian and Sufi, 2010, and Li, Linn, and Spiller, 2011).
To qualify, the scrapped vehicle had to be currently
registered, less than 25 years old, and have fuel economy rated by the EPA at 18 mpg or less. The program
was originally planned to disperse $1 billion over three
months, but when demand proved much higher than
expected, Congress appropriated an additional $2 billion.
Due to the program, light vehicle sales temporarily
jumped to 14.2 million units, measured at a seasonally
adjusted annual rate, in August 2009, up from July’s
11.3 million units. Well-timed to sustain a budding
recovery in vehicle sales at the time, the program’s
net effect was rather small.45
Assessment of government intervention
At the time of this writing, almost three years
have passed since the bankruptcy filings. The industry
has recovered slowly but steadily, and all three Detroit
carmakers reported profits for 2011.46 Yet opinions
regarding the government interventions are still divided,
as evidenced by the different responses to Chrysler’s
2012 Super Bowl ad, which referenced the company’s
recovery (see Fifield, 2012).47, 48
The White House has made it clear that it considers
the restructuring of Chrysler and GM a success. A year
after the bankruptcy filings, the administration stated,
“[w]hile this process of regaining long-term financial
health will require much work, innovation, and perseverance, there is no doubt that over the course of
the past year they have moved back from the brink to
a position of contributing to the economic recovery
of the nation and auto communities” (White House
2010, p. 16). More recently, President Obama cited
the auto industry intervention in his 2012 State of the
Union address as a success of his administration’s
manufacturing policy (White House, Office of the
Press Secretary, 2012). Around the same time, in remarks delivered at the National Automobile Dealers
Association convention, former President George W.
Bush stated that he would “make the same decision
again if I had to” (Wilson, 2012).
A more formal and quite extensive evaluation of
the government’s intervention in the auto sector was
performed by a congressional oversight panel, a bipartisan body created by Congress in 2008 in the underlying TARP statute.49 Established with the purpose
of reviewing the current state of financial markets
and the regulatory system, this committee has issued
several reports on TARP overall, as well as specifically
on the auto industry.50 The committee consisted of

43

five members, one each appointed by the majority
and minority leaders of the House and the Senate, as
well as one jointly appointed by the Speaker of the
House and the majority leader of the Senate. Its reports
were unanimous.
The panel concluded that the restructuring had
succeeded.51 “The industry’s improved efficiency has
allowed automakers to become more flexible and better
able to meet changing consumer demands, while still
remaining profitable. Improved production procedures
and lower inventory have resulted in fewer discounts
on new car sales, improving the profitability on each
car sold” (Congressional Oversight Panel, 2011b, p. 15).
“Treasury was a tough negotiator as it invested taxpayer funds in the automotive industry. The bulk of
the funds were available only after the companies had
filed for bankruptcy, wiping out their old shareholders,
cutting their labor costs, reducing their debt obligations
and replacing some top management” (Congressional
Oversight Panel, 2009, p. 2).
In its evaluation, the panel raised four principal
concerns with regard to the government intervention:
1.	 Some recovery of the U.S. auto industry would
have occurred anyway, even with the liquidation
of Chrysler and possibly GM.52 In addition, the
panel asked if TARP would be able to reverse the
long-term decline of the Detroit-based carmakers.
2.	 The rescue of Chrysler, GM, and their financial
arms created a moral hazard. The panel raised the
issue of an ongoing implicit guarantee from the
government with respect to the entire TARP program, as well as specifically in the case of the
auto industry.
3.	 The use of TARP money was “controversial”
(Congressional Oversight Panel, 2011b, p. 4) as
the definition of “financial firms” in the TARP
legislation did not mention manufacturing companies, such as the Detroit Three carmakers (Canis
and Webel, 2011, p. 2).53
4.	 Finally, the panel pointed out that government assistance had not yet resulted in a positive return
on the taxpayers’ investment.54
The panel also suggested improvements to the
governance of the bailout process, such as improved
transparency of both Treasury and company management, establishment of clear goals and benchmarks to
facilitate evaluation of progress, and a better balance
between Treasury’s dual roles as shareholder and
government policymaker (Congressional Oversight
Panel, 2011a).

44

Industry restructuring
We have summarized the events leading up to
the government intervention in this industry and the
details of the restructuring. Now, we look at how the
structure of the U.S. auto industry has subsequently
changed. We focus on significant changes in four
areas: utilization of production capacity; geographic
distribution of production facilities; allocation of
market share among the major producers; and cost
structure.
Production capacity
Auto assembly is a capital-intensive undertaking.
An assembly plant costs hundreds of millions of dollars
to build, employs several thousand workers when
operated at capacity, and produces more than 200,000
units per year under standard operating conditions.
As is typical for capital-intensive industries, auto
assembly is characterized by significant barriers to entry
(as well as to exit), at least at a global scale. However,
at the regional scale, as the auto industry has become
more international, existing producers have expanded
assembly operations beyond their home region. As a
result, the North American auto industry has been
impacted significantly by the arrival of foreign-headquartered producers.
Volkswagen was the first foreign-based carmaker
to start assembling vehicles in the United States, when
it opened a plant in western Pennsylvania in 1978.55
Since then, ten other foreign carmakers have set up
assembly plants in North America, raising the count
of producers operating full-scale assembly operations
to 14. In 2010, foreign-headquartered producers accounted for 44 percent of all light vehicle production
in North America.
Although the number of companies assembling
light vehicles in North America increased to 14 by
2010, the overall number of North American assembly
plants remained rather stable, averaging 77 between
1980 and 2007. As foreign-headquartered carmakers
opened new assembly plants in North America, the
three Detroit-based carmakers closed some of theirs
(figure 2).
What role did the restructuring during the Great
Recession play? Most importantly, it resulted in an
unprecedented number of plant closures. Between
January 2008 and December 2010, the Detroit Three
shut 13 assembly plants in North America and announced the closure of three more. The number of
plants closed by Detroit carmakers during the two
years of the recession matched the number of plants
closed during the previous seven years of the decade,

2Q/2012, Economic Perspectives

Capacity utilization in the production of light vehicles in the
Light vehicle assembly plants in North America;
United States averaged 77.6 percent
Detroit Three versus foreign producers, 1980–2012
between 1972 (when data collection
for that series began) and 2007. In
90
the auto industry, capacity utilizaIndustry
80
tion rarely reaches 90 percent, even
during peak sales years. During re70
cessions, capacity utilization below
Detroit Three
60 percent has been common (it
60
occurred for a combined total of
50
40 months between 1972 and
2007). At the depth of the Great
40
Recession, during January 2009,
a record-low level of 25.9 percent
30
was recorded for capacity utiliza20
tion in light vehicle assembly in the
Foreign-headquartered
United States. However, after the
10
producers
restructuring of GM and Chrysler,
0
industry capacity utilization rose
1980
’84
’88
’92
’96
2000
’04
’08
’12
more rapidly than did production,
Notes: GM’s Spring Hill, Tennessee, plant, formerly the Saturn plant, is not counted as
as a result of the large number of
closed in this chart. It was idled beginning in 2009 and, according to the 2011 contract
plants that the Detroit Three closed
between the UAW and GM, will reopen in 2012.
Source: Ward’s Auto Group, Auto Infobank, online database; company websites.
during the bankruptcy proceedings.
Since capacity utilization is a
key driver of profitability for carmakers, the unprecedented number
a period during which Detroit had significantly reof assembly plant closures during the recent restrucduced its production capacity.
turing is enabling carmakers to achieve profitability
To illustrate the outsized response in plant closat historically low output levels.
ings, we can compare the most recent downturn with
Industry geography
the period between 1978 and 1982, a similar event
The massive capacity reduction between 2007
according to several measures. U.S. employment in
and
2009
also altered the footprint of the auto indusvehicle assembly fell by 34 percent during the recent
try
by
accelerating
the clustering of nearly all U.S.
recession and by 32 percent between 1978 and 1982.
auto
production
in
the
interior of the country, in an
Similarly, employment in motor vehicle parts producarea
known
as
auto
alley.
Auto alley is centered along
tion declined by 32 percent during 2007–09 and by
north–south
Highways
I-65
and I-75 between the
28 percent during 1978–82. Production in light vehiGreat
Lakes
and
the
Gulf
of
Mexico.
Beginning around
cles fell by 46.5 percent in the most recent recession
1980,
the
Detroit
Three
and
the
international
carmakand by 45.4 percent in the earlier recession. Yet, the
ers
constructed
nearly
all
of
their
new
production
facilicapacity adjustment was much smaller then. Only six
ties
in
auto
alley,
and
the
Detroit
Three
began
to
close
assembly plants were shut between 1979 and 1983,
plants elsewhere in the country. The main impetus for
compared with 14 between 2008 and 2011.
the reconcentration of vehicle assembly in the interior
The recent plant closures correspond to a removal
of the country was the fact that nearly all vehicle
of approximately 2.6 million units of production capacimodels were produced at only one assembly plant.
ty in North America. The vast majority, 2.36 million
56
The plants in turn shipped their products from their
units, was taken out in the U.S. A result of this sharp
respective locations across the country to serve the enand rapid reduction in capacity has been a decoupling
tire market. Transportation cost efficiency necessitated
of the traditional relationship between the level of
an interior location. Agglomeration economies between
capacity utilization and the level of production in this
assembly and supply chain locations kept both types of
industry (see figure 3, which illustrates the change for
57
activities co-located.
the U.S.).
figure 2

Federal Reserve Bank of Chicago

45

figure 3

U.S. light vehicle production and capacity
percent of capacity, SAAR
100

units in millions, SA
14

Capacity utilization
(left-hand scale)

90

13
12

80

11
70

10

60

9
8

50

7
40
6
30

Industrial production
(right-hand scale)

5

shipping assembled vehicles to consumers. Second, as a result of a
more concentrated footprint, the
Detroit Three operate major manufacturing facilities in a
noticeably smaller number of states.
The number of states with a Detroit
Three assembly plant declined from
16 in 2007 to ten in 2011.59 On the
other hand, the foreign-headquartered carmakers had assembly
plants in ten states in 2011, compared to eight in 2007. The widespread opposition to the rescue of
Chrysler and GM reflected in part
the small number of states with substantial Detroit Three employment
(in 1980, the count had been 19).

Market share
Despite the remarkable turmoil
experienced by the auto sector durNotes: SA indicates seasonally adjusted; SAAR indicates seasonally adjusted
ing the recent recession, none of the
annual rate.
Sources: Board of Governors of the Federal Reserve System and Haver Analytics.
carmakers exited the industry. As a
result, the auto industry is more
competitive in 2011 than it was just
five years ago. The share of the largest four compaAuto alley’s share of U.S. light vehicle production
nies in U.S. light vehicle sales dropped from 75 perrose from 78 percent in 2007 to 83 percent in 2011.58
cent in 2000 and 67 percent in 2007 to 60 percent in
By the end of 2011, all assembly activity was located
2011. Seven companies each held at least 5 percent
in the interior of the country (figure 4). The only two
of the market in the United States last year. It appears
assembly plants not shown in the 2011 version of the
as if the U.S. industry structure is moving toward the
assembly map are located in the state of Texas.
European market structure, with eight sizable playThe restructuring of the Detroit Three carmakers
ers, but few representing more than 20 percent of the
has also resulted in a change in the distribution of
market.
assembly plants within auto alley. Since 2007, the
During the decade leading up to bankruptcy, the
production share of the Detroit Three in the southern
share of U.S. automotive sales held by the Detroit Three
half of auto alley (Kentucky and south) has dropped
had plummeted from 72 percent in 1997 to 47 percent
by half, from 23 percent to 12 percent. In the northern
in 2008. The Detroit Three had been losing market
half, it has remained constant at 74 percent. This bishare for decades, but at a much more modest rate.
furcation shows up even stronger at a higher level of
Their market share had declined from 95 percent in
resolution. The highway labeled US 30 runs east–west
1955 to 75 percent in 1980, but then had stabilized at
through northern Ohio, Indiana, and Illinois. At the
70–75 percent during the 1980s and 1990s (Klier, 2009).
end of 2011, the Detroit Three were operating 17
In contrast, the Detroit Three gained market share
assembly plants north of US 30 and two to the south
in 2011 for the first time since 1995—moving up to
(see horizontal line in figure 4, panel B). The foreign47 percent from 45 percent in 2010. Detroit Three
headquartered carmakers have 16 assembly plants
sales increased from 4.7 million in 2010 to 5.4 million
south of US 30 and only one to the north. That plant
in 2011, whereas those by foreign-headquartered caris scheduled to revert to Ford in the near future.
makers increased more modestly—from 5.7 million
The changing distribution of auto plants during
in 2010 to 6.1 million in 2011.
the restructuring is significant for two reasons. First,
The two restructured companies—Chrysler and
the concentration of Detroit Three assembly plants in
GM—increased their respective market share from
the northern portion of auto alley reduces transporta9.3 percent to 10.7 percent and from 19.1 percent to
tion costs for both receiving parts from suppliers and
20
1978 ’81

46

’84

’87

’90

’93

’96

’99

2002

’05

’08

’11

4

2Q/2012, Economic Perspectives

figure 4

Location of assembly plants in U.S. and Canada
label
A. 2007 label

B. 2011

Assembly plants

Assembly plants

Detroit Three plants

Detroit Three plants

Detroit Three plants closed
between 2007 and 2011
Foreign producers

Foreign producers

0

100

200

300

miles

Highway 30
0

100

200

300

miles

Notes: Neither map shows two assembly plants located in Texas. In 2007, there was also a plant on the West Coast in the San Francisco Bay area.
Source: Ward’s Auto Group, Auto Infobank, online database.

19.7 percent. Ford’s market share declined from 17.0
percent to 16.6 percent, primarily because Volvo was
counted in Ford’s total for the first seven months of
2010 until it was sold to Zhejiang Geely in August
2010.60 Especially noteworthy for the Detroit Three
was the increase in the share of their sales accounted
for by passenger cars rather than trucks, after three
decades of having ceded most of the high-volume
family car market to the Japanese carmakers. Detroit
Three passenger car sales increased from 1.7 million
in 2010 to 1.9 million in 2011, representing an increase in market share.
It is possible that the market share gain for the
Detroit Three in 2011 may turn out to be an anomaly,
reflecting the severe disruptions in production faced
by their Japanese competitors following the March 2011
earthquake and tsunami in Japan and the October 2011
floods in Thailand. It is possible, however, that the improved performance of the Detroit Three in 2011 represents a genuine shift in momentum, as Japanese
carmakers have suffered a number of other setbacks as
well. For example, the high value of the yen has had
a negative impact on profits, and several key models
have received lukewarm or negative reviews upon

Federal Reserve Bank of Chicago

introduction. At the same time, the Detroit Three have
introduced new models, especially smaller passenger
cars, that have been favorably reviewed and are selling
at much faster rates than the models they replaced.61
It is too early to tell which of these competing explanations will hold.
Cost structure
Labor costs were long cited as an important contributor to the uncompetitive position of the Detroit
Three. Over the years, the companies’ labor cost
structure had become essentially fixed, as job security
became a key element of successive labor agreements
with the UAW. In addition, health care and pension
liabilities skewed the competitive landscape against
the domestic carmakers.62
The UAW and the Detroit Three began to address
labor cost issues with the 2007 labor agreement. That
contract for the first time introduced a much lower second-tier wage; established the VEBAs, which would
ultimately, once funded, take on the health care liability for active and retired workers; and severely curtailed
the reach of the infamous “jobs bank.”63

47

As a result of the 2007 contract, the UAW average
hourly wage was $29.06.64 Wages at the Detroit Three
were somewhat higher than those at foreign-owned
assembly plants: $26 per hour at Toyota and $25 at
Honda in 2007. However, when the total cost of production labor—including benefits—was calculated,
the gap between the Detroit Three and foreign-owned
assembly plants was much bigger: The hourly average
became $61.48 at the Detroit Three versus $47.50 at
Toyota in 2007 (McAlinden, 2008).65
In light of the recession that soon followed, the
agreements from 2007 were not able to address the
uncompetitive labor cost structure of the Detroit carmakers fast enough. During the industry downturn
and financial crisis, the UAW and the Detroit carmakers
were engaged in continuous negotiations to find ways
to bring down costs. For example, the union agreed to
a no-strike clause for GM and Chrysler through 2015;
differences during contract negotiations would have
to be resolved by binding arbitration while the no-strike
clause was in effect. In its December 2008 restructuring
plan, Ford had attached a table that illustrated its labor
cost breakdown. Wages and wage-related costs in 2008
were $43 per hour, versus an average of $35 per hour
at foreign-owned U.S. auto manufacturers. However,
Ford’s all-in hourly labor cost came to $71, versus
$49 for the foreign-owned companies. The principal
difference was legacy costs of $16 per hour, versus
comparable costs at foreign companies of $3 per hour
(Cooney et al., 2009).66
Post restructuring, the negotiations between the
UAW and the Detroit producers regarding a new 2011
master contract were rather important. The outcome
would indicate if the lessons learned during the painful restructuring would soon be forgotten. The union
stated upfront that it expected to be made whole for
the concessions its membership had made during the
downturn. By the same token, the Detroit producers
argued that key to sustainable profitability was continued competitiveness of vehicle production within
North America. At the end, the contracts negotiated
and ratified during September and October 2011 found
a way to address both concerns. While fixed labor costs
hardly rose, variable pay options for union members
were increased significantly. Detroit’s labor costs were
now competitive with foreign producers operating
within North America. Hourly labor costs ranged
from $58 at Ford to $52 at Chrysler, compared with
$55 for Toyota (see McAlinden, 2011).67

48

Summary and outlook
As the U.S. auto industry started to recover from
a sharp and deep recession, the Detroit Three became
profitable again. During the fall of 2011, both Ford’s
and GM’s credit ratings were upgraded to within a shade
of investment grade.68 At the beginning of December
2011, Ford decided to reinstate its dividend for the
first time since 2006. And capacity utilization in U.S.
vehicle production had returned to respectable levels
by the end of 2011. Chrysler turned out to be the real
surprise story of this recovery. Virtually given up for
dead in early 2009, the company had repaid all its
loans by mid-2011, several years ahead of schedule.
It was rolling out new products and gaining market
share in the process.69
This article recapped the main events of the industry’s decline and restructuring. It is hard to say
how much of the current recovery is attributable to
the government intervention, but we can say that the
ensuing restructuring of the Detroit carmakers has
substantially changed the U.S. auto industry, perhaps
permanently. A large number of assembly plants have
closed, reducing assembly capacity while reinforcing
auto alley as the dominant footprint for the industry.
The new labor contract between the Detroit Three and
the UAW, agreed upon in late summer 2011, provides
for wage competitiveness going forward. Despite the
turmoil, no carmaker exited the industry, making for
a very competitive environment. Looking ahead, the
industry is facing a very dynamic stretch in light of
stricter regulations on vehicle safety and fuel efficiency.
In addition, there is significant uncertainty about the
evolution of engine and transmission technologies. This
unfolding story suggests that the newfound competitiveness of Detroit will be thoroughly tested over the
coming years.

2Q/2012, Economic Perspectives

NOTES
By 2008, Chrysler Financial and GMAC, once the captive financing arms of Chrysler and GM, were owned by Cerberus Capital
Management, a private investment firm. Cerberus owned 100 percent of Chrysler Financial and 51 percent of GMAC.

1

For example, AutoNation, one of the country’s largest publicly
held dealer groups, reported a 20 percent decline in vehicle sales
immediately after the collapse of Lehman Brothers—Lehman filed
for bankruptcy on September 15, 2008 (Strauss and Engel, 2009).

2

As the economy came out of the 1991 recession, vehicle sales
grew by more than 3 percent each year between 1992 and 1994.
Other than that, vehicle sales fluctuated by more than 3 percent
only one more time (8.9 percent in 1999) through the end of 2007.

3

Ward’s Auto Group, Auto Infobank, online database.

4

Data from the Bureau of Labor Statistics via Haver Analytics.
A number of these job cuts took place via buyouts (see note 7). In
addition, the Detroit carmakers vertically disintegrated a large part
of their in-house parts operations by spinning off Visteon (Ford) and
Delphi (GM) around the turn of the century. Both parts companies
subsequently downsized their U.S. operations in drastic fashion.

5

6
Loomis (2006) wrote in her Fortune magazine cover story that at
GM, “the evidence points, with increasing certitude, to bankruptcy.”
York (2006) suggested in a speech to the Detroit auto show that
GM’s rate of cash burn at the time would be sustainable for roughly
another three years. No separate bond ratings were available for
Chrysler at the time, since it had merged with the German carmaker
Daimler.
7
In light of the dire situation the carmakers were in, the UAW agreed
that retirees would, for the first time, pay monthly health care premiums as well as co-payments for doctor visits and prescriptions.
Active workers would forgo a $1.00 per hour wage increase with
the money going toward retiree benefits (Vlasic, 2011). Notably,
this agreement was reached while the existing labor contract was
good for another year.
8
Between 2006 and 2010, the Detroit Three eliminated over 100,000
jobs that way (Bunkley, 2009).

The VEBA was scheduled to take over responsibility for providing
health benefits to more than 700,000 members and dependents on
January 1, 2010. The total value of the trust was set to be about
$57 billion, with GM providing about $32 billion, Ford roughly
$14 billion, and Chrysler about $11 billion. In total, the Detroit
Three contributions were projected to fund 64 percent of the future
retiree health obligations (O’Brien, 2008). The VEBA is overseen
by a board consisting of 11 members—six independent directors
approved by the courts and five UAW designees.
9

10
GM had approached the Treasury several weeks earlier with a
request for aid, but had been turned down (Vlasic, 2011). Before
that, during midsummer of 2008, GM attempted to raise funds both
by selling assets and borrowing; however, the debt market had
pretty much shut down by then (Vlasic, 2011). That prompted GM
to hold discussions about a possible merger with either Chrysler or
Ford soon thereafter. The discussions between GM and Chrysler
went on between July and October of 2008.

Ford had started to implement its new business plan prior to the
onset of the recession. The plan was centered around a focus on the
Ford brand and a revival of the company’s car business. It included
spinning off brands such as Aston Martin (2007), Jaguar and Land
Rover (2008), and Volvo (2009). The business plan had started to

show positive effects by the beginning of 2008, when Ford reported
a small quarterly profit. The company’s U.S. market share bottomed
out in September 2008, six months earlier than those of its hometown competitors. Within nine months, Ford had essentially made
up the market share it had lost since the beginning of 2006. Ford
also had the benefit of having secured a large line of credit well before financial markets seized up. The company did, however, apply
for loans under the Department of Energy’s Advanced Technology
Vehicles Manufacturing Program. In September 2009, Ford received
a $5.9 billion loan as part of that program to finance up to 80 percent
of qualified expenditures to produce more fuel-efficient vehicles
(Vlasic, 2011).
The lack of support was accentuated during the hearings by the
revelation that the three CEOs had flown to Washington on private
jets (Vlasic, 2011).

12

A last-minute negotiating effort led by Senator Bob Corker failed
to reach agreement on the following three conditions: GM and
Chrysler had to cut their debt by two-thirds, the union had to take
stock instead of cash for half the VEBA, and wages and benefits
needed to match those in plants of foreign competitors within a
year (Vlasic, 2011). Ultimately, conditions similar to these became
part of both the Bush and Obama administrations’ rescue efforts
(see below).

13

“The company needed a bare minimum of $10 billion on hand
just to stay in business and maintain its rolling schedule of paying
suppliers for parts” (Vlasic, 2011, p. 273).

14

The decision to support the auto industry was communicated to
the incoming administration. However, Rattner (2010a) reports
there was little cooperation between the outgoing and incoming
administrations.

15

In conjunction, the governments of Canada and Ontario supported Chrysler and GM by extending initial interim loans representing
20 percent of the U.S. interim financing on December 20 (Industry
Canada, 2009). Ultimately the Canadian support package for both
carmakers amounted to CDN$14.4 billion ($10.6 billion to GM
and $3.8 billion to Chrysler). See Shiell and Somerville, 2012.
16

TARP authorized the Secretary of the Treasury to purchase troubled
assets from financial firms. Guiding principles for the Treasury’s
management of TARP were: to protect taxpayer investments and
maximize overall investment returns within competing constraints;
to promote stability for and prevent disruption of financial markets
and the economy; to bolster market confidence to increase private
capital investment; and to dispose of investments as soon as practicable, in a timely and orderly manner that minimizes financial market
and economic impact (U.S. Department of the Treasury, 2010, p. 10,
quoted in Canis and Webel, 2011, p. 3.)

17

GM also received a $1 billion loan from Treasury on December
29, 2008. The ultimate funding of the $1 billion agreement was dependent upon the level of investor participation in a GMAC rights
offering (it turned out to be $884 million). Pursuant to the rights of
the loan agreement, in May 2009 Treasury exchanged its $884 million
loan to old GM for a portion of old GM’s common equity interest
in GMAC (U.S. Department of Treasury, 2012). That’s why here
and in table 1, the initial support for GMAC is listed as $6 billion
($5 billion plus the $1 billion loan to GM at the time).

18

11

Federal Reserve Bank of Chicago

The primary difference was the requirement that U.S. employees
of GM and Chrysler accept reductions in their compensation to
bring it into line with that of employees in foreign transplants in
the United States (Cooney et al., 2009). President Bush’s team

19

49

compromised between elements of the House bill and the specific
conditions put forth by Senator Corker by including requirements
similar to Corker’s, but making them nonbinding and subject to the
judgment of the administration’s “car czar” (Rattner, 2010a, p. 41).
Rattner (2010a) later argued that “Bush appropriately designated
the Treasury Secretary as the ultimate authority under the loan
agreements, effectively declaring that there would be no independent
car czar. Finally, adopting Corker’s conditions—as imperfect as
they were—provided a baseline of expected sacrifices that paved
the way for our demands for give-ups from stakeholders”(p. 42).
“This was not a managerial job; it was a restructuring and private
equity assignment” (Rattner, 2010a, p. 48).
20

The estimates of job losses varied considerably. The Council of
Economic Advisers expected a loss of more than 1 percent in real
GDP growth and about 1.1 million jobs, including parts production
companies and dealers (Congressional Oversight Panel, 2011b).
Moody’s Analytics chief economist Mark Zandi estimated the total
job losses from a liquidation of Chrysler and perhaps GM would
ultimately be about 2.5 million. The Economic Policy Institute
suggested an even bigger number, 3.3 million (Zandi, 2008; Scott,
2008; Executive Office of the President, 2010).
21

There were fees associated with tapping into that program. According
to Rattner (2010a), “suppliers thought twice before signing up.”

22

The history of Delphi’s slow recovery from bankruptcy provides
some justification for wanting to act more promptly. GM’s former
parts subsidiary, Delphi, was spun off as a separate company in
1999. The company filed for bankruptcy in October 2005, but it
took four years until it emerged from Chapter 11 in October 2009.
Moreover, the new company only returned to the public markets
with an initial public offering in November 2011.
23

24
Treasury committed $640.7 million to this program—$360.6
million to GM and $280.1 million to Chrysler. On July 10, 2009,
the companies fully repaid Treasury (Office of the Special Inspector
General of the Troubled Asset Relief Program [SIGTARP], 2012).

Chrysler had begun discussions with Fiat a year earlier
(Congressional Oversight Panel, 2009, p. 12, fn. 37; Vlasic, 2011).

cost factors, such as the cost to the government to borrow the funds
that it then provided to Chrysler, a premium to compensate the
government for the riskiness of the loans, and the cost to the government in managing the assistance given (Canis and Webel, 2011).
Rattner (2010b) suggested that the auto team never anticipated a
full recovery of the capital infusion, considering the industry bailout succeeded in avoiding considerable economic and human
calamities.
Rattner (2010b) states that “if ever a board needed changing, it
was GM’s, which had been utterly docile in the face of looming
disaster. ... The top brass was sequestered on the uppermost floor
[of corporate headquarters], behind locked and guarded glass doors. ...
Analyses seemed engineered to support pre-ordained conclusions. ...
[GM leaders] appeared to believe that virtually all their problems
resulted from some combination of the financial crisis, oil prices, the
yen–dollar exchange rate, and the UAW” (Rattner, 2010b, pp. 4–5).

34

35
At the time, it was announced that GM’s board would be overhauled.
Six of the existing members, including the long-time lead director
George Fisher, would resign by the time new GM emerged from
bankruptcy. The open slots on GM’s board were filled by the auto
task force. Chrysler’s board was also restructured during bankruptcy.
36
As of December 31, 2011, the GM entities had made approximately
$756.7 million in dividend and interest payments to Treasury under
AIFP. New GM repaid the $6.7 billion loan provided through AIFP
with interest, using a portion of the escrow account that had been
funded with TARP funds. What remained in escrow was released to
new GM with the final debt payment by new GM (SIGTARP, 2012).

All secured creditors were paid in full. The VEBA’s claims on
GM, which amounted to $20.56 billion, were satisfied by means
of a 17.5 percent ownership in new GM, a $2.5 billion note,
$6.5 billion in preferred stock, plus warrants to buy an additional
2.5% in equity. See Congressional Oversight Panel (2009), figure
2, p. 31, for more details.

37

The VEBA can break even if it sells its remaining shares at
$36.96 per share (Muller, 2010).

38

25

The private equity firm that had acquired Chrysler from Daimler
in 2007.

See SIGTARP (2010) for more detail on GM’s and Chrysler
reduction of their respective dealer networks.

39

26

Daimler at the time still owned a minority stake in Chrysler.

27

This would commonly be referred to as a “pre-packaged bankruptcy.”

GM shed $65 billion of liabilities with the bankruptcy (Rattner,
2010a). By comparison, Ford reduced its automotive debt by $20.8
billion on its own between 2009 and 2011. It also paid its VEBA
obligations in full.

40

28

Fishman and Gouveia (2010) suggest that it would be a mistake
to treat the Chrysler and GM cases as a signal that a new order in
bankruptcy law implementation is in place. They argue that few
future debtors will be able to argue, as Chrysler and GM could,
that the national economy is tied to their fate.
29

Their secured claims had amounted to $6.9 billion.

30

In the spirit of shared sacrifice, the VEBA was awarded 50 to 60
cents on the dollar (Rattner, 2010a). Going forward, Chrysler has
to meet a schedule of payments through 2023 to fund the balance
of the claims.
31

See Congressional Oversight Panel (2009), figure 1, p. 27, on
who received what in the Chrysler restructuring.
32

Exactly how large of a loss might be attributed to the Chrysler
assistance, however, depends on what accounting method is used.
This $1.3 billion figure does not fully include a number of other

33

50

Unlike in Chrysler’s case, new GM assumed future product liability claims involving its older vehicles. Chrysler’s bankruptcy court
papers kept it immune from punitive damages involving older
vehicles (see Spector, 2012).
41

42

See Klier and Rubenstein (2011).

43
Montgomery returned to the University of Maryland in August 2010,
and 12 months later, Jay Williams, former mayor of Youngstown,
Ohio, was named to the position. The function was transferred to
the Department of Labor and renamed the Office of Recovery for
Auto Communities and Workers.

Both GM and Chrysler withdrew their applications for loans
under the Department of Energy’s Advanced Technology Vehicle
Manufacturing Program after emerging from bankruptcy. GM had
applied for $14.4 billion and withdrew its application in January
2011; Chrysler withdrew its application for $3.5 billion in February
2012 (Snavely, 2012).

44

2Q/2012, Economic Perspectives

45

During the first half of 2009, light vehicle sales in every month
had reached less than 10 million units on a seasonally adjusted annualized basis. Li, Linn, and Spiller (2011) suggest that “cash for
clunkers” had no positive effect on vehicle sales beyond 2009 and
that about 45 percent of the stimulus went to consumers who
would have purchased a new vehicle anyway.

54

46
Specifically, the net full-year profit for 2011 was $183 million
at Chrysler, $7.6 billion at GM, and $20.2 billion at Ford.

55

Rattner (2010a) reflected in his account of the restructuring that a
bit more “shared sacrifice” might have been possible. Specifically,
he wondered whether the recovery share of Chrysler’s secured
creditors should have been lower, the compensation of old GM’s
bondholders should have been wiped out, and active workers’ wages
as well as the generous pensions plans should have been cut (Rattner,
2010a). On the other hand, Senator Bob Corker, who was instrumental
in the negotiations to broker a deal in the Senate during December
2008, suggested in 2010 that the auto task force deserves credit for
going further than his suggested requirements by implementing
further reductions in debt from the automakers as well as convincing
the UAW to accept more of its retiree health care obligations from
GM in equity (Crain Communications Inc., Automotive News, 2010).

56
Between 2007 and 2011, GM’s North American production capacity
declined by 31 percent, Chrysler’s by 22 percent, and Ford’s by 8
percent. These reductions were not spread evenly across the three
NAFTA countries. The Detroit Three’s capacity fell by 19 percent
and 30 percent in Canada and the U.S., respectively, but rose by
25 percent in Mexico (authors’ calculations based on data from
Ward’s Auto Group, Auto Infobank, online database).

47

48
Often the Chevy Volt, GM’s plug-in hybrid electric vehicle, becomes
a focal point of this debate. That car was unveiled during the celebration marking GM’s 100th anniversary on September 16, 2008,
to demonstrate the company’s commitment to leadership in new
technology (Vlasic, 2011). The auto task force provided a critical
view of the vehicle’s prospects in its March 2009 evaluation of
GM’s viability plan: “While the [Chevy] Volt holds promise, it is
currently projected to be much more expensive than its gasolinefueled peers and will likely need substantial reductions in manufacturing cost in order to become commercially viable (White
House, 2009a).

Another group, the Office of the Special Inspector General of the
Troubled Asset Relief Program (SIGTARP), was also established
by Congress in 2008. Its purpose was to prevent fraud, waste, and
abuse of the $700 billion TARP program. It is a law enforcement
agency and submits quarterly reports to Congress.
49

The committee issued its final report on TARP on March 16, 2011.

50

[G]overnment intervention in the auto sector has been noteworthy
for the major restructuring that was required as a condition for receiving government financing” (Congressional Oversight Panel, 2011b,
p. 8). As a result of government intervention, “GM and Chrysler
are both more viable firms than they were in December 2008”
(Congressional Oversight Panel, 2011b, p. 7). GM in particular has
been judged to be “on a credible path to recovery” (Congressional
Oversight Panel, 2011b, p. 7).
51

“Over the longer term, it is highly likely that the assets of these
firms—particularly those related to the production of the more successful truck and minivan models—would have been brought back
into production by competing firms such as Ford or the international
auto manufacturers that build vehicles in the United States”
(Congressional Oversight Panel, 2011b, pp. 7–8).
52

“Although the TARP seemed originally to target only those companies whose financial operations made them a potential risk to
systemic stability, the use of the TARP to support the automotive
industry suggests that a company may be considered ‘systemically
significant’ merely because it employs a certain number of workers” (Congressional Oversight Panel, 2011a, p. 107).

53

Federal Reserve Bank of Chicago

The panel concluded that “[t]o the extent that success is defined
as a return of taxpayer money, it remains somewhat unlikely that
all TARP funds invested will be returned” (Congressional Oversight
Panel, 2011a, p. 106). In March 2012, the Congressional Budget
Office (2012) estimated the loss from the intervention in the auto
industry at $19 billion.
Volkswagen first entered Mexico as a producer during the mid1960s. (Nissan entered the same year.)

Similar reductions in auto industry capacity were not made in
either Europe or Asia.

57

Here, auto alley is defined as the following states: Wisconsin,
Illinois, Michigan, Indiana, Ohio, Kentucky, Tennessee, Mississippi,
Alabama, Georgia, and South Carolina.

58

The count for 2011 includes Tennessee, even though the old
Saturn plant located there is not scheduled to reopen until 2012.

59

However the company’s market share was up noticeably from
14.7 percent in 2008.

60

For example, in 2011 the Chevrolet Cruze, GM’s newly introduced
compact car, was ranked sixth among the bestselling cars in the U.S.
and second among compact cars, just behind the Toyota Corolla.

61

In 2003, for example, according to Sean McAlinden of the Center
for Automotive Research (CAR), the cost of labor at Detroit Three
assembly plants averaged $2,530 per vehicle, compared with $1,260
at foreign-owned assembly plants in the United States. Higher labor
costs per vehicle came in part from a wage rate of $46 per hour at
the Detroit Three plants, compared with $28 per hour at the international plants. The gap also resulted from lower productivity at
the Detroit Three plants: It took 55 hours to assemble a vehicle at
the Detroit Three plants, compared with 45 hours at the international plants (McAlinden 2008).

62

The Detroit carmakers and the union had created the jobs bank as
an “employee-development bank” in the 1984 labor contract. “Back
then, it was designed as a temporary repository for laid-off workers
so they could be retrained for new positions in higher-tech factories.
For the UAW, the jobs bank was an ironclad means to provide security for its members when the industry hit a rough patch. What it
evolved into, though, was a holding bin for excess workers.” The
workers kept getting paid while in the jobs bank; some of them
remained there for years (Vlasic, 2011, pp. 108–109).

63

The 2007 average hourly wage compared with $17.35 for all
U.S. manufacturing. The gap between the UAW rates and the overall average wage rates had grown especially large after 2000
(McAlinden, 2008).
64

That comparison does not include health care costs. Once the
VEBAs were approved, the responsibility for health care costs for
retired auto workers lay with those organizations and was off the
books of the Detroit Three. Note, however, that the VEBAs have
not yet been fully funded by GM and Chrysler (see Schwartz, 2011a).

65

51

66
Ford also demonstrated that by transferring the retiree health
benefit obligations to the VEBA, its hourly wage cost would fall to
$58. If the company could replace 20 percent of its projected work
force with new employees earning the entry-level wage, its hourly
labor costs would come down to $53 (see Cooney et al., 2009).

A key factor in the variation in labor costs among the Detroit
Three is variation in the shares of second-tier wage earners each
of them has hired to date. Second-tier wages are about half of what
“continuing workers” earn.
67

Ford regained its investment grade rating from Fitch Ratings on
April 24, 2012.

68

Between 2009 and 2011, both companies also grew their U.S. production faster than the industry as a whole (up 51 percent). Chrysler’s
U.S. output rose by 142 percent, and GM’s rose by 59 percent.

69

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“Establishing a White House Council on Automotive
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Rattner, Steven, 2010a, Overhaul—An Insider’s
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Rescue of the Auto Industry, New York: Houghton
Mifflin Harcourt.
__________, 2010b, “Reflections on the auto restructurings,” speech at the Federal Reserve Bank of Chicago
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Forces Shaping the Auto Industry, Detroit, May 10–11,
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events/2010/automotive_perfect_storm/rattner.pdf.
Schwartz, Arthur R., 2011a, “A look back and a
look forward,” presentation at the CAR (Center for
Automotive Research) Breakfast Briefing, Detroit 3–
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Community College, Livonia, MI, November 29,
available at www.cargroup.org/assets/files/labor.pdf.
__________, 2011b, “Setting the stage: 2005–2009
UAW–Detroit Three talks,” presentation at the 2011
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Briefing Seminars, Bargaining for a Competitive
Future: The 2011 Negotiations between the UAW
and the Detroit Three, Grand Traverse Resort & Spa,
Traverse City, MI, August 3, available at http://mbs.
cargroup.org/2011/Dziczek&Schwartz.pdf.

53

Scott, Robert E., 2008, “When giants fall: Shutdown
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White House, 2010, “Annual report of the White
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Snavely, Brent, 2012, “Chrysler withdraws application for Department of Energy loan,” Detroit Free
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54

__________, 2009a, “GM February 17 plan: Viability
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GM_Viability_Assessment.pdf.
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gov/news/releases/2008/12/20081219-6.html.
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2Q/2012, Economic Perspectives

No-arbitrage restrictions and the U.S. Treasury market
Andrea Ajello, Luca Benzoni, and Olena Chyruk

Introduction and summary
The secondary U.S. Treasury market is among the largest,
most liquid, and most important financial markets worldwide. Daily trading volume in 2011 averaged $567.8
billion, more than tenfold the volume at the New York
Stock Exchange (NYSE).1 The market is open around
the clock, with trading involving both U.S. and international participants. Competition among dealers and
brokers typically results in low bid–ask spreads, low
brokerage fees, and fast order execution (for example,
Fleming, 1997). Such features make the market very
liquid across a wide spectrum of maturities.
Arbitrage is the practice of taking advantage of a
price differential between securities that pay out similar
cash flows (we provide a more rigorous definition at the
beginning of the next section). This concept has immediate application in the U.S. Treasury market. For
instance, consider two alternative investment strategies.
The first entails purchasing a ten-year Treasury note.
The second involves an investment of the same amount
in a three-month Treasury bill that we repeatedly roll
over at maturity into a newly issued three-month bill.
For markets to clear, and absent market frictions, the
price of the ten-year note needs to reflect investors’
expectations about the future path of the three-month
Treasury rate during the next ten years. These expectations involve an adjustment to compensate risk-averse
investors for bearing the risk that the price of the tenyear note will fluctuate during the holding period. If
Treasury yields were to violate this condition, in a wellfunctioning capital market arbitrage trading would move
funds across assets until prices adjust to balance out
profit opportunities. By the same argument, yields on
Treasury securities with various maturities will satisfy
similar cross-sectional restrictions.
The Federal Reserve exploits the linkage across
the term structure of bond yields to influence the
availability and cost of money and credit in the economy.

Federal Reserve Bank of Chicago

For instance, the Federal Open Market Committee
(FOMC) uses open market operations to achieve a
desired target rate in the federal funds market, where
depository institutions lend balances at the Federal
Reserve to other depository institutions overnight.2
Changes in the federal funds rate trigger a chain
of events that affect other short-term interest rates,
Andrea Ajello is an economist in the Division of Monetary
Affairs at the Board of Governors of the Federal Reserve
System. Luca Benzoni is a senior financial economist and
Olena Chyruk is a senior research analyst in the Economic
Research Department at the Federal Reserve Bank of Chicago.
The authors are grateful to Gene Amromin, Gadi Barlevy,
Marco Bassetto, Jarda Borovička, Charlie Evans, Robert
Goldstein, Alejandro Justiniano, Spencer Krane, David Marshall,
Richard Porter, Robert Steigerwald, an anonymous referee,
and seminar participants at the Federal Reserve Bank of
Chicago for helpful comments and suggestions.
© 2012 Federal Reserve Bank of Chicago
Economic Perspectives is published by the Economic Research
Department of the Federal Reserve Bank of Chicago. The views
expressed are the authors’ and do not necessarily reflect the views
of the Federal Reserve Bank of Chicago or the Federal Reserve
System.
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President and Director of Research; Spencer Krane, Senior Vice
President and Economic Advisor; David Marshall, Senior Vice
President, financial markets group; Daniel Aaronson, Vice President,
microeconomic policy research; Jonas D. M. Fisher, Vice President,
macroeconomic policy research; Richard Heckinger, Vice President,
markets team; Anna L. Paulson, Vice President, finance team;
William A. Testa, Vice President, regional programs; Richard D.
Porter, Vice President and Economics Editor; Helen Koshy and
Han Y. Choi, Editors; Rita Molloy and Julia Baker, Production
Editors; Sheila A. Mangler, Editorial Assistant.
Economic Perspectives articles may be reproduced in whole or in
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ISSN 0164-0682

55

foreign exchange rates, and the amount of money and
credit. Most people, however, care especially about the
cost of long-term credit—many firms rely on long-term
debt to fund capital investment, and households take on
long-term loans to buy their homes and cars. These
observations underscore the importance of term structure
models that help us gauge the effect of monetary policy
actions (which typically impact the short end of the term
structure) on long-term yields and, ultimately, a range
of economic variables, including employment, output,
and the prices of goods and services.
In this article, we discuss the pricing of U.S.
Treasury securities via no-arbitrage arguments. We
initially define what an arbitrage is and provide an
intuitive one-period example that shows how to construct an arbitrage investment strategy in a frictionless
capital market. We argue that absent transaction costs,
information asymmetries, and other market imperfections, investors will trade away arbitrage opportunities.
This will discipline the movement in prices of assets
that are exposed to the same source of risk. We then
formalize this intuition in the classical no-arbitrage
term structure model of Vasicek (1977). We show that
no-arbitrage arguments restrict the amount of return
that investors demand in compensation for bearing a
unit of risk (the so-called market price of risk) to be
identical across the cross section of bonds. Exploiting
this condition, Vasicek obtains a bond pricing formula
that expresses the price of bonds of various maturities
as a function of the spot interest rate, the market price
of risk, and other model parameters.
This discussion also highlights the limitations of
the Vasicek model. First, Vasicek assumes the market
price of risk to be exogenous—his approach is silent
about the economic forces that determine the amount
of compensation investors require to bear risk. To clarify
this link, we recast his model in a general equilibrium
setting. This analysis shows that the market price of
risk depends in fact on economic fundamentals such
as the investors’ attitude toward risk and the volatility
of the growth rate in aggregate consumption.
Second, in the Vasicek model a single variable,
the spot interest rate, explains the fluctuations in the
entire cross section of Treasury yields. One implication
of this assumption is that bond yields and their changes
are perfectly correlated. Correlations in pairs of yields
with different maturities are positive and high in the
data; however, they decrease considerably as the time
to maturity of bonds becomes further apart. This feature
suggests that additional factors might drive the U.S.
Treasury yield curve and motivates a vast literature that
extends the class of no-arbitrage term structure models
to include multiple factors. We present an overview

56

of this class of models, with an emphasis on the specifications that, similar to Vasicek’s model, allow for
tractable bond pricing formulas (the so-called affine
dynamic term structure models).
Third, the predictions of no-arbitrage models hinge
on the critical assumption that markets are “perfect.”
In order to take advantage of arbitrage opportunities,
investors require access to capital. To trade away price
misalignments, they need to be able to exchange securities at minimal cost based on information that is
available to, and readily interpretable by, all investors.
Clearly, no market satisfies all these conditions, and
frictions typically become more severe during times
of market stress. In extreme cases, markets could become segmented and arbitrage opportunities remain
unexploited because of balance-sheet capacity limitations or because of higher-than-normal uncertainty and
risk aversion. These conditions could reduce the effectiveness of no-arbitrage pricing arguments, possibly to
a point where prices deviate from fundamental values.
Most of the time, frictions in the U.S. Treasury
market are small. For instance, bid–ask spreads and
other transaction costs are usually very low, and investors
can trade securities with ease (for example, Fleming,
1997). Financial and economic crises typically do not
impair these conditions. In fact, a flight to quality and/
or liquidity can increase the demand for U.S. government debt, especially the most recently issued shortmaturity nominal Treasury securities. This happened,
in particular, during the recent financial crisis, when
investors displayed a desire to hold only the safest and
most liquid assets (for example, Gorton and Metrick,
2011; and Krishnamurthy, 2010). Nonetheless, government debt markets can exhibit some degree of segmentation because of the preferences by some investor
clienteles (for example, pension funds, insurance companies, and other institutional investors) to hold securities that have specific maturities. So-called preferred
habitat theories argue that these preferences could limit
the substitutability of short- and long-term Treasury
securities, distorting their relative pricing; capital constraints and risk aversion might prevent arbitrageurs
from eliminating such profit opportunities. In the last
part of the article, we expand on this discussion, focusing on the literature that studies limits to arbitrage in
the government debt market.
Fourth, the dynamic term structure models that
we review here typically rely on latent factors (or linear combinations of yields) to explain the variation in
Treasury yields. Thus, this framework does not explain
how bond yields respond to macroeconomic shocks,
as these factors are void of immediate economic interpretation. Similarly, these models are silent about

2Q/2012, Economic Perspectives

the effect of monetary policy on economic variables,
such as unemployment, gross domestic product (GDP)
growth, and consumer prices. In response to these
shortcomings, several recent studies explore the linkage
between U.S. Treasury securities and the macroeconomy
in no-arbitrage term structure models. We touch upon
these issues at the very end, and postpone further discussion to the future.

Substituting the expression for the rate of return
Δ P ( t ) and rearranging the terms, we simplify

No-arbitrage pricing in a one-period example

An appropriate choice of W2 and W1 eliminates uncertainty in the strategy’s return. In particular, if the investor sets W1 = W Σ2 /(Σ1– Σ2) and W2 = W Σ1/(Σ1– Σ2),
the second term in equation 3 vanishes and the rate
of return on invested wealth over the interval from
t to t + 1 simplifies to

An arbitrage is an investment strategy that entails
a nonpositive initial cost to generate a nonnegative cash
flow that is positive with positive probability at some
future date. Arbitrage opportunities should not exist
in a frictionless market. Without transaction costs, information asymmetries, and other market imperfections,
investors would immediately take advantage of any
arbitrage opportunity. By doing so, they will close any
misalignment in prices: Excess demand will push up
the cost of securities that are relatively undervalued, and
excess supply will lower the price of overvalued assets.
Thus, no-arbitrage trading guarantees that securities
are priced to reflect their future cash flow stream.
As a simple illustration of this concept, consider
the case of an investor who trades in two assets at prices
P1(t) and P2(t) on date t. The two securities do not pay
dividends and are exposed to the same source of risk,
so that their returns from t to t + 1 are described by
the model
1)

∆Pi (t ) Pi (t + 1) − Pi (t )
≡
= µi + Σi ε ( t + 1) , i = 1, 2.
Pi (t )
Pi (t )

Here, µi denotes the constant expected rate of return
on security i during the unit interval, while the stochastic term (Σiε) is a mean zero innovation in the rate
of return, with constant variance Σi2. Being subject to
the same shock ɛ, the returns on the two assets by construction are perfectly correlated. Thus, the investor
can exploit the co-movement in the two securities to
eliminate risk from her portfolio. Suppose that she sells
short W1 worth of the first security’s shares and places
a wealth amount W2 in the second security. At time t,
the portfolio is worth W ≡ W2 – W1 in wealth. During
the interval from t to t + 1, the change in wealth is
determined by the rate of return on the two securities
over that interval,
2) ∆W (t ) ≡ W (t + 1) − W (t ) = W2 (t )
− W1 (t )

∆P1 (t )
.
P1 (t )

Federal Reserve Bank of Chicago

∆P2 (t )
P2 (t )

i

Pi ( t )

equation 2 to

3) ∆W (t ) = (W2 (t ) µ 2 − W1 (t ) µ1 )
+ (W2 (t ) Σ 2 − W1 (t ) Σ1 ) ε(t + 1).

4)

∆W (t ) µ 2Σ1 − µ1Σ 2
=
.
W (t )
Σ1 − Σ 2

At this point, we want to rule out arbitrage opportunities.
To this end, we need to have the return on wealth in
equation 4 equal the risk-free rate, r, which we assume
to be constant in this example. Thus, we have the following condition:
5)

µ 2Σ1 − µ1Σ 2
= r.
Σ1 − Σ 2

Rearranging terms in equation 5, we obtain the market
clearing condition that links the expected return on the
two securities, in excess of the risk-free rate, per unit
of return standard deviation:
6)

µ 2 − r µ1 − r
=
.
Σ2
Σ1

We denote the common value for this ratio with λ:
7) λ =

µi − r
, i = 1, 2.
Σi

The ratio λ measures the market price of risk; that is,
it quantifies the amount of return that investors demand
in compensation for a unit of risk that they bear. To
rule out arbitrage opportunities, we must have the
coefficients µi and Σi that determine the returns on
securities i = 1 and 2 in equation 1 satisfy the condition in equation 7. Intuitively, this restriction ties the
price of the first security to that of the second security.

57

In the next section, we explain how these prices are
tied together.

where we have suppressed time t subscripts and
defined

The Vasicek model
Here, we follow the Vasicek (1977) framework
closely. We let the length of the time interval shrink to
zero and recast the example from the previous section in
continuous time. This simplifies the exposition considerably and clearly conveys the intuition for the results.
Assume that the spot risk-free rate, r, in a frictionless market follows a mean-reverting diffusion process
8) dr = κ( θ − r )dt + Σ dZ ,
where Z is a standard Brownian motion. Equation 8
is a continuous-time analogue to the return process in
equation 1. The left-hand side has the instantaneous
change in the spot interest rate, dr = r(t + dt) – r(t).
Similar to equation 1, the right-hand side of equation 8
is the sum of the expected change in r, conditional on
the realization of the time t spot rate, as well as a random shock. In particular, the term κ(θ – r) describes
the conditionally deterministic component of the
spot rate evolution, with the coefficient κ > 0 controlling the speed of mean reversion of the process r
toward its long-run mean θ. The Brownian shock
dZ = Z(t + dt) – Z(t) has Gaussian distribution with
mean zero and variance dt, N(0, dt). It takes place of
the mean zero shock ɛ over the discrete time interval
from t to t + 1 in equation 1, where Var(ɛ) = Δt = 1.
The coefficient Σ2 represents the constant instantaneous variance of the stochastic fluctuations of the
spot rate. Equation 8 satisfies the affine restrictions of
Duffie and Kan (1996); that is, the drift term κ(θ – r)
is a linear-plus-constant function of the spot rate r, and
the quadratic variation of the process is the constant
Σ2. These restrictions help us to obtain a closed-form
bond pricing formula, which we derive next.
In the Vasicek model, the spot rate r summarizes
the uncertainty in the economy. In particular, the time
t price of a zero-coupon bond with maturity date T is
determined by the assessment, at time t, of the evolution of the spot rate rs  , with t ≤ s ≤ T. Itô’s formula
gives then the dynamics for the bond price Pt = P(rt  , τ),
where τ = T – t:
 ∂P ∂P
1 ∂2P 2 
9) dP = 
+
κ(θ − r ) +
Σ  dt
2 ∂r 2 
 ∂t ∂r
+

10) µ( r, τ) ≡
σ( r , τ ) ≡

1  ∂P ∂P
1 ∂2P 2 
κ(θ − r ) +
+
Σ ,

P  ∂t ∂r
2 ∂r 2 
1 ∂P
Σ.
P ∂r

Following steps similar to those of the previous
example, we consider an investor who sells short W1
worth of the bond with maturity T1 and who places
wealth W2 in the bond with maturity T2 . This strategy
is worth W ≡ W2 – W1 in wealth at time t, which
evolves according to
11) dW = W2

dP( r, τ2 )
dP( r, τ1 )
− W1
P( r, τ2 )
P( r, τ1 )

= µW dt + σW dZ ,
where µW = W2  µ(r, τ2) – W1  µ(r, τ1) and σW = W2  σ (r, τ2)
– W1  σ (r, τ1). The investor can choose W1 and W2 to
dynamically hedge her portfolio. In particular, setting

12) W1 =
W2 =

σ( r , τ 2 ) W
,
σ( r, τ1 ) − σ( r, τ2 )
σ( r, τ1 )W
σ( r, τ1 ) − σ( r, τ2 )

eliminates risk from her investment; that is, σW = 0
and the second term in the right-hand side of equation 11
vanishes. Thus, the position is insulated from the stochastic shock dZ, and the instantaneous rate of return on
invested wealth simplifies to
13)

dW σ( r, τ1 ) µ( r, τ2 ) − σ( r, τ2 ) µ( r, τ1 )
=
dt.
W
σ( r, τ1 ) − σ( r, τ2 )

To avoid arbitrage opportunities, we need to have
the growth rate in wealth to equal the risk-free rate,
14)

σ( r, τ1 ) µ( r, τ2 ) − σ( r, τ2 ) µ( r, τ1 )
= r.
σ( r, τ1 ) − σ( r, τ2 )

∂P
Σ dZ
∂r

= P µ( r, τ) dt + P σ( r, τ) dZ ,

58

2Q/2012, Economic Perspectives

Rearranging terms, we obtain a condition similar to
equation 6:
15)

µ( r, τ1 ) − r µ( r, τ2 ) − r
=
.
σ( r, τ1 )
σ( r , τ 2 )

That is, the market price of risk λ is a function of the
sole state variable of the economy, r, and is independent of the bond time to maturity τ,
16) λ( r ) =

µ( r , τ) − r
, ∀τ ≥ 0.
σ( r , τ )

To obtain a closed-form bond pricing formula,
Vasicek assumes the market price of risk is constant;
that is,
17) λ( r ) = λ 0 .
Substituting the expression for µ(r, τ) and σ(r, τ)
from equation 10 in equation 16 yields a partial differential equation for the bond price P:
∂P
∂P 1 2 ∂ 2 P
18)
+ ( κ ( θ − r ) − Σλ 0 )
+ Σ
∂t
∂r 2 ∂r 2

The determinants of the market price of risk
The Vasicek (1977) bond pricing formula hinges
on the principle that absent arbitrage opportunities,
the return on a locally risk-free portfolio of bonds must
equal the risk-free rate. This approach is silent about
the sources of the market price of risk λ, and it takes
the spot risk-free rate dynamics in equation 8 as given.
Here, we show that the Vasicek bond pricing formula
is consistent with the solution of the intertemporal consumption decision problem of a representative investor.
While we arrive at the same pricing formula, this general equilibrium approach restricts the properties of the
market price of risk and the instantaneous risk-free
rate r, which become functions of the investor’s attitude
toward risk and the parameters that govern the aggregate dividend process. These results are well known in
the literature (for example, Cox, Ingersoll, and Ross,
1985). The discussion in this section follows Goldstein
and Zapatero (1996) and Cochrane (2005) closely.
Consider a security with ex-dividend price p
that represents a claim to the aggregate output of the
economy, which is paid out to the holder of the security in the form of a dividend D. We assume that the
security generates an ex-dividend return

21)

dpt
= µ t dt + σt dZ t ,
pt

with terminal condition P(r, τ = 0) =1. The solution to
this equation is exponentially affine in the spot rate r;
that is, there are functions A( τ) and B( τ) of time to
maturity τ such that

where μt is the ex-dividend expected rate of return
on security p, σt2  is the instantaneous variance of the
stochastic fluctuation in security p’s return, and Z is
a standard Brownian motion. The quantities μt and σt
are endogenous to the model and will be determined
in equilibrium. In contrast, the aggregate dividend is
exogenously given by

19) P( r, τ) = exp{ A( τ) + B( τ) r }.

22)

− rP = 0 , T ≥ t ,

Thus, we obtain a closed-form expression for the
term structure of interest rates. In particular, the yield
y on the bond with maturity date T is affine in the
spot rate r:
20) y ( r, τ) = A( τ) + B ( τ) r ,
where A( τ) = − A( τ) / τ and B(τ) = − B(τ) / τ.

dDt
= αt dt + ξ dZ t ,
Dt
d αt = κ( α − αt )dt + ν dZ t .

Consider now an infinitely lived representative
investor who trades in the security p and maximizes
her lifetime utility of consumption,
∞
23) U ({cs , s ≥ t}) = Et  ∫ e − δ ( s −t )u( cs )ds  .
 t


Cochrane (2005) shows that the first-order condition
for this problem generates the basic pricing equation,

Federal Reserve Bank of Chicago

59

∞

24) pt u′( ct ) = Et ∫ e − δs u′( ct + s ) Dt + s ds ,

so that equation 30 becomes:

which equates the marginal cost of acquiring the security
today at price pt to the marginal benefit generated by
its future dividend stream. Defining the discount factor
as Λ t ≡ e −δt u′( ct ) , we can rewrite equation 24 as:

 dp  D
 dc dp 
= γEt  t t  .
32) Et  t  + t dt − rdt
t
p
p
t
 t 
 ct pt 

0

25)

∞

pt Λ t = Et ∫ Λ t + s Dt + s ds .
0

Consider now a strategy that buys security p at
time t and sells it at time t + Δ . Equation 25 then
yields
26)

∆

pt Λ t = Et ∫ Λ t + s Dt + s ds + Et [ Λ t +∆ pt +∆ ].
0

For small Δ → 0, this can be approximated by:
27) 0 = Λ t Dt dt + Et [d ( Λ t pt )].
Itô’s lemma yields d ( Λ t pt ) = pt d Λ t + Λ t dpt + dpt d Λ t ,
so that equation 27 becomes:
28) 0 =

 d Λ dp d Λ t dpt 
Dt
dt + Et  t + t +
.
Λ t pt 
pt
pt
 Λt

Equation 32 says that the expected excess cum-dividend
return on security p is proportional to the risk aversion
coefficient γ. Thus, more-risk-averse investors demand
a higher risk premium to hold p. Moreover, the risk
premium on p depends on the correlation between
aggregate consumption growth and the return on p,
Et  dcctt dpptt  . Thus, an investor will require a positive
risk premium to hold a security that generates a high
return when consumption growth is high, that is, when
Et  dcctt dpptt  > 0. This is intuitive, as such security
generates, in expectation, a low payoff when consumption is low. This property makes the security less valuable to the investor, who is risk averse and wishes to
smooth her consumption profile.
Note that in equilibrium, aggregate consumption
equals the aggregate dividend, and thus it has dynamics identical to those given in equation 22. Substituting the endowment growth rate in equation 29 yields
an expression for the equilibrium risk-free rate:
33)

1
rt = δ + γαt − γ ( γ + 1)ξ2 .
2

Using equation 25 to price the (instantaneous)
risk-free zero-coupon bond, we obtain an expression
for the spot risk-free rate,

Itô’s lemma gives us the spot rate dynamics

 d Λt 
29) rdt
= − Et 
.
t
 Λt 

where we have defined the coefficients θ ≡ γα + δ
− 12 γ ( γ + 1)ξ2 and Σ ≡ γν. Equation 34 is identical to the
spot rate dynamics in equation 8, as in the Vasicek
(1977) model. However, via equilibrium arguments
we have established a linkage between the coefficients κ, θ, and Σ and economic fundamentals (that
is, the coefficients κ, ᾱ, δ, ξ, and ν that govern the
endowment dynamics in equation 22 and the risk
aversion parameter γ).
To obtain a formula for the price P of a zero-coupon
bond with maturity date T, it is useful to compute the
spot rate dynamics under the risk-adjusted probability
measure Q (Harrison and Kreps, 1979). With the help
of equation 32, we obtain:

Then, rearranging equation 28, we obtain an equilibrium condition for the expected rate of return on security p, μt:
 dp  D
 d Λ dp 
= − Et  t t  .
30) Et  t  + t dt − rdt
t
p
p
t 
t
 Λ t pt 



µt dt

Assume now that the
investor has the power
1− γ
utility function u( ct ) = c1t− γ with the coefficient of
risk aversion γ. By the definition of Λt  , the stochastic
discount factor dynamics are
2

31)

60

 dc 
d Λt
dc 1
= −δdt − γ t + γ (1 + γ ) t  ,
Λt
ct 2
 ct 

34) drt = κ( θ − rt )dt + Σ dZ t ,

35) drt = κ( θQ − rt )dt + Σ dZ tQ ,
where we have defined θQ ≡ θ − γξκΣ and dZ tQ ≡ dZ t
+ γ ξdt. Then, we have
2Q/2012, Economic Perspectives

figure 1

U.S. Treasury yields
label
percent per
year
18
16
14
12
10
8
6
4
2
0
1962

’65

’68

’71

’74

’77

’80

’83

1Q
4Q

’86

’89
12Q
20Q

’92

’95

’98

2001

’04

’07

’10

40Q
80Q

Notes: The plot depicts the time series of monthly U.S. Treasury yields with one-, four-, 12-, 20-, 40-, and 80-quarter (Q) maturities. The onequarter yield is from the Fama CRSP Treasury bill files. The yields with a maturity greater than one quarter are zero-coupon yields interpolated
from daily constant-maturity par yields computed by the U.S. Department of the Treasury and distributed by the Board of Governors of the
Federal Reserve System in the H.15 statistical release. The sample period is January 1962–December 2010.
Sources: Authors’ calculations based on data from the University of Chicago Booth School of Business, Center for Research in Security Prices
(CRSP), Fama CRSP Treasury bill files; and Board of Governors of the Federal Reserve System, H.15 statistical release.

 −
36) P(t, T ) = EtQ  e ∫t


T

ru du


,


where the conditional expectation EtQ [⋅] is computed
under the risk-adjusted measure Q.
The spot rate in equation 35 is a continuous Markov
process. Thus, the evolution of ru over the interval
(t, T ), given the history up to time t, depends only on
rt. Equation 36 then implies that the bond price is a
function of rt , P(t, rt , T ), and by Itô’s lemma we obtain:
1 ∂ 2 P 2 
∂P ∂P
∂P
κ(θ − r ) +
Σ  dt +
ΣdZ .
+
2
 ∂t

2 ∂r
∂r
∂r





37) dP = 

Moreover, we can apply equation 32 to determine the
expected rate of return on the zero-coupon bond, in
excess of the spot rate:
 dP 
 dc dP 
.
38) Et   − rdt = γEt 
P
 c P 

Federal Reserve Bank of Chicago

Combining equations 37 and 38, we derive the fundamental differential equation for bonds:
39)

 1 ∂ 2 P 2 ∂P
∂P 
 κ ( θ − r ) − Σ γξ  +
Σ +
− rP = 0 ,
 2 ∂r 2
∂r 
∂t
≡λ 0 


where ξ is the diffusion coefficient of the aggregate
endowment process given in equation 22. Equation 39
is identical to the partial differential equation of the
Vasicek model (equation 18) with the restriction
λ0 = γξ. Consequently, assumptions about investors’
preferences and their endowment pin down the specification of the market price of risk. Specifically, λ0 is
higher when the investor is more risk averse, γ↑, and
when consumption growth is more volatile, ξ↑.
Multifactor dynamic term structure models
In the Vasicek (1977) model, a single factor, the
spot rate r, explains the fluctuations in the entire term
structure of interest rates. One implication of this assumption is that bond yields and their changes are perfectly
correlated. A cursory glance at figure 1 shows that there
are co-movements in yields with different maturities,

61

			

Table 1

Pairwise correlations in U.S. Treasury yield series

	

corr ( y τi	 ,yτ j )
	
	

corr (∆y τi ,∆yτ j )

1Q	 4Q	12Q	20Q	40Q	 80Q		 1Q	4Q	12Q	 20Q	40Q	80Q

A. Monthly series
	
1Q	
	
4Q	
12Q	
	
20Q	
	
40Q	
	
80Q	
	

1.00							
1.00
0.99	
1.00						
0.71	
1.00
0.95	0.98	1.00					
0.63	0.92	1.00
0.93	0.96	0.99	 1.00				
0.56	0.86	0.97	 1.00
0.88	0.92	0.97	 0.99	 1.00			
0.47	0.73	0.87	 0.93	 1.00
0.82	0.86	0.93	0.96	0.98	1.00		
0.36	
0.58	0.71	 0.79	0.88	1.00

B. Quarterly series
	
1Q	
	
4Q	
12Q	
	
20Q	
	
40Q	
	
80Q	
	

1.00							
1.00
0.99	
1.00						
0.90	
1.00
0.96	0.98	1.00					
0.78	0.94	1.00
0.93	0.96	0.99	 1.00				
0.69	0.88	0.98	 1.00
0.88	0.92	0.97	 0.99	 1.00			
0.58	0.77	0.91	 0.96	 1.00
0.82	0.86	0.93	0.96	0.98	1.00		
0.43	
0.60	0.75	 0.82	0.90	1.00

Notes: Both panels show the pairwise correlations between U.S. Treasury yields with various maturities. Panel A reports the correlations computed
on monthly yields (left) and changes in monthly yields (right). Panel B shows the results for quarterly yields (left) and changes in quarterly yields
(right). The data series consist of yields with one-, four-, 12-, 20-, 40-, and 80-quarter (Q) maturities. The one-quarter yield is from the Fama CRSP
Treasury bill files. The yields with a maturity greater than one quarter are zero-coupon yields interpolated from daily constant-maturity par yields
computed by the U.S. Department of the Treasury and distributed by the Board of Governors of the Federal Reserve System in the H.15 statistical
release. The sample period is January 1962–December 2010.
Sources: Authors’ calculations based on data from the University of Chicago Booth School of Business, Center for Research in Security Prices
(CRSP), Fama CRSP Treasury bill files; and Board of Governors of the Federal Reserve System, H.15 statistical release.

from one quarter to 20 years.
While the correlations in both the
Principal component analysis
monthly (panel A) and quarterly
	
Percentage of 		
Total percentage of
(panel B) series are positive, they
	
variance explained		
variance explained
decrease considerably as the time
	
monthly	 quarterly	
monthly	quarterly
to maturity in the pairs of bonds
becomes
further apart. This feature
PC1	 95.19	 95.34	
95.19	95.34
suggests that additional factors
99.44	99.51
PC2	 4.25	 4.17	
99.85	99.88
PC3	 0.41	 0.37	
might drive the term structure of
99.96	99.96
PC4	 0.11	 0.08	
U.S. Treasury yields.
99.99	99.99
PC5	 0.04	 0.03	
The evidence in table 2 lends
0.01	
100.00	100.00
PC6	 0.01	
additional support to this conclusion.
Notes: The table reports the percentage of the yields’ variation explained by the principal
It shows the percentage of the yields’
components, PC ,  j = 1, …, 6, extracted from the panel of yields with one-, four-, 12-,
20-, 40-, and 80-quarter maturities sampled at the monthly and quarterly frequencies.
variation explained by the principal
The one-quarter yield is from the Fama CRSP Treasury bill files. The yields with a maturity
components (PCs) extracted from the
greater than one quarter are zero-coupon yields interpolated from daily constant-maturity
par yields computed by the U.S. Department of the Treasury and distributed by the Board
panel of bond yields with one-, four-,
of Governors of the Federal Reserve System in the H.15 statistical release. The sample
12-, 20-, 40-, and 80-quarter maturiperiod is January 1962–December 2010.
Sources: Authors’ calculations based on data from the University of Chicago Booth School
ties. The first principal component
of Business, Center for Research in Security Prices (CRSP), Fama CRSP Treasury bill
files; and Board of Governors of the Federal Reserve System, H.15 statistical release.
has the highest explanatory power,
accounting for more than 95 percent
of the variation in monthly and
quarterly yields. The second and third components
but such correlations are far from perfect. This is
account for virtually all of the residual variation in
evident in table 1, which reports pairwise correlations
yields. This is well known in the term structure literain yields and their changes, corr ( yτi , yτ j ) and
ture; for instance, Litterman and Scheinkman (1991)
corr ( ∆yτi , ∆yτ j ), for maturity pairs τi and τj ranging
		

Table 2

j

62

2Q/2012, Economic Perspectives

resembles the shape of the yields in
figure 1.
U.S. Treasury yields’ principal components coefficients
In contrast, the coefficients of
the second PC are increasing in
0.6
yields’ maturity τ, while those of the
BτPC 1
third one are U-shaped, as shown in
0.4
figure 2. Thus, as in Litterman and
Scheinkman (1991), PC2 is a proxy
0.2
for a slope factor (positive shocks to
this factor are associated with lower
3
BτPC 2
BPC
τ
0
short-maturity yields and higher longmaturity yields), while PC3 is a proxy
−0.2
for curvature. Indeed, the correlation
between PC2 and a measure of the
term structure slope, (y80Q – y1Q ),
−0.4
exceeds 90 percent, and the correlation of PC3 with a measure of cur−0.6
vature, (y80Q – 2y12Q + y1Q ), is higher
than 83 percent.
−0.8
Taken together, these empirical
0
10
20
30
40
50
60
70
80
maturity in quarters
observations motivate a vast literature that extends the no-arbitrage
Notes: The plot depicts the coefficients B that multiply the yields to form the U.S.
Treasury yields’ first three principal components, PC ,   j = 1, 2, and 3, as a function of
term structure model class to include
the yields’ maturity τ. The authors compute the principal components using monthly
multiple factors. As in the Vasicek
yields series with one-, four-, 12-, 20-, 40-, and 80-quarter maturities. The one-quarter
yield is from the Fama CRSP Treasury bill files. The yields with a maturity greater than
(1977) model, the no-arbitrage conone quarter are zero-coupon yields interpolated from daily constant-maturity par yields
computed by the U.S. Department of the Treasury and distributed by the Board of
ditions restrict the relative pricing
Governors of the Federal Reserve System in the H.15 statistical release. The sample
of bonds with different maturities
period is January 1962–December 2010.
Sources: Authors’ calculations based on data from the University of Chicago Booth
while remaining silent about all othSchool of Business, Center for Research in Security Prices (CRSP), Fama CRSP
er conditions that characterize the
Treasury bill files; and Board of Governors of the Federal Reserve System, H.15
statistical release.
equilibrium in the economy. Consistent with the evidence that level,
slope, and curvature factors capture
show that the variation in U.S. Treasury rates is best
virtually all variation in Treasury yields, much of this
captured by three factors, interpreted as changes in
literature has focused on three-factor models.
“level,” “slope,” and “curvature” of the yield curve.
To maintain tractability, most studies rely on
Figure 2 clarifies this interpretation. The yields’
so-called affine models. In line with Duffie and Kan
PCs are an orthogonal linear transformation of the
(1996), Dai and Singleton (2000, 2003), and Piazzesi
yields’ series; they are constructed so that each com(2010), the short-term interest rate, r(t), is an affine
ponent explains the highest fraction of residual vari(that is, linear-plus-constant) function of a vector of
ance in the original series and is orthogonal to the
state variables, X(t) = {xi(t), i =1, ..., N}:
preceding PCs. Figure 2 shows the coefficients in the
N
vector Bτ that multiply the yields to form the first
40
)
r
(
t
)
=
δ
+
δi xi (t )
∑
0
three principal components, PCj  , j = 1, 2, and 3, as a
i =1
function of the yields’ maturity τ. The coefficients as= δ0 + δX′ X (t ) ,
sociated with the first PC are roughly the same across
the yields’ maturities. This suggests that PC1 is a
proxy for a level factor, that is, shocks to that factor
where the state vector X evolves according to
result in a parallel shift in yields across maturities.
Consistent with this view, the correlation between
41) dX (t ) = κ( Θ − X (t ))dt
PC1 and yτ, τ ∈{1, 4, 12, 20, 40, and 80 quarters} rang+Σ S (t )dZ (t ) .
es from 93.6 to 99.7 percent in monthly data; we find
similar values in the quarterly series. This is also evident in figure 3, which shows that the pattern in PC1
figure 2

τ

j

Federal Reserve Bank of Chicago

63

figure 3

Principal components (PC) series: Level, slope, and curvature
principallabel
components
0.25
PC1 (level)

0.20
0.15
0.10
0.05

PC3 (curvature)

0.00
−0.05
PC2 (slope)

−0.10
−0.15
1962

’65

’68

’71

’74

’77

’80

’83

’86

’89

’92

’95

’98

2001

’04

’07

’10

Notes: The plot depicts time series of the first three principal components (level, slope, and curvature) computed using monthly U.S. Treasury
yields series. The data consist of yields with one-, four-, 12-, 20-, 40-, and 80-quarter maturities. The one-quarter yield is from the Fama
CRSP Treasury bill files. The yields with a maturity greater than one quarter are zero-coupon yields interpolated from daily constant-maturity
par yields computed by the U.S. Department of the Treasury and distributed by the Board of Governors of the Federal Reserve System
in the H.15 statistical release. The sample period is January 1962–December 2010.
Sources: Authors’ calculations based on data from the University of Chicago Booth School of Business, Center for Research in Security
Prices (CRSP), Fama CRSP Treasury bill files; and Board of Governors of the Federal Reserve System, H.15 statistical release.

Equation 41 extends the state dynamics in the Vasicek
(1977) model (equation 8) to include N latent factors.
The N × N matrix κ in the first term on the right-hand
side of equation 41 captures the dependence of infinitesimal changes in each xi(t) variable on the state vector
X(t). Similar to equation 8, the state vector X(t) reverts
to its mean Θ, which is now an N-dimensional vector of
constants. The process Z is an N-dimensional Brownian
motion. However, unlike the Vasicek (1977) model,
the instantaneous variance of the fluctuations in X is
no longer constant. It depends on the level of X via
the N × N diagonal matrix S(t), which has ith diagonal
element sii (t ) = αi + β′i X (t ).
To price bonds, we specify the market price of
risk, Λ(t). This is often assumed to depend on the state
vector X(t), rather than being constant, as in equation
17. For instance, Dai and Singleton (2000) set

this structure limits the variability of the compensation
that investors expect to receive for facing a given risk.
In particular, he shows that this condition is restrictive as it prevents risk compensation to switch sign
over time—a feature that is important to explain the
variation in Treasury returns. He goes on to extend the
market price of risk in a way that relaxes this restriction;
subsequently, Duarte (2004) and Cheridito, Filipović,
and Kimmel (2007) offer further generalizations.
Within this setting, the time t price of a zerocoupon bond with time to maturity τ is given by
43)

P( X , τ) = exp{ A( τ) + B( τ)′ X (t ) },

42) Λ (t ) = S (t )λ ,

where the functions A( τ) and B( τ) solve a system
of ordinary differential equations (ODEs); see, for
example, Duffie and Kan (1996). Thus, the yield y
on the bond with time to maturity τ is affine in the
state vector X:

where λ is an N × 1 vector of constants. This functional
form guarantees that risk compensation goes to zero as
the variance of the state vector vanishes—a condition
that rules out arbitrage opportunities. However, Duffee
(2002) notes that since the variance term is nonnegative,

44)	 y(X,t) =A(t) + B(t)X,
	
where A( τ) = − A( τ) /τ and B( τ) = − B ( τ) /τ . This is
similar to equations 19 and 20 for the Vasicek (1977)
model, except that the N-dimensional state vector X

64

2Q/2012, Economic Perspectives

takes the place of the spot rate r.
Semiclosed-form solutions are
also available for bond derivatives, for example, bond options
as well as caps and floors (see,
for instance, Duffie, Pan, and
Singleton, 2000).
Limits to arbitrage in the
market of government debt

		

Table 3

U.S. Treasury market liquidity
	
	
Percentile
		Standard		
Maturity	
Mean	 deviation	 10th	 50th	90th
A. Summary statistics for period June 17, 1991–June 15, 2001
Treasury bills’ bank discount rate bid–ask spreads
	
( - - - - - - - - - - - - - - - - basis points - - - - - - - - - - - - - - - )
Three months	
0.75	
0.90	
0	
1/2	
3/2
Six months	

0.80	

0.83	

0	

1/2	

3/2

The models we present in
One year	
0.71	
0.72	
0	
1/2	
3/2
this article hinge on the assumpTreasury notes’ prices bid–ask spreads
tion that whenever an arbitrage
	
( - - - - - - - - - - 32nds of a percentage point - - - - - - - - - )
opportunity arises, investors
Two years	
0.26	
0.18	
0	
1/4	
1/2
implement trading strategies to
Five years	
0.38	
0.26	
0	
1/2	
1/2
Ten years	
0.40	
0.29	
0	
1/2	
1/2
profit from it until asset prices
change to drive risk-adjusted net
B. Summary statistics for period January 1, 2001–January 31, 2012
expected returns to zero. In pracTreasury notes’ prices bid–ask spreads
tice, however, prices might not
	
( - - - - - - - - - - 32nds of a percentage point - - - - - - - - - )
converge if markets are not perTwo years	
0.36	
0.21
Five years	
0.48	
0.37
fect. For instance, frictions such
Ten years	
0.84	
0.47
as transaction costs, leverage
constraints, and limited availNotes: The table reports liquidity measures for the secondary U.S. Treasury market. Panel A
shows summary statistics for the intradaily bid–ask spreads for Treasury securities with a
ability of capital could hinder
maturity of three and six months, as well as one, two, five, and ten years, for the sample
period June 17, 1991–June 15, 2001. Panel B reports the mean and standard deviation
investors’ ability to trade away
of the bid–ask spreads for daily prices of Treasury securities with a maturity of two, five,
arbitrage opportunities. In this
and ten years for the sample period January 1, 2001–January 31, 2012.
Sources: Authors’ calculations based on intraday quotes data from GovPX; and Board of
section, we first provide eviGovernors of the Federal Reserve System staff’s calculations based on daily data from BrokerTec.
dence that transaction costs in
the U.S. Treasury market are
small. We then explore the role
of leverage and capital constraints in arbitrage tradcould be a noisy, and possibly even poor, liquidity
ing. In particular, we argue that financial institutions
measure. Fleming (2003) shows that trading volume
relax these constraints by participating in a vast repo
in the secondary U.S. Treasury market, as well as
market in which U.S. Treasury securities are a valuyields’ volatility, often peak during periods of market
able form of collateral. Next, we report some wellstress, when trading is more difficult than usual. In
documented patterns in Treasury securities’ yields that
contrast, the difference between bid and ask Treasury
can arise because of institutional constraints, arbitrage
prices (the so-called bid–ask spread) is a simple and
capital requirements, and market segmentation. We
more robust indicator of the ease with which invesconclude by briefly considering the relevance of
tors can exchange securities. For instance, Fleming
Treasury market frictions for monetary policy inter(2003) shows that bid–ask spreads on Treasury secuventions during the recent financial crisis and for the
rities correlate more highly with popular liquidity indispecification and estimation of no-arbitrage term
cators, such as price impact, defined as the sensitivity
structure models.
of price changes to net trading activity (the difference
between buyer- and seller-initiated trades). Moreover,
Transaction costs and liquidity in the U.S.
the bid–ask spread has an intuitive interpretation in
Treasury market
terms of transaction costs that an investor would incur
As we mentioned earlier, the secondary U.S.
if she were to buy/sell securities. For these reasons,
Treasury market is one of the largest and most imporwe focus on this measure of liquidity here.
tant financial markets worldwide. The around-the-clock
Table 3 shows summary statistics for the bid–ask
trading activity in this market, by both U.S. and interspread on Treasury prices quoted in the secondary
national participants, far exceeds that observed on many
U.S. Treasury market. Panel A relies on a sample
popular exchanges.
of intraday quotes on the most recent (on-the-run)
While high trading volume is often used as an inissues of bills and notes from June 17, 1991, through
dicator of asset marketability, there is evidence that it

Federal Reserve Bank of Chicago

65

June 15, 2001.3 It is evident that bid–ask spreads are
small across bond tenors. For instance, the median
spread on bills is one-half of a basis point. Spreads
remain low even in the right tail of the distribution
(for example, the 90th percentile is one and a half basis
points). Among Treasury notes, the two-year security
appears to be the most liquid, with a median spread
of one-quarter of a 32nd of a percentage point of par.4
Transaction costs remain low on longer-maturity
Treasury securities, with a typical bid–ask spread of
one-half of a 32nd of a percentage point. Table 3,
panel B shows similar diagnostics using a more recent sample of Treasury prices from January 1, 2001,
through January 31, 2012. At various maturities, spreads
fall in a range from 0.36 to 0.84 32nds of a percentage
point, and standard deviations are small, too. Taken
together, this evidence confirms that investors can
typically trade Treasury securities with ease across the
term structure. Those who seek to take advantage of misalignments in prices can do so at low transaction costs.
Leverage constraints and the availability
of arbitrage capital
A liquid secondary market is not necessarily
enough to guarantee that Treasury prices will converge
to their no-arbitrage equilibrium values. For instance,
Gromb and Vayanos (2010) suggest that transaction
costs are only one of the financial market inefficiencies
that can pose limits to arbitrage. In a simple theoretical
framework, they show that no-arbitrage pricing does
not hold in asset markets when arbitrageurs face leverage constraints (for example, Gromb and Vayanos, 2002;
Geanakoplos, 2003; and Gârleanu and Pedersen, 2011)
as well as equity capital requirements (for example,
Shleifer and Vishny, 1997). In this respect, the presence
of a vast market for repurchase agreements (repos) facilitates arbitrage trading greatly. A repo is a transaction
that combines a spot market sale with a simultaneous
forward agreement to repurchase the underlying instrument at a later date, often the next day (for example,
Duffie, 1996). Effectively, a repo is a collateralized loan.
The loan amount equals the sale value of the security
(typically given by the market price of the security
minus a margin, the so-called haircut), while the repo
rate is the interest on the loan. The counterparty in a
repo contract, who provides the funds for the loan
and earns interest at the repo rate, is said to engage
in a reverse repo.
Access to the repo market provides financial institutions with arbitrage capital to finance their trading
activity. For instance, if the price of an asset falls below
its fundamentals, a dealer can purchase it in the secondary
market. Concurrently, if the security constitutes an

66

acceptable form of collateral, the dealer can pledge it
in the repo market and thus obtain funds in the amount
of the price of the security, net of the repo haircut. The
funds borrowed against the security offsets, up to the
haircut, the cost to acquire it. Excess demand for the
security will push its price up. If the price increase
exceeds the cost of financing in the repo market, the
dealer will reap a profit. Conversely, if a dealer perceives
a security to be overpriced, the dealer can engage in a
reverse repo. The dealer can then sell the (overpriced)
collateral in anticipation that its price will fall. If that
happens, the dealer will be able to buy the security back
at a lower price on a later date, and use it to unwind
the reverse repo.
Over the past decades, the repo market has grown
dramatically in size and popularity (for example, Gorton
and Metrick, 2011). On one side, mutual funds (especially money market funds), corporations, and state
and local governments have been expanding their use
of reverse repos to put their cash reserves to work while
concurrently acquiring high-quality collateral for protection of their investment.5 On the other side, financial institutions have been increasingly relying on repos
to finance their operations. For instance, figure 4 shows
the outstanding value of repurchase and reverse repurchase agreements by primary dealers from 1996 through
2011. The outstanding value of repos on dealers’ books
is very high, and it exceeds that of reverse repos. The
increasing pattern in quantities is also evident, in spite
of a large decline at the peak of the U.S. financial crisis
in 2008–09. Yet, figure 4 greatly underrepresents the
magnitude of the U.S. repo market, which is, in fact,
imprecisely documented.6 Gorton and Metrick (2011)
provide an overview of different sources that estimate
it to be around $10 trillion in the late 2000s. These
estimates include transactions taking place in the triparty
repo market, in which clearing banks (JPMorgan Chase
and the Bank of New York Mellon) provide clearing
and settlement services to the lender (the cash investor)
and the borrower (the collateral provider); see, for example, Copeland, Martin, and Walker (2011). Estimates
by the Tri-Party Repo Infrastructure Reform Task Force
at the Federal Reserve Bank of New York place the size
of that market at nearly $1.7 trillion as of January 2012
(see table 4).
Treasury securities are a valuable form of collateral
in repurchase agreements. Table 4 shows that they account for approximately a third of the notional value
of the underlying securities in triparty repos (other
categories include securities issued by corporations,
federal agencies, and municipalities). Similar evidence holds in the bilateral repo market (for example,
Copeland, Martin, and Walker, 2011). Moreover, when

2Q/2012, Economic Perspectives

figure 4

Activity in the repurchase agreement (repo) market by the primary dealers
trillions oflabel
U.S. dollars
7
6
5
Total

4
3

Repos

2

Reverse repos

1
0
1996

’97

’98

’99

2000

’01

’02

’03

’04

’05

’06

’07

’08

’09

’10

’11

Notes: The plot depicts the outstanding value of repurchase and reverse repurchase agreements by primary dealers. Quantities include repos
backed by government, federal agency, and corporate and federal agency mortgage-backed securities.
Source: Federal Reserve Bank of New York.

pledged as collateral, U.S. government debt is subject
to a haircut that is usually very small. The margin on
short-term Treasury securities is typically around 2 percent. It is higher for longer-maturity bonds, which
have a higher price sensitivity to interest rate fluctuations; nonetheless, at approximately 5–6 percent, it is
below the margin on other securities that are forms of
collateral in repurchase agreements. Such margins have
been remarkably stable even during times of market
stress. This is in stark contrast with haircuts on corporate bonds, asset-backed securities, and collateralized
mortgage obligations that lacked the support of government guarantees.7
Table 4

Triparty repurchase agreement (repo) market
	
Asset group	

Collateral	Percentage
value	
of total

	(billions of U.S. dollars)
U.S. Treasury securities	
Other	
Total	

567.31	
34
1,098.93	66
1,666.24	100

Notes: The table summarizes the activity in the triparty repo market
for different types of collateral as of January 11, 2012. The “other”
category includes repos collateralized with corporate bonds, federal
agencies’ securities, and municipality debt.
Source: Authors’ calculations based on data from Federal Reserve
Bank of New York, Tri-Party Repo Infrastructure Reform Task Force,
available at www.newyorkfed.org/tripartyrepo/.

Federal Reserve Bank of Chicago

In sum, this discussion highlights that financial
institutions can rely on a vast repo market to fund their
arbitrage positions, especially in the Treasury market.
This is evident from the sheer value of Treasury securities pledged as collateral in repo transactions. Moreover, small and stable haircuts on Treasury securities
allow investors to finance a larger portion of their
positions via repos, contributing further to relaxing
capital and leverage constraints.
Yet, market frictions matter
Arbitrage opportunities across Treasury securities
tend to disappear quickly as investors trade them away
in a liquid secondary market, often using repos to finance their positions. Nonetheless, market frictions
can still play an important role in this market.
The fact that newer vintages of Treasury bonds
typically trade at a premium compared with older
vintages is a classic example. This phenomenon is
often documented by the spread between the yield for
on-the-run bonds (the most recent issue of bonds with
a certain maturity) and that for off-the-run bonds (older
issues of bonds with the same tenor). This evidence is
puzzling, as the cash flows associated with two long-run
(for example, 30-year) bonds are similar, even though
the bonds are issued six months apart. It motivates a
convergence trade that involves the purchase of the
(cheaper) off-the-run bond and a short position in the

67

(more expensive) on-the-run security.8 The spread between old vintages of bonds tends to narrow as time
goes by; thus, absent market frictions, a convergence
trade would generate an arbitrage profit. In practice,
arbitrageurs attempting to trade this strategy engage
in a reverse repo to establish a short position in the
on-the-run bonds (see the previous subsection). Since
these bonds are in limited supply, excess demand for
this collateral pushes repo rates below the market interest rate. This creates a significant cost of carry associated with the convergence trade, which erodes profits
(for example, Duffie, 1996; and Krishnamurthy, 2002).
Thus, a positive spread between off-the-run and on-therun bond yields is not an arbitrage as long as the spread
in repo rates compensates for the yield differential. Yet,
the puzzle remains: Why are new bonds more expensive than old ones? Duffie (1996) and Krishnamurthy
(2002) note that this situation can arise when some investors have a preference for liquidity and are restricted
from participating in the repo market. For example,
fixed-income mutual funds tend to hold liquid on-the-run
bonds (similar to those included in the bond indexes
to which they benchmark their performance).
The market for Treasury Inflation-Protected
Securities (TIPS) provides another striking example.
The U.S. Department of the Treasury started to issue
TIPS in 1997. In the early stages of TIPS life, secondary
market liquidity was very limited and TIPS traded at
a discount (for example, Ajello, Benzoni, and Chyruk,
2011; D’Amico, Kim, and Wei, 2010; Haubrich,
Pennacchi, and Ritchken, 2010; and Pflueger and
Viceira, 2011). By 2004, the liquidity premium in
TIPS yields had declined considerably as trading became more active in the TIPS market. More recently,
the TIPS market experienced new significant disruptions during the financial crisis, with the five-year TIPS
rate climbing above 4 percent in fall 2008. Fleckenstein,
Longstaff, and Lustig (2010) go one step further and
argue that TIPS prices allow for arbitrage opportunities.
In particular, they suggest a strategy that involves
buying TIPS and selling inflation protection in the
inflation swap market. They fine-tune the position to
replicate the cash flows of a nominal bond and conclude
that TIPS are undervalued relative to nominal Treasury
securities. The strategy, however, involves committing
arbitrage capital for the duration of the investment
(possibly a long period of time), with the risk that if
liquidity conditions deteriorate and investors are forced
to unwind the position, they might incur a loss. These
concerns, combined with disruptions in the TIPS and
inflation swap markets, might have contributed to
pushing the price differential up, especially in the fall
of 2008, during the financial crisis.

68

These examples suggest that investors’ demand
for bonds could depend on factors that go beyond the
maturity structure of the cash flow and the issuer’s
default risk. In the next subsection, we expand on
these ideas.
Preferred habitat theories
One relevant implication of the absence of arbitrage in the market for Treasury securities is a perfect
degree of substitutability across bond maturities—investors are willing to absorb any amount of bonds at
their equilibrium prices. Shocks to the net supply of,
or demand for, bonds of one maturity do not affect
other yields, nor the shape of the term structure of
interest rates. Early empirical studies that tested this
condition in the U.S. Treasury market could not identify
violations of the no-arbitrage principle. In particular,
several papers (for example, Modigliani and Sutch,
1966; and Ross, 1966) evaluate the effectiveness of
the so-called Operation Twist. Between 1962 and 1964,
the Federal Reserve and the U.S. Department of the
Treasury started selling short-term government bonds
while purchasing long-term ones. The policy objective
was to flatten the slope of the term structure by raising
short-term interest rates to improve the balance of payments while lowering long-term rates to stimulate
private investment. None of the papers found a significant effect of Operation Twist on the level of yields
across the term structure.9
These results discouraged further attempts to explore early theories that introduced limits to arbitrage
across Treasury securities of different maturities in
the form of investors’ preferred habitat, demand/supply
pressure, and bond market segmentation (for example,
Culbertson, 1957; and Modigliani and Sutch, 1966).
According to these theories, various classes of investors
have well-defined preferences for specific maturities.
Pension funds and life insurance companies, for example,
purchase bonds of longer maturities, while banks buy
short-term securities. Because of such differences in
preferences or regulatory requirements, bonds of different maturities end up being imperfect substitutes.
Consequently, equilibrium yields are determined by
the interaction between the demand by various clienteles
and the aggregate bond supply for each specific maturity.
More recently, new evidence has been supporting
the view that there are limits to arbitrage in government bond markets, consistent with preferred habitat
theories. For example, Greenwood and Vayanos (2010b)
study the consequences of the Pensions Act 2004, which
reformed the UK pension system. The act introduced
capital requirements to ensure the solvency of pension
funds and anchored the evaluation of their liabilities
to long-term interest rates. These institutional changes

2Q/2012, Economic Perspectives

prompted pension funds to hedge their liabilities
against interest rate risk and shifted their demand toward long-term government bonds. While these events
were unfolding, there was a simultaneous drop in longterm yields. This evidence is not inconsistent with demand pressure and habitat preference theories, and it
is difficult to explain based solely on the notion of
sudden changes in either interest rate expectations or
fundamental risk within the framework of a no-arbitrage
model. Similarly, Greenwood and Vayanos (2010a, b)
also document evidence of demand pressure in the
U.S. Treasury market. Between March 2000 and
December 2001, the U.S. Department of the Treasury
repurchased 10 percent of the long-term government
bonds outstanding as of December 1999. This intervention reduced the spread between the 20- and five-year
yields by 65 basis points in a few weeks and contributed to the inverting of the term structure slope.
Implications for monetary policy
Recent interventions of the Federal Reserve in
the government bond markets, known as large-scale
asset purchases (LSAPs), have revived interest in the
market segmentation hypothesis and its applications
to the nominal yield curve. After a first round of LSAPs
directed to the stabilization of the government agency
bond market in late 2008 (known as “quantitative
easing 1,” or “QE1”), the Federal Reserve started purchasing long-term Treasury bonds in 2009 and stepped
up its demand with a second purchase program of
$600 billion from November 2010 through June 2011
(often referred to as “quantitative easing 2,” or “QE2”).
Several recent empirical studies assess the effect
of the Federal Reserve’s purchases of long-term
Treasury securities and other bonds on interest rates
(for example, D’Amico and King, 2010, D’Amico et al.,
2012; Gagnon et al., 2010; Hancock and Passmore, 2011;
and Krishnamurthy and Vissing-Jørgensen, 2010, 2011).
This literature attempts not only to quantify the effect
of LSAPs on different yields, but also to identify the
channels through which these unconventional monetary policy interventions work.
A direct comparison of their findings is difficult
because of differences in data, sample frequency, and
approaches used to disentangle various channels. There
is some agreement that LSAPs have been effective in
lowering medium- and long-term rates.10 However,
the channels through which this policy works are
more controversial. For instance, Krishnamurthy and
Vissing-Jørgensen (2011) find evidence for a signaling channel, a unique demand for long-term safe assets, and an inflation channel for both QE1 and QE2;
and they find evidence for a mortgage-backed securities
prepayment channel and a corporate bond default risk

Federal Reserve Bank of Chicago

channel for QE1. They argue that Treasury-securitiesonly purchases in QE2 had a disproportionate effect on
Treasury and agency securities relative to mortgagebacked and corporate securities, with yields on the
latter falling primarily through the market’s anticipation
of lower future federal funds rates. This is consistent
with the view that QE2 constitutes a commitment by the
Federal Reserve to keep interest rates low in the future:
Lower expected future spot rates push long-term yields
down regardless of market segmentation (Clouse et al.,
2003; and Eggertsson and Woodford, 2003).
In contrast, D’Amico et al. (2012) and Gagnon
et al. (2010) conclude that reductions in interest rates
primarily reflect lower risk premiums rather than lower
expectations of future short-term interest rates. This is
consistent with the view that LSAPs reduce duration
risk and create a scarcity effect on long-term bonds that
are in high demand among some investor clienteles.
While empirically challenging, disentangling
the relative importance of various channels is critical
to guide monetary policy. On one side of the debate,
the findings for QE2 by Krishnamurthy and VissingJørgensen (2011) raise the question of whether the
main impact of a Treasury-securities-only QE may
have been achievable with a Federal Reserve statement
committing to lower federal funds rates (a policy that
does not require the Federal Reserve to commit its
balance sheet). On the opposite side of the debate, the
conclusions of D’Amico et al. (2012) and Gagnon et al.
(2010) support the use of LSAPs in the Treasury
market as a powerful tool of monetary policy easing
when the federal funds rate is at the zero lower bound.
Moreover, this debate has interesting implications for
no-arbitrage term structure models, which we discuss
in the next subsection.
Implications for no-arbitrage term structure models
Recent developments in the limits-to-arbitrage
literature are useful to sharpen the specification of
no-arbitrage term structure models. For instance,
Krishnamurthy and Vissing-Jørgensen (2011) suggest
that QE2 has affected long-term Treasury yields
mainly by lowering the market’s expectations of future
federal funds rates. To accommodate this evidence,
one could extend the term structure models discussed
in this article to allow for changes in the way agents
form expectations about future spot rates. Models that
allow for regime switches in monetary policy (for example, Ang et al., 2011; Bikbov and Chernov, 2008;
and Fuhrer, 1996) and evolving beliefs about inflation
dynamics (for example, Sargent, 2001) are a useful
step in this direction. One challenge is to extend the
analysis to an environment in which the federal funds
rate is at the zero lower bound.

69

Moreover, preferred habitat theories motivate
structural, theoretically founded restrictions on the
dynamics of yields that could be useful to refine existing dynamic term structure models. This is an interesting area of research that has seen considerable
progress in the past few years. Hamilton and Wu (2012),
for example, follow Greenwood and Vayanos (2010a, b)
and Doh (2010) in using the promising theoretical
framework developed by Vayanos and Vila (2009) to
rationalize and evaluate the Federal Reserve’s largescale purchases of U.S. Treasury securities across different maturities. In their models, risk-averse arbitrageurs
interact with preferred habitat investors, whose demand
for a bond with a specific maturity is an increasing
function of its yield. Hamilton and Wu (2012) introduce
this market segmentation in an affine term structure
model and conclude that the maturity structure of
debt held by the public affects the level, slope, and
curvature of the yield curve. In this setting, they find
that bond demand shocks have a significant effect on
bond prices, even in the presence of a binding zero
lower bound constraint for the federal funds rate (see
also related evidence in Krishnamurthy and VissingJørgensen, 2010).
Finally, the liquidity differential often observed
across bond vintages, which we discussed earlier,
raises the question about which Treasury yield series
are more suitable for the estimation of dynamic term
structure models. Most empirical studies have been
focusing on liquid on-the-run securities. However,
some researchers have advocated using off-the-run
bonds, which include a smaller liquidity premium
compared with new issues (for example, Gürkaynak,
Sack, and Wright, 2007). More broadly, this discussion
highlights the challenge to choose an appropriate measure for the risk-free rate. To what extent is the ability
to trade the security with ease a defining feature of
the risk-free asset? In principle, one could explicitly
model the liquidity wedge across yields to identify
the “true” term structure of interest rates. This approach
could be particularly useful when modeling segments
of the Treasury market that are more sensitive to liquidity
disruptions (for example, the TIPS market).11

70

Conclusion
In this article, we discuss the role of arbitrage
trading in the U.S. Treasury market. We start out by
defining the concept of arbitrage and illustrate it in a
simple one-period example. We then show how the
absence of arbitrage aligns risk-adjusted returns across
bonds with different maturities in the framework of
the Vasicek (1977) one-factor term structure model.
Along the way, we explain the link between bond risk
premiums and the underlying economy in a stylized
general equilibrium setting. Empirical evidence on
bond yields suggests that at least three factors drive
fluctuations in the term structure of interests rates.
This observation motivates a vast literature on multifactor models, which we briefly review with an emphasis on tractable affine specifications. The article ends
with an evaluation of market frictions in the government
debt market and their implications for no-arbitrage
term structure models.
In the models we discuss here, the factors are
typically latent variables (or linear combinations of
yields) void of immediate economic interpretation.
Thus, these models are silent about the response of
bond yields to macroeconomic shocks, as well as the
chain of events through which monetary policy intervention ultimately impacts the real economy. Early
studies investigate these questions by directly relating
current bond yields to past yields and macroeconomic
variables in a vector autoregression framework (for
example, Estrella and Mishkin, 1997; and Evans and
Marshall, 1998, 2007). More recently, much work has
gone into incorporating macroeconomic information
in no-arbitrage dynamic term structure models. We postpone further discussion of this literature to the future.

2Q/2012, Economic Perspectives

NOTES
Authors’ calculations based on data from the Securities Industry
and Financial Markets Association (SIFMA) and the New York
Stock Exchange (NYSE) Facts and Figures (formerly the online
NYSE Fact Book). The data are available at www.sifma.org/research/
statistics.aspx and www.nyxdata.com/factbook. The label “secondary” market refers to the market in which Treasury bills, notes, and
bonds are traded once they are issued. This label sets the market
apart from the “primary” market in which these securities are first
auctioned and sold by the U.S. Department of the Treasury.

1

See the “About the FOMC” section at www.federalreserve.gov/
monetarypolicy/fomc.htm.

2

Treasury bill prices are quoted on a bank discount rate basis with
tick size of 1 basis point. Treasury notes and bonds are quoted at
percentage of par in 32nds of a point. See, for example, Sundaresan
(2001) for more information on trading practices in the secondary
U.S. Treasury market.

3

The two-year note is the shortest-maturity coupon-bearing security
issued by the U.S. Treasury. This makes it appealing to people who
seek a medium-term investment that comes with the convenience
of regular coupon payments.

See, for example, Gorton and Metrick (2011) and Krishnamurthy
(2010) for evidence based on the bilateral repo market. Margins
and funding were mostly stable during and after the crisis period in
the triparty repo market, except in rare cases when funding dropped
precipitously (Copeland, Martin, and Walker, 2011).

7

Convergence trades were important positions in the portfolio of
the Long-Term Capital Management (LTCM) fund. These trades
received considerable attention in the news in 1998, when an increase
in the spread between off-the-run and on-the-run bond yields produced significant losses for LTCM. The fund was eventually liquidated.
See, for example, Lewis (1999).

8

9
Recently, Swanson (2011) revisits this episode using an event-study
approach that matches high-frequency changes in financial markets
within narrow windows of time around major, discrete announcements to measure the effects of those announcements. He finds
some support for the notion that Operation Twist performed as its
designers thought it would.

4

5
In the United States, retail depositors at a bank insured by the
Federal Deposit Insurance Corporation (FDIC) are entitled to interest
payments and are reimbursed up to a certain amount if the bank
fails. Limits to the amount of deposit insurance reduce the appeal
of demand deposit accounts to corporations. Under the Federal
Reserve’s Regulation Q, as in effect until July 21, 2011, corporations were not entitled to earn interest on demand deposit accounts.
In contrast, engaging in a reverse repo allows institutional investors
to earn interest at lower risk because of the presence of collateral.

This is not, however, a unanimous view. For a dissenting voice,
see, for instance, Cochrane (2011), who states: “QE2 doesn’t seem
to have lowered any interest rates. Yes, five-year rates trended
down between announcements, though no faster than before. The
November [2010] QE2 announcement and subsequent purchases
coincided with a sharp Treasury rate rise. The five-year yields
where the Fed bought most heavily didn’t decline relative to the
other rates, as the Fed’s ‘segmented markets’ theory predicts. The
corporate and mortgage rates that matter for the rest of the economy
rose throughout the episode.”
10

Recent work by D’Amico, Kim, and Wei (2010) is an interesting
example.

11

6
Most estimates of the repo market size rely on surveys of its participants. Adrian et al. (2012) provide an overview of data requirements necessary to monitor repos and securities lending markets
for the purposes of informing policymakers and researchers about
firm-level and systemic risk. They conclude that data collection is
currently incomplete, and argue that a comprehensive collection
should include six characteristics of repo and securities lending
trades at the firm level: principal amount, interest rate, collateral
type, haircut, tenor, and counterparty.

Federal Reserve Bank of Chicago

71

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