[Economic Report of the President (2013)]
[Administration of Barack H. Obama]
[Online through the Government Printing Office, www.gpo.gov]



Following the recession that began in December 2007, the most severe
since the Great Depression, the economy is healing and moving in the
right direction. By the fourth quarter of 2012, real output was 2.5
percent above the level at its previous business-cycle peak in the
fourth quarter of 2007. The economy has added 6.1 million private
sector jobs, and 5.5 million jobs overall, since the level of
employment hit bottom in February 2010. During the four quarters of
2012, real gross domestic product (GDP) increased at a moderate 1.6
percent rate. Over the 12 months of the year, 2.2 million jobs were
added, and the unemployment rate, while still elevated, dropped 0.7
percentage point to 7.8 percent.
The near-term outlook is for further expansion. Consumer spending
is rising moderately, as the gradual healing in the labor market lifts
income and as households continue to pay off debt and rebuild wealth. A
wide array of indicators suggests the housing sector is finally
recovering, and the long contraction in the State and local sector
appears to be coming to an end. Financial conditions continue to become
more supportive; for example, senior loan officers report that banks
have become more willing to lend to both small and large businesses.
Although many of the headwinds that have buffeted growth are
receding, some remain. Long-term fiscal sustainability requires a path
of declining government spending and rising revenue that will exert
fiscal drag on the economy. In addition, ongoing congressional
deliberations over the appro�priate means through which long-term
fiscal sustainability will be achieved foster uncertainty that could
weigh on consumer and business confidence. Moreover, tepid growth
across the global economy--particularly in Europe and Asia--may reduce
growth in U.S. exports and slow the rebound in domestic manufacturing
This chapter provides an overview of the economic recovery so far,
beginning with a review of notable macroeconomic events of 2012. The
chapter then turns to a broader discussion of the recovery in
historical context. Although the recovery has been slow by historical
standards, much--perhaps two-thirds, according to a recent study by the
Congressional Budget Office (CBO 2012d)--of the slower growth relative
to previous postwar recoveries reflects the long-term demographic
shifts discussed in Chapter 4 as well as other long-term structural
factors. The remaining one-third reflects unique cyclical factors
largely related to the financial crisis, including limitations on the
ability of households and small businesses to borrow, which led to
associated reductions in consumption and investment; the slow recovery
of the housing sector as it works off excess inventories of foreclosed
and distressed properties; the contraction of State and local
government budgets arising, in part, from the drop in assessed house
values and property taxes; softening export demand resulting from
slower growth in Asia and Europe; and limitations on conventional
monetary policy due to the Federal Reserve's lowering of its main
policy rate to zero percent (the ``zero lower bound'').
As severe as the recent recession was, the drop in real GDP in the
United States as a result of the financial crisis of 2007-08 was
smaller than both the average decline in other global financial crises
over the past 40 years and the contraction in the aftermath of the 1929
stock market crash here in the United States. Furthermore, the recovery
since June 2009 has been stronger than in most other developed
economies. Active government poli�cies helped the economy avoid an even
deeper recession and have played an important role in supporting the
recovery. These active policies include the American Recovery and
Reinvestment Act (the Recovery Act), the tempo�rary payroll tax cut,
the extension of unemployment insurance benefits, and both standard and
nonstandard monetary policy conducted by the Federal Reserve.

An Economy in Recovery: Key Events of 2012

The past year was another challenging one for an economy in the
midst of a recovery from a global financial crisis. Concern over
European sovereign debt and the ongoing fiscal consolidation in Europe
contributed to a contraction in the European economy during the year,
and growth among several of our Asian trading partners also slowed.
Natural disasters such as the severe drought in the Midwest and
Hurricane Sandy in the Northeast impaired economic output over much of
the year. Although the economic sanctions against Iran do not appear
responsible (Box 2-1), retail gasoline prices fluctuated widely over
the course of 2012, which may have intermittently dampened economic
activity. The possibility of tax increases and mandatory spending cuts
that had been scheduled to take place at the beginning of 2013 loomed
large as the year closed and may have hampered consumer and business
Real GDP rose 1.6 percent over the four quarters of 2012, a bit
below the pace in 2011 (quarterly figures are shown in Figure 2-1).
Growth was uneven (but no more than usual) throughout the course of the
year, reflect�ing, in part, the impact of the drought and Hurricane
Sandy, as well as out�sized swings in Federal defense outlays and
inventory investment. Outside of these factors, business fixed
investment and exports slowed notably from 2011. In contrast, personal
consumption spending continued to post moder�ate gains, rising 1.9
percent over the four quarters of 2012, matching the rate of growth
recorded in 2011. The fiscal contraction among State and local
governments appears to be easing somewhat, and the residential
construction sector, which turned a corner in 2011, strengthened
further in 2012, growing for seven consecutive quarters for the first
time since 2004-05.
The recovery in payroll employment, like that in real output, was
uneven. Payrolls expanded briskly at the beginning of the year, but job
growth slowed in the spring and early summer before picking up again in
the late summer and fall. The fact that the worst months of the crisis
occurred during the winter raises the question of whether normal
seasonal adjustment procedures contributed volatility to higher
frequency indicators, but that


Box 2-1: Effectiveness of Iran Sanctions

In cooperation with an international coalition, the United States
has established strict economic sanctions against the Islamic Republic
of Iran, sanctions described by this Administration and others as
``comprehensive and biting.'' The goal of these sanctions is to
persuade the Iranian government to abandon its nuclear weapons program.
Since President Obama took office, he has steadily increased unilateral
and multilateral pressure on Iran because of its inability to meet its
international obligations. As a part of that effort, Congress passed
and the President signed the Comprehensive Iran Sanctions,
Accountability, and Divestment Act of 2010, the National Defense
Authorization Act for Fiscal Year 2012, and the Iran Threat Reduction
and Syria Human Rights Act of 2012. These laws increased our ability to
target the Iranian Central Bank, private banks supporting the Iranian
regime, and--importantly--the Iranian petroleum sector. In addition to
these efforts with Congress, the President has signed Executive Orders
imposing additional sanctions against the Iranian energy and
petrochemical sectors. These actions received support from members of
the international community, includ�ing the European Union and our
allies in the Middle East. The United States has also worked to
establish multilateral sanctions. For example, the United States
collaborated with other members of the United Nations Security Council
to adopt Resolution 1929, which called on Iran to end its nuclear
program and imposed the broadest multilateral sanctions ever faced by
the regime.
For Iran, the consequences of the sanctions have been severe.
Iranian President Mahmoud Ahmadinejad called these sanctions ``the most
severe and strictest sanctions ever imposed on a country.'' The value
of Iran's currency, the rial, has dropped substantially in 2012.
Governments and private firms from around the world have ended business
with, and divested from, Iran, as these actions now carry a heavy
price. And perhaps most importantly, oil production in Iran has
nose-dived (see the figure below). According to the U.S. Energy
Information Administration (EIA), Iran's crude oil production, which
averaged 3.7 million barrels a day in 2011, dropped to approximately
2.7 million barrels a day by the end of 2012, a decline of about 30
percent. That amounts to billions of dollars in lost revenues for the
The effect of these sanctions on the U.S. economy has been
minimal. The sanctions do not appear to have increased the price of
oil. As shown in the figure above, while Iranian oil production has
dropped, world supply has not. The effects of the sanctions are
reviewed regularly; for example, Federal agencies, such as the EIA,
watch closely for develop�ments in international energy markets. The
President and Congress have structured the implementation of the
sanctions to minimize any impact on global energy markets and, by
extension, the U.S. economy, and the authorities granted to the
executive branch allow us to continue to moni�tor those effects going
Sanctions do not always prevent or replace war. Indeed, sanctions
have sometimes led to war, as shown by Lektzian and Sprecher (2007).
Moreover, the fact that Iran's currency has depreciated, its oil
production and exports have plunged, and its economy has slowed does
not, by itself, fully answer the question: ``Are the sanctions
working?'' The sanctions will have succeeded if and when Iran ends its
nuclear program.
Evidence on the effectiveness of sanctions in other settings is
mixed. In a widely-cited study, Hufbauer, Shott, and Elliott (1990)
find that the rate of success of economic sanctions is low�about 35
percent. Some argue that even 35 percent is an overestimate (Pape
1997). However, Morgan, Bapat, and Krustev (2009) find that adjusting
the sample of sanctions to include threats of sanctions in addition to
sanctions actu�ally imposed, and limiting the focus to more recent
events, increases the success rate from 35 percent to 45 percent. The
success rate is even higher when costs borne by the target are severe
or when sanctions are multilateral, both of which are the case with
Iran. Moreover, Marinov (2005) finds economic sanctions do tend to
destabilize the governments they target, that is, they increase the
probability of leadership or regime change.


does not seem to be the case, as discussed in Data Watch 2-1. The
unemployment rate, which fell 0.8 percentage point during 2011, fell
another 0.7 percentage point during 2012, reaching 7.8 percent by the
end of the year. The drop in the jobless rate during 2012 was
concentrated in the first and third quarters of the year, with
most--roughly 90 percent--of this decline accounted for by employment
growth rather than withdrawal from the labor force.

European Crisis and the Slowdown in Global Growth

In 2012, the consequences of the European debt crisis continued to
affect the world economy. In many advanced economies, fiscal
consolidation, vulnerable financial systems, and market uncertainty
have suppressed demand, and world economic growth has suffered as a
consequence. While these adverse shocks are, for the most part,
external to the United States, the globalized nature of world trade and
financial markets means that the United States cannot escape their
impact. Likewise, the turmoil in European financial markets led U.S.
branches of foreign banks to tighten credit stan�dards for commercial
and industrial loans.

Hurricane Sandy and the Drought

Natural disasters cause human suffering and physical destruction.
From the perspective of economic activity, their widespread disruptions
also lead to lost work and output. Historical experience suggests,
however, that over time much of this lost production is recouped. After
storms, some of the missed work is made up and sizable additional
expenditures are required for cleanup, repairs, and rebuilding. Thus,
while hurricanes can have a major impact on regional economies,
national trends in economic activity typically have not been affected
by calamities such as hurricanes and droughts.
Hurricane Sandy is now estimated to have resulted in $35.8 billion
in damages to private fixed assets according to the Commerce Department,
which would rank it as the second costliest natural disaster in recent
U.S. his�tory after adjusting for inflation, though still well behind
Hurricane Katrina in 2005. In addition, power outages that affected 8.2
million customers on October 30, and left 930,000 without power a week
later, rendered many workers unable to perform their jobs. The storm
also disrupted transporta�tion centers such as seaports, airports, and
rail lines, as well as refineries and factories, many of which were
restored only gradually.
All told, analysts currently estimate that Hurricane Sandy lowered
real GDP growth in the fourth quarter by around 0.2 to 0.5 percentage
point at an annual rate. Although indicators such as industrial
production, vehicle sales, and jobless claims were adversely affected
in October or early November, they subsequently improved and rebuilding
activity is likely to provide some support to economic growth going
forward. The region hit by Sandy has ample spare capacity available to
be mobilized for storm recovery efforts: in October 2012, just before
the storm hit, the unemployment rate was 0.6 percentage point higher in
the five states most directly affected by Hurricane Sandy than in the
rest of the country. Construction employment, in particular, had
declined in the first 10 months of 2012 across these five states while
seeming to have stabilized or expanded elsewhere. Supplemental Federal
relief for reconstruction after Sandy, which was enacted in January
2013, should provide needed repairs and reconstruction and thereby
support short-term economic growth in the region.
As a result of the severe drought in the Midwest that damaged corn
and soybean harvests, farm inventory investment subtracted an average
of one-fourth of a percentage point from real GDP growth in the second
and third quarters of 2012 (for additional discussion, see Chapter 8).
In 2013, the initial estimates of quarterly farm output will be based
on the Agriculture Department's initial projection of annual farm
output, which in turn will be based on an assumption of normal growing
conditions. As a result, farm production, as measured in the National
Income and Product Accounts, will probably jump up beginning in first
quarter of 2013, bringing with it an associated bump up in estimated
GDP  growth.

Monetary Policy

In 2012, the Federal Open Market Committee (FOMC) continued to
provide substantial policy accommodation and announced several new
steps, including for the first time linking its forward guidance for
the main policy interest rate to a specific level of the unemployment
Between September 2011 and June 2012, the FOMC conducted the first
installment of its Maturity Extension Program, widely known as
Operation Twist. As first announced, the Fed said it would purchase
``by the end of June 2012, $400 billion of Treasury securities with
remaining maturi�ties of 6 years to 30 years and...sell an equal amount
of Treasury securities with remaining maturities of 3 years or less.''
According to the FOMC, the objective of this program was to ``put
downward pressure on longer-term interest rates'' and thus provide an
additional stimulus for the overall economy. In June 2012, the
Committee decided to continue this program at a pace of approximately
$45 billion a month, which corresponded to an additional ``face value
of about $267 billion by the end of December 2012,'' according to the
minutes of the June meeting. Then, in September 2012, the FOMC
announced it would further ``increase policy accommodation by

Data Watch 2-1: Seasonal Adjustment in Light of the Great Recession

For the purposes of economic analysis, researchers are primarily
interested in the longer-term direction of a time series and any
deviations from that trend. Seasonal fluctuations in the data arising
from summer holidays, seasonal shopping, and so forth can obscure these
trends and deviations. As a result, most public sources of economic
data endeavor to remove normal seasonal patterns from their
high-frequency indica�tors. Unfortunately, this process of seasonally
adjusting economic data is fraught with complexity. Seasonal factors
cannot be directly observed and must be estimated using various
statistical techniques. Moreover, the seasonal patterns for a
particular series may not be constant over time. Thus, the accurate
estimation of seasonal patterns is a challenge of great importance to
the economics community and policymakers.
A number of analysts have argued that the severity of the Great
Recession may have distorted several high-frequency economic
indicators. The Great Recession, which lasted from December 2007
through June 2009, was particularly acute during the fall of 2008 and
the winter of 2009. Real GDP fell more than 7 percent at an annual rate
over the fourth quarter of 2008 and the first quarter of 2009, and
total nonfarm payroll employment plunged by more than 4 million jobs
from September 2008 to March 2009. Given the severity of the downturn
during this period, some commentators have hypothesized that the
outsized decline in eco�nomic activity may have been inadvertently
incorporated into the sea�sonal factors for several key economic
indicators. And as a consequence of this statistical bias in the
seasonal adjustment process, these observers have raised concerns that
the pace of the current recovery has exhibited an abnormal seasonal
pattern in which economic activity has appeared not only substantially
stronger than it really is during the fall and winter but also
correspondingly weaker during the spring and summer.
A few providers of economic data have acknowledged this concern
and noted that unusually sharp swings in certain indicators may not be
properly accounted for by standard seasonal adjustment techniques. The
Federal Reserve reported that the application of default seasonal
adjustment procedures to its monthly industrial production data would
have artificially raised output in many industries during the first
halves of the years 2008 through 2010, if these distortions not been
identified in advance and corrected (Federal Reserve Board of Governors
2011). And the Institute for Supply Management concluded that its
typical seasonal adjustment procedures did not adequately identify
outlier observations during the recent recession. As a result, it
introduced more precise criteria for the detection of outliers as part
of the seasonal adjustment of its purchasing manager survey data
(Institute for Supply Management 2012). Nevertheless, it is important
to emphasize that these particular issues pertain to the use of default
seasonal adjustment techniques. In general, statistical agencies
approach the seasonal adjustment of eco�nomic data idiosyncratically
based upon the unique characteristics of each individual time series.
Indeed, detailed studies of a wide range of principal economic
indicators suggest that the seasonal adjustment techniques that had
already been employed by the Bureau of Labor Statistics (BLS)
adequately accounted for the effects of the Great Recession. BLS
analysts calculated alternative seasonal factors for total nonfarm
payroll employment after manually excluding the sharp declines that
were recorded during the downturn (Kropf and Hudson 2012). This
counterfactual experiment failed to generate meaningful revisions to
the actual published estimates of total nonfarm payroll employment
since January 2010. In fact, the BLS analysts concluded that the
implementation of these counterfactual seasonal factors would have
revised total nonfarm payroll employment upward by a mere 24,000 jobs
over the second and third quarters of 2011 (in other words, an average
of 4,000 jobs a month) and downward by just 19,000 jobs over the fourth
quarter of 2011 and the first quarter of 2012 (or an average of roughly
3,000 jobs a month). BLS analysts also thor�oughly investigated the
seasonal adjustment of the Current Population Survey data over the
course of the recovery (Evans and Tiller 2012). This inquiry showed
that alternative assumptions regarding seasonal adjustment did not
meaningfully affect estimates of the unemployment rate since 2007.
Macroeconomic Advisers (2012) tested the stability of seasonally
adjusted nominal GDP by comparing the official estimates to a proxy
series that had been constructed using the source data for the national
accounts. Contrary to the hypothesis that inaccuracies in the seasonal
adjustment process have been artificially suppressing economic activity
during the spring and summer months of the current recovery, this
analysis found that seasonal factors had not been subtracting as much
from GDP growth during the second and third quarters of each calendar
year as they had before the downturn. All told, these analyses provide
little evidence to support serious concerns over the soundness of
seasonally adjusted high-frequency economic variables.

purchasing additional agency mortgage-backed securities at a pace of
$40 billion per month.''
The September and June actions together, the Committee said, were
intended to increase the Federal Reserve's ``holdings of longer-term
securities by about $85 billion each month through the end of the
year.'' In December

2012, the Committee announced that it would replace the expiring
Maturity Extension Program with a program of purchases of longer-dated
Treasuries at a pace of $45 billion a month, thereby further expanding
its balance sheet, rather than funding these purchases with the sale of
shorter-dated securities, as was the practice under Operation Twist.
These purchases, combined with its September 2012 decision to purchase
$40 billion a month in agency mortgage-backed securities, kept total
purchases of longer-term securities at $85 billion a month.
The nature of the Fed's forward guidance also evolved over the
year. The FOMC announced in September 2012 that it would explicitly
condition future policy decisions on progress in the labor market and
issued additional forward guidance that the Fed's main policy interest
rate would likely remain low through mid-2015, an extension from late
2014 as previously announced. In December 2012, the Committee went a
step further and announced that it would maintain the ``exceptionally
low range for the federal funds rate...at least as long as the
unemployment rate remains above 6� percent, inflation between one and
two years ahead is projected to be no more than a half percentage point
above the Committee's 2 percent longer-run goal, and longer-term
inflation expectations continue to be well anchored.'' The explicit
link to numerical values of economic variables replaced the previous
reference to a ``mid-2015'' reference date that had been introduced in
In August 2012, during a speech at the annual Federal Reserve Bank
of Kansas City Economic Symposium, Federal Reserve Chairman Ben Bernanke
assessed the effectiveness of the balance sheet and forward guidance
policies that had been implemented in response to the recession.
Bernanke (2012a) surveyed research finding that large-scale asset
purchases (LSAPs) had significantly lowered yields on long-term
Treasury notes, corporate bonds, and mortgage-backed securities;
reduced retail mortgage rates; and also boosted stock prices (see for
example, Krishnamurthy and Vissing-Jorgenson 2011). One study by Chung
and others (2012) used the Federal Reserve Board's FRB/US model of the
economy and found that the early phase of the Fed's LSAPs may have
raised the level of real GDP by almost 3 percent and increased private
payroll employment by more than 2 million jobs, relative to what
otherwise would have occurred. Although Chairman Bernanke cautioned
against putting too much weight on the estimates of any particular
study, he concluded that ``a balanced reading of the evidence supports
the conclusion that central bank securities purchases have provided
meaningful support to the economic recovery while mitigating
deflationary risks.''

Fiscal Policy

After months of negotiations, in February 2012 Congress extended
both the 2 percentage point cut in the payroll tax and the Emergency
Unemployment Compensation program through the end of the year. These
temporary measures, which were among the Administration's key economic
priorities for 2012, had originally been put in place with the passage
of the 2010 Tax Relief, Unemployment Insurance Reauthorization, and Job
Creation Act. The extension through December 2012 provided critical
support to American families trying to weather the various headwinds
that threatened the recovery over the course of the year.
The economy faced great uncertainty as the end of calendar year
2012 approached. As a result of the confluence of various policies that
had been passed in previous years, the economy faced a ``fiscal cliff''
of across-the�board tax hikes as the Bush-era tax cuts expired, a sharp
reduction of the Alternative Minimum Tax (AMT) exemption amounts to the
levels that had been in effect in 2001, the imposition of substantial
spending cuts through budget sequestration, and the expiration of a
number of other tax provi�sions. In addition, temporary measures to
support the economy, including the extension of unemployment insurance
benefits and the payroll tax reduction, were also set to expire. As the
end-of-year deadline approached, uncertainty in financial markets
ticked up, although not as much as during the August 2011 debt ceiling
debate. This uncertainty was partly resolved by the passage of the
American Taxpayer Relief Act by the House on January 1, 2013, averting
what could have been sharply contractionary policies.1
Looking ahead, the American Taxpayer Relief Act--which permanently
extends the middle-class tax cuts, indexes the AMT to inflation, and
raises rates on the highest-income taxpayers in order to reduce the
deficit relative to the previous policy baseline (see Chapter 3)--has
removed much of the uncertainty about taxes facing the economy.

1 Several studies suggested that going over the full fiscal cliff would
likely result in a recession and substantial job losses; see for
example CBO (2012a). These studies, including the CBO report, focused
on cash flow effects of the fiscal cliff (revenues and spending). A
growing body of literature suggests that the uncertainty created by
going over the cliff would have further hurt economic activity and
employment, although those channels are more difficult to quantify; see
for example Bloom (2009).

Developments in 2012 and the Near-Term Outlook

Labor Market Trends

The labor market continued to heal in 2012. The private sector
added 2.2 million jobs, although State and local government employment
fell by 32,000, after falling by 286,000 in 2011. Private sector
payroll employment has grown in each month since February 2010.
Focusing on 12-month changes to abstract from monthly and seasonal
volatility, the 12-month change in total nonfarm payroll employment
excluding Census hiring has been smooth, hovering around 2 million jobs
since the fall of 2011, as shown in Figure 2-2.
Private-sector job growth during the current recovery has been
roughly comparable with that in the 1991 recovery and noticeably faster
than in the 2001 recovery, as illustrated in Figure 2-3. As is typical,
the recovery in hiring since 2009 lagged the recovery in output.
Private nonfarm payrolls in the current recovery began growing 9 months
after the business-cycle trough. By comparison, payrolls first began
expanding consistently 12 months into the 1990�91 recovery, and
sustained private-sector job growth in the 2001 recovery did not begin
until 21 months after the official end date of the recession. Thus,
although the 2007�09 recession lasted longer and led

to deeper job losses than did the recessions of 1990-91 and 2001,
recovery in the labor market began somewhat sooner.
Despite continuing improvements in hiring, the unemployment rate
remains elevated, reflecting both the deep losses during the recession
and the steady but moderate pace of hiring during the recovery. The
unemploy�ment rate has receded from its peak of 10.0 percent in October
2009 to 7.8 percent in December 2012, with 0.7 percentage point of that
decline during the 12 months of 2012 (Figure 2-4). Layoffs--as measured
by the four-week average of initial claims for unemployment
insurance--fell in 2012 (Figure 2-5), and other indicators of labor
market adjustment such as the workweek continued to show improvement.
By December 2012, the workweek had increased to 34.4 hours, recovering
most of the 0.8 hour lost during the recession.2

Almost all of the decline in the unemployment rate in 2012
reflects growth in employment rather than labor force withdrawal.3
Nevertheless, the recession coincided with a sharp drop in the labor
force participation
2 A lengthening of the workweek by 0.1 hour is roughly equivalent, in
terms of labor input, to an increase in employment of more than 300,000
3 This calculation reflects an adjustment for updated Census
Bureau population estimates that were incorporated into the January
2012 Current Population Survey by the Bureau of Labor Statistics (BLS).
In accordance with usual practice, the BLS does not revise the official
Current Population Survey estimates for earlier months to reflect the
updated population values.

rate, which fell from 66.0 percent in December 2007 to 64.9 percent in
February 2010--a period when the economy shed jobs at an average rate
of 320,000 a month. Since then, labor force participation has continued
to decline, reaching 63.6 percent by December 2012.

To what extent can this sharp drop in the labor force
participation rate be attributed to the prolonged slack in the labor
market? Answering this question requires distinguishing between
cyclical movements arising from the prolonged downturn and the
demographic trends of an aging, and thus retiring, workforce. To this
end, Table 2-1 provides a decomposition of the labor force
participation rate into a trend component and a cyclical component over
the current business cycle. The trend, or demographic, component from
2007-12 is estimated by extrapolating a linear trend in the labor force
participation rate from the 10 years preceding 2007,4 and the cyclical
component is computed as the difference between the actual labor force
participation rate and this trend.
As can be seen in the bottom half of Table 2-1, the labor force
participation rate fell by 2.2 percentage points from 2007-12. Of that
drop, 1.2 percentage points are attributed to a declining trend caused
primarily by the aging of the workforce, while 1.0 percentage point is
cyclical. An analogous calculation for 1980-85--the only other postwar
period that includes a double-digit unemployment rate--shows that the
labor force participation rate rose by 1.0 percentage point over the
twin recessions of the early 1980s. But at that time, trend labor
force participation was rising by 2.0 percentage points--a consequence
primarily of the rising participation of women dur�ing that period--so
the cyclical component during the early 1980s declined by 0.9
percentage point. Thus, the cyclical component of the change in the
labor force participation rate during 2007-12 is close to its value
over 1980-85, and so, by this measure, the recession-induced rate of
labor force decline differs little from the early 1980s.

Consumption and Saving

Consumer spending, which accounts for approximately 70 percent of
GDP, rose moderately in 2012, as credit conditions continued to ease,
household liabilities fell relative to income, and the labor market
improved. Real household consumption grew 1.9 percent during the four
quarters of the year and was supported by an extension of the payroll
tax cut, which first went into effect in January 2011 as part of the
Tax Relief, Unemployment Insurance Reauthorization, and Job Creation

4 Specifically, for each gender and age group, labor force
participation rates are projected using the previous 10-year trend, and
the trend in the overall participation rate over the subsequent period
is computed using actual population weights for each group.

Several key developments in 2012 shaped the contours of consumer
Household Income in 2012. Nominal personal income grew 5.0 percent
during the four quarters of 2012, a somewhat faster pace of growth than
in 2011. Growth in nominal personal income over the course of the year
was largely attributable to gains in employee wages, salaries, and
benefits. Real disposable personal income, which is personal income
less personal taxes and adjusted for price inflation, rose 3.2 percent
over the four quarters of 2012, a substantial improvement over the 2011
increase of 0.3 percent. The pattern partly reflects a moderation in
inflation mostly due to a drop in energy price inflation. The
expiration of the temporary payroll tax cut will subtract about $120
billion from disposable income in 2013.
Household Wealth and Saving in 2012. Households continued to
rebuild their balance sheets in the aftermath of the worst economic
downturn since the Great Depression. On balance, the wealth-to-income
ratio, depicted in Figure 2-6, rose over the first three quarters of
2012 and has improved considerably since the beginning of 2009.
Consumption as a share of disposable income tends to fluctuate with the
wealth-to-income ratio. As a rule of thumb, a one dollar drop in wealth
reduces annual consumer spending by two to five cents. The decline in
the wealth-to-income ratio from the first quarter of 2007 to its low
point in the first quarter of 2009 was equivalent to roughly 1.7 years
of disposable income. Through the third quarter of 2012, this measure
regained the equivalent of nearly 0.7 year of disposable income. This
simple framework suggests that the household wealth lost during the
recession has not yet been recovered and that this loss of wealth has
left the level of consumption roughly 2 to 6 percent below

what it would have been otherwise. Much of that loss of wealth resulted
from the bursting of the housing bubble, and the wealth-to-income ratio
now is where it was in the mid-1990s (before the information technology
stock price bubble) and early 2000s (before the housing bubble).
The personal saving rate--expressed in the National Income and
Product Accounts as personal saving as a share of disposable personal
income--averaged 3.9 percent in 2012, a bit lower than the rate
observed in 2011. The rate of personal saving jumped during the
recession as households sharply curtailed spending in response to the
crisis, but overall, the saving rate fell modestly over the course of
the recovery and is now at the level it was in the early 2000s.
Household Credit and Deleveraging in 2012. Lending standards for
consumers, as reported in the Federal Reserve's Senior Loan Officer
Opinion Survey, eased for the third consecutive year. Moreover, driven
by a surge in nonrevolving lending categories (such as auto and student
loans), consumer credit expanded 5.7 percent at an annual rate over the
four quarters of 2012. However, because mortgage credit continued to
decline, the overall level of household debt decreased 0.6 percent at
an annual rate over the first three quarters of 2012. Household debt
has declined every year since 2007, as households continue to
Although household debt increased in the period before the
financial crisis, the extent to which household leverage has
restrained consumer spending during the recovery remains unsettled.
Traditional models of consumption imply that, absent borrowing
constraints, households con�sume a fraction of their expected lifetime
wealth, which implies that the consumption-wealth ratio fluctuates
around its mean (Campbell 1987; Lettau and Ludvigson 2003). This theory
and its extensions imply that con�sumption and saving will adjust to
maintain appropriate lifetime savings, so for example a loss in housing
wealth will cause consumers to increase saving, as they did during and
shortly after the recession, to pay down debts and rebuild retirement
savings. But consumers, of course, face borrowing constraints and can
be locked into mortgage or debt payment streams that might impose
additional, direct limitations on consumption. Dynan (2012) and Mian,
Rao, and Sufi (2012) provide evidence that these additional effects of
the so-called debt overhang from the collapse in housing have further
suppressed consumption during the recovery.
Whether one looks at wealth or leverage, household finances have
improved substantially in recent years. From the third quarter of 2007
to the first quarter of 2009, household net worth fell by an estimated
$16.1 trillion. By the third quarter of 2012, however, households had
added $13.5 trillion, recovering more than 80 percent of wealth lost.
Households have also made progress in reducing debt burdens. Total
household debt stood at 81.4 percent of GDP in the third quarter of
2012, the lowest since 2003 and down from a peak of nearly 98 percent
in 2009. Moreover, payments on mortgage and consumer debt took up about
10.6 percent of household disposable income in the third quarter of
2012, the lowest household debt service ratio since 1993.
Effect of Rising Inequality on Consumption. Some of the recent
patterns in aggregate consumption behavior--including the sluggish
growth in consumer spending relative to previous recoveries--may
reflect the sharp rise in income inequality over the past 30 years.
According to CBO (2012c), after-tax incomes of the top 1 percent of
households rose by more than 155 percent from 1979 to 2009, while
those of median households increased by less than 33 percent. About
one-fifth of this increase in inequality is due to the declining share
of income that goes to labor (Box 2-2). As discussed in the 2012
Economic Report of the President, some research suggests that this rise
in inequality may have reduced aggregate demand, because the highest
income earners typically spend a lower share of their income--at least
over intermediate time horizons--than do other income groups.

Business Fixed Investment

Real business fixed investment grew 4.6 percent during the four
quarters of 2012, after rising 10.2 percent in the four quarters of
2011. Both of its principal components--equipment and software
investment and nonresidential structures investment--contributed to this
slower growth. Investment in equipment and software slowed to 4.6
percent over the four quarters of 2012, down from robust growth of 11.4
percent in 2011. Investment in nonresidential structures increased 4.7
percent, following a 6.9 percent increase in 2011.
Within equipment and software investment, major components such as
industrial equipment, transportation equipment, and
information-processing equipment all posted notably slower growth in
2012 than in 2011. The relatively stable pace of GDP growth during 2011
and 2012 provided little overall stimulus to equipment investment. The
slowing pattern of equipment investment growth may also partially
reflect the reduced pace of bonus depreciation, which had been
available at a 100 percent rate during 2011 but fell to 50 percent in
2012. (Bonus depreciation encourages investment by allowing firms to
write-off equipment purchases immediately, rather than over an extended
period). The American Taxpayer Relief Act (ATRA) extended the 50
percent rate through 2013.
Real investment in nonresidential structures grew 4.7 percent
during the four quarters of 2012, down from 6.9 percent during 2011.
Solid growth in office buildings and electric power plants was
partially offset by a decline in petroleum and natural gas drilling,
which followed strong growth during the preceding two years.
Despite the slower growth of business investment in 2012, the
sector is poised to grow rapidly if demand accelerates because
corporations have ample internal funds (Figure 2-7). Corporate profits
continued to rise through the first three quarters of 2012, exceeding
their pre-recession level, even as a percent of GDP, while corporate
dividends remained at roughly pre-recession levels through the first
three quarters of the year before spiking in the fourth quarter, before
ATRA was passed. As a consequence, corporate cash flow, the sum of
undistributed profits and depreciation that represents the internal
funds that corporations have available for invest�ment, has remained
elevated during the recovery. Cash flow now exceeds investment, an
unusual situation insofar as corporations usually have to borrow funds
to finance their capital spending plans. A large portion of these
investable funds has been channeled to financial investments rather
than to new physical capital, as can be seen by the rising level of
liquid assets held by nonfinancial corporations. Indeed, as of the
third quarter of 2012, nonfinancial corporations held $1.7 trillion of
liquid financial assets.

Box 2-2: Why Is the Labor Share Declining?

The ``labor share'' is the fraction of income that is paid to
workers in wages, bonuses, and other compensation. Income of
self-employed workers is also included in some definitions of labor
income, as it is in the figure below. The labor share in the United
States was remarkably stable in the post-war period until the early
2000s. Since then, it has dropped 5 percentage points. Because capital
income is distributed more unequally than labor income, the decline in
the labor share accounts for some, but not all, of the rise in
inequality. CBO (2011) has estimated that 21 percent of the increase in
inequality from 1979 to 2007 was accounted for by shifts between labor
and other sources of income, with the remain�ing 79 percent accounted
for by rising inequality within capital, business, or labor income.
Nevertheless, the decline in the labor share has adverse implications
for government revenues because wages and salaries are taxed at a
higher rate than other major income sources.
The decline in the labor share is widespread across industries and
across countries. An examination of the United States shows that the
labor share has declined since 2000 in every major private industry
except construction, although about half of the decline is attributable
to manufacturing. Moreover, for 22 other developed economies (weighted
by their GDP converted to dollars at current exchange rates), the labor
share fell from 72 percent in 1980 to 60 percent in 2005.
Proposed explanations for the declining labor share in the United
States and abroad include changes in technology, increasing
globalization, changes in market structure, and the declining
negotiating power of labor. Changes in technology can affect the share
of income going to labor by changing the nature of the labor needed for
production. More specifically, much of the investment made by firms
over the past two decades has been in information technology, and some
economists have suggested that information technology reduces the need
for traditional types of skilled labor (Bound and Johnson 1992; Autor,
Katz, and Krueger 1998). According to this argument, the labor share
has fallen because traditional middle-skill work is being supplanted by
computers, and the marginal product of labor has declined.
Increasing globalization also puts pressure on wages, especially
wages in the production of tradable goods that can be produced in
emerging market countries and some less-developed countries. These
pressures on wages can lead to reductions in the labor share. Changes
in market structure and in the negotiating power of labor could also
lead to a declining labor share. One such change is the decline in
unions and collective bargaining agreements in the United States.

These explanations are neither exhaustive nor mutually exclusive
(OECD 2012). Overall, these changes have moved the distribution of
income towards a winner-take-all society.


Business Inventories

Inventory investment--measured as the change in inventories from
one quarter to the next--is typically an important contributor to the
changes in real GDP during recessions and the early stages of
recoveries. During the recession, inventories fell but by less than
sales, so the ratio of inventories to sales rose; through the first two
years of the recovery, inventories rose less rapidly than sales, and by
the end of 2011, the inventory-sales ratio had returned to its level of
the mid-2000s. With this inventory cycle behind us, real private
nonfarm inventory accumulation in 2012 made only a small, slightly
positive contribution to real GDP growth. Looking ahead, inventory
investment is expected to make only a minor contribution to growth
during 2013.

Government Outlays, Consumption, and Investment

The Federal budget deficit during fiscal year (FY) 2012--which
ended on September 30, 2012--was $1.1 trillion, about $200 billion less
than the

preceding year. As a share of GDP, the deficit fell to 7.0 percent in
FY 2012, down from 8.7 percent in FY 2011.
As measured in the Federal unified budget, Federal receipts rose
6.4 percent in FY 2012 compared with the previous year, reflecting a
3.7 percent increase in individual income tax receipts, a 33.8 percent
increase in corporate tax receipts, and a 3.2 percent increase in
receipts for social insurance. The $61 billion increase in corporate
tax receipts accounted for 42 percent of the rise in overall revenues.
Current dollar values of individual income taxes and social insurance
and retirement receipts have each risen to 97 percent of their FY 2007
levels, while corporate tax receipts were just 65 percent of their
previous high.
Federal outlays declined 1.7 percent in nominal dollars in FY 2012
from FY 2011, falling from 24.1 percent of GDP to 22.8 percent of GDP.
The decline in spending during the fiscal year reflected several
factors, including reduced outlays on unemployment insurance,
Medicaid, and defense. Specifically, fewer individuals received
unemployment benefits, a temporary increase in Federal aid to states
for Medicaid expired, and the number of U.S. Army personnel stationed
in Afghanistan and Iraq was reduced.
During the four quarters of calendar year 2012, the National
Income and Product Accounts measure of real Federal expenditures on
consumption and gross investment (which does not include Federal
transfers to States and individuals) declined 2.8 percent, as a 4.9
percent decline in real defense spending more than offset a 1.5 percent
increase in real nondefense spending.
The Federal deficit as a share of GDP fell for the third
consecutive fiscal year in 2012. The change in this ratio is one
measure of the drag on the economy imposed by fiscal consolidation, and
in FY 2012, this drag was 1.7 percentage points (the difference between
the deficit-GDP ratio of 8.7 percent in FY 2011 and 7.0 percent in FY
2012). Moreover, the drop in the deficit-to-GDP ratio from 10.1 percent
in 2009 to 7.0 percent in 2012 is the largest 3-year decrease since
1949. Looking further ahead, policy changes to be recommended in the FY
2014 Budget will put debt as a share of the economy on a stable path
and place the budget in a fiscally sustainable posi�tion in the 10-year
budget window.

State and Local Governments

Although State and local governments continued to experience
fiscal pressure in 2012, the long contraction in the sector finally
appears to be coming to an end. State and local consumption and
investment (purchases) have shown unprecedented weakness compared with
previous recoveries (Figure 2-8). From the end of the recession in
mid-2009 to the fourth quarter of 2012, real State and local purchases
declined 6.8 percent. By contrast, during the comparable period of
each of the six previous recoveries, real State

and local purchases posted positive growth, averaging an increase of
10.3 percent over the first three and a half years of the recovery.
Nominal State and local government tax receipts increased during the
first three quarters of 2012. Federal support from the Recovery
Act--which helped support State and local governments during 2009 and
2010--phased out during 2011 and 2012. And while the pace of State and
local government job losses eased in 2012, employment in this sector
remained 724,000 jobs below its previous peak as of the end of the
year, with more than 40 percent of the loss in educational services
On the revenue side, State and local tax receipts rose at an
annual rate of 2.6 percent during the first three quarters of 2012, a
bit below the pace during 2011. The slow recovery in State and local
tax revenue reflects in part the effect of lower house prices on
property tax collections. Historically, property taxes have accounted
for about 30 percent of State and local government tax receipts and
are critical to local governments, but property tax receipts have edged
up slowly in the years after the housing bubble burst. Nationwide,
property tax receipts have grown just 11.4 percent over the past five
years, only slightly faster than inflation, compared with 36.0 percent
growth during the preceding five year period from 2002-07. Moreover,
State and local governments are still feeling the effect of the drop in
house prices: because property value assessments lag behind market
valuations, the effect of house prices on property tax receipts
operates with a delay of about three years (Lutz 2008). Although
policymakers in some states have increased the tax rate on assessed
property values to partially offset declines in those values (Lutz,
Molloy, and Shan 2011), local governments have still needed to adjust
spending to make up for the lost revenue. Despite these difficulties,
the recent upturn in house prices suggests that improvement in State
and local government finances is on the horizon. In addition, revenues
from sales and income taxes--which make up about 50 to 60 percent of
State and local tax receipts--have also continued to recover, with
income tax collections up 7.6 percent during the four quarters of 2012,
and sales taxes growing 2.2 percent.
Another factor weighing on State and local government revenues has
been the phase-out of the Recovery Act. After rising notably in 2009
and 2010, Federal grants-in-aid to State and local governments plunged
$82.1 billion in 2011 before stabilizing during 2012. Both the earlier
increase and the recent return to a lower level were largely
attributable to the Recovery Act, which was designed to offer temporary
support to State and local gov�ernments. The portion of Federal
grants-in-aid to the States from Recovery Act programs stood at just
$17.9 billion in 2012, down from a peak of more than $100 billion in
Current State and local government expenditures--which include
transfers to individuals as well as government consumption--rose 2.8
per�cent over the four quarters of 2012, following a 0.2 percent
increase in the previous year. A recent CBO report (CBO 2012b) noted
that the weakness in State and local government spending relative to
previous recoveries could be attributed roughly equally to three
different areas: hiring of employees, purchases of goods and services,
and construction spending. Despite continued spending restraint across
these major components, the operating position of State and local
governments deteriorated to an aggregate deficit of $140 billion by the
third quarter of 2012, on pace for a fifth consecutive year of
operating deficits for the sector.
State and local government employment fell 32,000 during the 12
months of 2012, a much shallower decline than the 286,000 jobs lost in
2011. Nevertheless, employment in the sector remains well below its
peak in 2008. To date, the Administration has taken important steps to
help State and local governments maintain critical services in public
safety and education. In addition to the grants-in-aid components of
the Recovery Act, the Administration established a new fund to support
teaching jobs and extended the enhanced Federal matching formula for
certain social services and medical insurance expenditures. In 2011,
the President proposed additional resources for the teacher job fund
as part of the American Jobs Act, which also would have supported the
modernization of more than 35,000 schools. Although Congress did not
enact this proposal, the President remains committed to supporting
educators and first responders in his second term.

Real Exports and Imports

Compared with previous recessions, real exports experienced a
sharper-than-usual contraction and rebound during 2007-10. This sharp
cyclical decline was partly attributable to the synchronized nature of
the 2007-09 contraction and recovery across nearly all countries, a
collapse and rebound in commodity prices, and foreign consumers'
postponement of purchases of U.S. durable goods, which account for a
large share of tradable goods (Baldwin 2009). Now, with the recent
slowing of world growth, real exports appear to be reverting to their
historical trend (Figure 2-9), growing 1.8 percent during the four
quarters of 2012, after rising 4.3 percent in 2011 and 8.8 percent in
2010. As discussed in Chapter 7, the recent slowing in export growth
appears to have restrained the pace of U.S. manufacturing activity.
Continued export growth will depend, in part, on healthy growth of the
world economy and on exchange rates. The value of the dollar has been
generally increasing since July 2011, in part reflecting increased

international demand for U.S. Treasury bonds in a time of global
financial turmoil and rapidly deteriorating global growth. Changes in
the terms of trade have contributed to the weakening demand for U.S.
goods abroad.
Real imports grew 0.1 percent during the four quarters of 2012,
down from 10.9 percent and 3.5 percent in 2010 and 2011, respectively.
A decline in imports of petroleum products offset a moderate rise in
imports of nonpetroleum goods. Consistent with Houthakker and Magee
(1969), the pattern in real imports parallels, but is sharper than, the
general shape of the contraction and rebound in overall U.S. personal
consumption spending. Because imports tend to be concentrated more in
goods than is overall consumer spending, real imports move more closely
with goods consumption--which is cyclically sensitive--than with total
consumption. In addition, because business equipment investment
includes imported capital goods, real imports track this cyclical
series as well.
Shrinking exports subtracted from real GDP growth in each quarter
of the worst period of the recession from the third quarter of 2008 to
the first quarter of 2009, but real exports have added to real GDP in
every quarter since, except for in the fourth quarter of 2012.

Housing Markets

Housing activity firmed markedly in 2012 and, although the level
of activity remains low by historical standards, the recovery in the
sector finally appears to be gaining momentum. On the production side,
new housing starts increased to an annual rate of 900,000 units by the
fourth quarter of 2012, up from an annual low of 550,000 units in 2009,
and 610,000 units in 2011 (Figure 2-10). Demand for housing has also
increased, with new and existing home sales reaching their highest
levels of the recovery period during 2012. Similarly, inventories of
unsold new homes have fallen to their lowest ever recorded level.
Following large declines from 2007 through 2011, housing prices
bottomed out in early 2012, and rose 8.3 percent over the 12 months of
the year, according to the CoreLogic home price index. Private sector
housing experts expect house prices to appreciate at a 3.0 to 3.5
percent annual pace for the next several years. Because households have
a choice between renting and owning a home, the price of new homes
should increase in tandem with rental costs, at least over long periods
of time. As seen in Figure 2-11, house prices increased to a level
above parity with rents during the mid-2000s but descended to a level
consistent with rents by the end of 2011.

In 1998, the Council of Economic Advisers estimated that the pace
of construction of new housing units and mobile homes that would be
consistent with projected rates of population and household formation
would be 1.64 million units a year over the 10 years from 1996 to 2006.
Relative to this 1996 estimate, the subsequent 10 years through 2006 saw
a period of tremendous overbuilding that led to an excess supply of 2.6
million housing units by 2007 (Figure 2-12). Since then, the very low
levels of new construction effectively allowed the underlying
demographics of household formation to catch up to the supply of
constructed and manufactured homes nationwide by 2011, with some
possible  overshooting in 2012.
Although construction, sales, and prices are finally rising,
progress has been impaired by the substantial stock of vacant homes and
homes still in the foreclosure process; therefore, a recovery in
housing  starts to the annual pace of roughly 1.76 million units
suggested by the demographics of household formation will likely still
take several years to achieve (Masnick, McCue, and Belsky 2010).
Nevertheless, sustained increases in homebuilding should provide a
major impetus to economic growth over the medium term.
Several other factors also appear to be restraining the housing
recovery. First, although mortgage rates are at historically low
levels, approxi�mately 22 percent of current mortgage holders were
underwater (that is, the

amount owed on their mortgage exceeded the market value of their home)
through the third quarter of 2012, impeding their ability to refinance
or sell.
Second, although some tightening of lending standards was
inevitable in the aftermath of the financial crisis, these standards
have not eased by as much as expected this far into the recovery.
According to the Federal Reserve Senior Loan Officer Opinion Survey,
the net percentage of responding banks that have eased their standards
for approving prime residential mortgage loans has been flat since the
beginning of 2011, even though demand for prime residential mortgages
has increased sharply. According to the April 2012 survey, which
included special questions on real estate lending, more than half the
lenders reported they were less likely to originate a mortgage to a
borrower with a credit score of 680 today than in 2006. All told, the
origination of first-lien mortgages to homebuyers now stands at its
lowest level since 1995.
As the President emphasized in the State of the Union, moving
forward with programs to help homeowners with strong payment histories
refinance their homes will provide them with additional liquidity and
will spur consumption. In addition, streamlining regulations associated
with issuing new mortgages will provide creditworthy potential
borrowers the opportunity to purchase homes and will further the
recovery of the housing sector.

Financial Markets

Financial market conditions in the United States continued to
improve, on net, in 2012, reflecting the ongoing economic recovery and
the highly accommodative monetary policies undertaken by the Federal
Reserve. The broad, overall improvement in financial conditions is
consistent with the performance of the Standard and Poor's (S&P) 500
Composite Index, a measure of U.S. equity prices, which rose 14.4
percent over the 12 months of 2012. Measures of market volatility, such
as the Chicago Board Options Exchange Market Volatility Index (also
known as the VIX), were also more subdued in 2012 than they were in
Yields on 10-year Treasury notes averaged 1.7 percent in December
2012, down slightly from 2.0 percent in December 2011. For the year as
a whole, the 10-year yield averaged 1.8 percent, the lowest since at
least 1953 when the Federal Reserve's constant-maturity series began.
Long-term interest rates in the United States were driven even lower
than in 2011 by the relative safety of U.S. issues in the presence of
concern over sovereign debt issues abroad and by the Federal Reserve
System's program to lengthen the maturity of its holdings of U.S.
government securities. With these nominal yields falling to historic
lows, long-term real interest rates (that is, the nominal yield less
expected inflation) also fell. Yields on Treasury Inflation-Protected
Securities, an indicator of real rates, averaged negative 0.5 percent
in 2012 (Figure 2-13).
Credit standards for commercial and industrial loans, as measured
by the Federal Reserve Board's Senior Loan Officer Opinion Survey, have
eased since the financial crisis for firms of all sizes, including
small firms. Data from the Federal Deposit Insurance Corporation also
suggest that the number of loans to small businesses increased in 2012,
after having remained depressed through 2011. Nevertheless, the value
of small-business commercial and industrial loans remains below its
pre-recession level.

Wage and Price Inflation

Core consumer price inflation (the consumer price index excluding
the volatile components of food and energy) was stable from 2011 to
2012, rising 1.9 percent in 2012, and down slightly from a 2.2 percent
year-earlier increase (Figure 2-14). Twelve-month increases in core
consumer prices have fluctuated in the fairly narrow range of 0.6 to
2.3 percent during the past three years. This relative stability is
striking, given that standard Phillips curve models of inflation would
predict sustained disinflationary pressure over this period because of
the considerable slack in labor and product markets.

As is usually the case, the overall, or headline, consumer price
index, including food and energy prices, fluctuated more in 2012 than
did core inflation. Inflation as measured by the overall consumer price
index fell from 3.0 percent during the 12 months of 2011 to 1.7 percent
in 2012, with the decline stemming from lower rates of food and energy
inflation. Energy prices edged up only 0.5 percent during 2012, more
than 6 percentage points below their 2011 pace, and food price
inflation dropped 2.9 percentage points. Data Watch 2-2 discusses one
of the challenges faced by statistical agencies when constructing price
indexes based on statistical samples.

The Recovery in Historical Perspective

Following the worst recession since the Great Depression, the
recovery that began in the third quarter of 2009 has been a long and
difficult one for many Americans. During the recession, 7.5 million
jobs were lost, and real GDP fell by 4.7 percent. To date during the
subsequent recovery, 4.2 million jobs have been added since June 2009,
and real GDP has grown by 7.5 percent. Since the trough in employment
in February 2010, the private sector has grown for 35 straight months
and added over 6.1 million jobs. Real GDP growth in the United States
has exceeded the cumulative growth in the euro area and the United
Kingdom (Figure 1-4) as well as in Japan since the fourth quarter of
2007. Nevertheless, U.S. real GDP growth since the end of the recession
has been less than the average increase in previous postwar recoveries.
From 1960 to 2007, the U.S. economy had seven recessions, and the
average annual rate of growth of real GDP during the 12 quarters
following those recessions was 4.2 percent. In contrast, during the 12
quarters following the trough in the second quarter of 2009, the
average annual rate of growth of real GDP was 2.2 percent. After three
years of recovery, the cumulative growth of real GDP was 6.3 percentage
points lower than its average value for the earlier post-1960
recessions. This shortfall is depicted in Figure 2-15, which shows the
paths of real GDP for the three most recent business cycles (with
cyclical troughs in the first quarter of 1991, the fourth quarter of
2001, and the second quarter of 2009), along with the average path for
U.S. business-cycle recoveries from 1960 through 2007. For each of the
three most recent cycles, the recovery in real GDP has been slower than
the 1960�2007 average. It is worth noting that the most recent recovery
has been stronger than the post-2001 recovery if only private demand is
considered (that is, excluding government purchases). Still, the fact
remains that these three recoveries have been slower than the pre-2007

The reasons underlying the relatively slow pace of the current
recovery have been the subject of considerable research. This research,
discussed in more detail below, reaches three main conclusions. First,
most--perhaps two-thirds, using a central estimate across studies--of
the gap between the 12-quarter growth of GDP after the second quarter
of 2009 and the average 12-quarter growth following previous troughs is
accounted for primarily by changes in the long-term dynamics of the
U.S. labor force and economy, mainly long-term demographic shifts.
These demographic changes also help explain why the 1991 and 2001
recoveries were slower than the post�1960 average. Second, much of the
remaining one-third of the gap can be attributed to the financial
crisis dynamics discussed by Reinhart and Rogoff (2009), Reinhart and
Reinhart (2010), Hall (2010), Woodford (2010), and others. This
research finds that recoveries following financial crises tend to be
slow because of delays in the reemergence of credit and reductions in
consumer spending as households pay down debt or rebuild their savings,
a process referred to as ``deleveraging.'' Third, some unique factors
proved to be particularly important impediments to this recovery, as
discussed previously: the limited effectiveness of standard monetary
policy caused by the zero lower bound on nominal interest rates; the
presence of millions of underwater and foreclosed properties, which has
impaired the recovery of the housing market; and the contraction in
State and local government

Data Watch 2-2: The Effect of Statistical
Sampling on Laspeyres Indexes

The purpose of a price index is to provide a single measure of the
overall rate of change in prices for some set of goods and services,
for example, all purchases made by consumers. If data on all prices
were readily available, the true rate of price increase could be
calculated by weighting the relative increases in the prices for every
item in the bundle using weights that reflect spending on the items,
then combining those weighted price increases to form a price index.
Because it is not possible to collect all prices, however, statistical
agencies collect a sample of prices and use the sample to construct the
price index.
The consequences of using a sample of prices, instead of all
prices, can be significant. To be concrete, consider a Laspeyres price
index, in which inflation is measured as an arithmetic weighted average
of price increases for individual categories of items and the weights
are spending shares measured at the beginning of the interval. In
practice, each item (for example, apples or a haircut) is sold in an
area (such as the Seattle metropolitan region), so the price increase
of interest is an item-area price (the increase in the price of apples
in Seattle from one month to the next). In reality, there are many
item-area prices (one can purchase apples or haircuts at many shops in
Seattle), so a sample of item-area prices is taken, and the sampled
price increases (the increase in the price of apples at a given store,
relative to last month's price at that store) are averaged. Since 1999,
the Bureau of Labor Statistics (BLS) has computed this average of the
sample of price increases within an item-area using the geometric mean.1
If the number of sampled prices for an item-area is large, the
geometric mean of sample price changes will be close to the true
item-area price. But collecting many item-area prices is expensive, so
in many cases only a small number of item-area prices are collected.
When computed using a small sample, the sample geometric mean tends to
overstate the true geometric mean. The extent of this
overstatement--the statistical bias arising from using a small
sample--decreases as the number of prices sampled for an item-area
How large is this finite sample bias? As an example, consider a

1 The geometric mean of two numbers is the square root of their
product. Suppose apple prices are sampled at two stores, one of which
held prices constant and the other increased apple prices by 20
percent. Then the arithmetic mean relative price is (1 + 1.2)/2 = 1.10
(an increase of 10 percent), and the geometric mean is (1x1.2)� =
1.095 (an increase of 9.5 percent). The BLS adopted the geometric mean
in part because its slightly lower increase captures the effect of
shoppers migrating to the store at which apple prices remain constant,
so that from the shopper's perspective the overall price increase is in
fact less than 10 percent.

Laspeyres price index constructed using equal weights (that is, an
index for which all item-areas have the same consumption shares), with
many item-areas and with 10 prices randomly sampled per item-area.
Suppose that the true item-area price increase is zero and the standard
deviation of the price changes (a measure of the dispersion of the
price changes) for sampled goods within each item-area is 10 percentage
points. Then the bias is small: The geometric mean index for each
item-area overstates the price change by only 0.05 percentage point per
period, and under the assumptions made here, this translates into an
upward bias of 0.05 percentage point in the overall Laspeyres index.
But if only 5 items are sampled per item-area, and the standard
deviation of the price changes across stores is a bit larger, say, 15
percentage points, then the bias is larger, and the price change is
overstated by 0.23 percentage point per period. If this bias can be
calculated (as has been done in the simple example laid out here), a
technical correction can be made to the Laspeyres index to eliminate
the bias. At a technical level, this bias arises because the Laspeyres
index is an arithmetic weighted average of the item-area geometric
means. Interestingly, if the geometric means for each item-area are
aggregated to a national index using a weighted geometric mean, as with
a Trnqvist price index, rather than a weighted arithmetic mean, as
with the Laspeyres, the small-sample bias is eliminated, and there is
no need for a technical bias correction. For further reading on
small-sample bias in index numbers, see McClelland and Reinsdorf (1999)
and Bradley (2005).

hiring due to sharply eroded property and sales tax bases. Given the
deep and prolonged effects of financial crises, the cyclical component
of the current recovery would have lagged even further behind the
postwar average were it not for Federal fiscal stimulus--notably
through the Recovery Act (Box 2-3), the temporary payroll tax cut, and
extended unemployment insurance benefits--and for the nonstandard
monetary stimulus provided by the Federal Reserve.

Demographics, Productivity, and Long-Term Economic Growth

A useful starting point for analyzing long-term trends in output is
to note that GDP is the product of two terms: real GDP per worker times
the number of workers. In turn, GDP per worker is the product of real
GDP per hour of labor input--that is, labor productivity--times average
hours per worker. Although average hours per worker have been
declining, the rate of this decline since the mid-1980s has been
relatively small. Thus, variation in the long-run growth rate of GDP
is, to a first approximation, determined by

Box 2-3: Economic Impacts of the American
Recovery and Reinvestment Act

To counter the contraction of aggregate demand in the Great
Recession, Congress passed and President Obama signed into law the
American Recovery and Reinvestment Act (the Recovery Act) in February
2009. The Recovery Act was a major part of the Federal govern�ment's
efforts to reinvigorate the economy through direct fiscal stimulus. The
Recovery Act authorized an estimated $787 billion for purchases of
goods and services by the Federal government, transfers to State and
local governments, payments to individuals, and temporary tax
reductions for individuals and businesses (based on actual outcomes,
the final total exceeded $800 billion).
Numerous studies have examined the success of the Recovery Act in
raising employment and stimulating growth. As is the case with policy
evaluation generally, the methodological challenge is to compare
outcomes from an event that actually happened (implementation of the
Recovery Act) to outcomes from a counterfactual event that did not (no
Recovery Act). One approach is to use a large macroeconometric model or
other statistical techniques to estimate a baseline, non-stimulus
forecast that excludes Recovery Act provisions and a stimulus forecast
that includes them, and then either compare the two forecasts or
compare the actual data to the non-stimulus forecast. Of the studies
employing this method, most estimate that the Recovery Act stimulated
growth. A Congressional Budget Office study (CBO 2012b) estimated that
the Recovery Act boosted the level of GDP by 0.4-1.8 percent in 2009,
0.7-4.1 percent in 2010, 0.4�2.3 percent in 2011, and 0.1�0.8 percent
in 2012, with more than 90 percent of the Recovery Act's budgetary
impact realized by the end of September 2012. The most recent review by
the Council of Economic Advisers (CEA 2013) estimated that the Recovery
Act raised the level of GDP as of the third quarter of 2010 by 2.7
percent, which is roughly in the same range estimated by CBO. A report
by Blinder and Zandi (2010) estimated that the stimulus raised GDP in
2010 by 3.4 percent. Additional reports by IHS Global Insight and
Macroeconomic Advisers provide estimates consistent with these ranges
(as reported in CEA 2013). Estimates based on macroeconometric models
typically do not include the additional benefits of avoiding very high
levels of unemployment, which could be particularly persistent and
exhibit so-called hysteresis; see DeLong and Summers (2012) for
additional discussion.
A different approach to evaluating the Recovery Act is to use
cross-state variation in Recovery Act spending levels to estimate the
effects of the spending, and then to extrapolate these effects to the
full economy.
Wilson (2012) studied state-level variation in Recovery Act spending to
determine its employment effect; he estimated that Recovery Act
spending created 2 million jobs in its first year and 3.4 million by
March 2011, with substantial gains in the construction, manufacturing,
education, and health industries. Conley and Dupor (2012) estimated
that the spending components of the Act created between 82,000 and 1.5
million jobs. Other papers that use state-level variation to estimate
Recovery Act effects on employment include Chodorow-Reich and others
(2012), who investigated the employment effects of the Recovery Act's
aid to states through increased Federal Medicaid matching funds, and
Feyrer and Sacerdote (2011), who considered both total spending and
type of spending; both papers found positive employment effects.
The range of estimates of the effect of the Recovery Act is large,
and research on this topic is ongoing. Surveying the literature,
however, the evidence suggests that the Recovery Act substantially
lessened the impact of the Great Recession by increasing employment and
output in the years immediately following the crisis.

the long-run growth rate of both productivity and the number of
workers.5 The discussion here focuses on the growth of productivity for
nonfarm busi�nesses and the growth of overall payroll employment.
Figure 2-16 shows quarterly growth of nonfarm business
productivity and its cyclically adjusted long-term mean at an annual
rate.6 According to this mean, annual trend productivity growth fell
from 2.6 percent in 1965 to 1.5 percent in 1985, recovered to 2.3
percent in 2005, and then fell to 2.0 percent as of 2010. Despite the
considerable uncertainty and difficulty in distinguishing the trend
from cyclical components given the severity of the recent recession,
this pattern is in line with others in the academic literature. Gordon
(2010) found that trend productivity growth declined from 2.75 percent
in 1962 to 1.25 percent in 1979, then rebounded to 2.45 percent by
2002. Fernald (2012) divided the period since 1973 into three regimes
of average labor productivity growth: 1.5 percent from 1973 to 1997,
3.6 per�cent from 1997 to 2003, and 1.6 percent from 2003 to 2012. The
very strong

5 Because labor productivity is conventionally measured for the nonfarm
business sector, there are additional terms that account for the
difference between the growth of GDP per hour and nonfarm business
output per hour and between nonfarm business hours and total hours.
6 The cyclically adjusted long-term mean, or trend, is estimated using
regression methods with a cyclical component, specifically two leads
and lags of the CBO's unemployment gap, and a flexible trend component.
The flexible trend component is estimated by a smooth weighted average
using a two-sided 15-year moving window, which is truncated at the ends
of the sample.

productivity growth of the late 1990s and early 2000s evident in Figure
2-16 appears, in part, to have been transitory.
Figure 2-17 plots the quarterly growth of total payroll employment
and its cyclically adjusted long-term mean at an annual rate, and
Figure 2-18 plots the quarterly change in employment, measured by the
number of jobs; the method for computing the trends in both figures is
the same as that used to calculate the trend shown in Figure 2-16. The
smoothed mean growth of employment rose from 2.2 percent annually in
1965 to 2.4 percent in 1975 but then declined steadily to 2.0 percent
in 1985 and just 0.8 percent in 2005. The trend in the number of jobs
added remained high through the 1990s, and in fact more jobs were added
in the 1990s than in the 1980s.
The high growth rate of employment in the 1970s reflected the
historic surge of women into the U.S. labor force. The trend decline in
employment growth since the late 1990s has been largely associated with
demographics, in particular the plateauing of female labor force
participation during the late-1990s, the steady multi-decade trend
decline in male labor force participation, the downward trend in youth
labor force participation, and, starting in the 2000s, the entry of
the baby-boom generation into retirement. Demographic trends are
discussed in more detail in Chapter 4. Indeed, the implications of
demographic trends extend beyond the labor

force to include, for example, changes in the patterns of consumption
as the population ages (Box 2-4).
The net effect of the declines in the long-term trends for
productivity and employment has been a fairly steady decline in the
long-run mean growth rate of GDP over the past 50 years. Indeed, the
cyclically adjusted long-term mean growth rate of real GDP fell from
3.7 percent in 1965 to 2.9 percent in 1985 and 2.4 percent in 2005.
This steady slowdown is evident in Figure 2-19, in which real GDP is
plotted along with trend lines estimated using the quarterly data
spanning a full business cycle as dated by the National Bureau of
Economic Research (NBER), measured from one business-cycle peak to the
next.7 The slopes of these trend lines are less steep over time; in
other words, the trend growth of real GDP has been slowing over this
period. Indeed, trend growth has slowed enough that, after every
post-1960 recession, real GDP has never attained the previous trend
growth line that is implied using data from the preceding business
cycle. From this perspective, the slower pace of the current recovery
is not unusual or unexpected.
In a November 2012 study of the current recovery, CBO decomposed
the growth of real GDP in the 12 quarters following a NBER-dated
trough into trend growth plus a cyclical component. It attributed about
two-thirds of the difference between the growth in real GDP in the
current recovery and the average for other recoveries to slow growth in
potential GDP. The CBO study estimated potential real GDP growth--that
is, the maximum sustainable rate of growth of real GDP--using a presumed
economy-wide production function in which potential GDP varied with the
capital stock.
For comparison purposes, the long-term mean growth rate of GDP is
computed here using the methodology of Figures 2-16 and 2-17. The
results from this analysis are summarized in Table 2-2. As reported
earlier, during the first 12 quarters of recoveries from 1960 through
2007, real GDP grew, on average, at an annual rate of 4.2 percent,
whereas during the 12 quarters following the trough in the second
quarter of 2009, the annual rate of GDP growth was 2.2 percent, or 2.1
percentage points below the 1960�2007 aver�age. The estimated trend
growth rate of real GDP since the second quarter of 2009, however, was
2.1 percent, or 1.1 percentage points below the average trend growth
during the 1960-2007 recoveries (3.2 percent). Thus, of the 2.1
percentage points of slower-than-average growth in this recovery, fully

7 The cycle starting with the peak in the first quarter of 1980 lasted
only six quarters. Because it is not meaningful to estimate trends
using only six quarterly observations, the cycles for the first quarter
of 1980 and the third quarter of 1981 are merged for the trend
estimates in Figure 2-19.

1.1 percentage points, or 53 percent, can be attributed to the overall
trend slowdown in real GDP growth over the past 50 years.8
The 1991 and 2001 recoveries also exhibited slower than average
growth in real GDP (Kliesen 2003; Berger 2011; Bachmann 2011). As can
be seen in Table 2-2, the slowdown in trend growth accounted for less
than one-fifth of the relatively slower growth in real GDP following
the 1991 recession (-0.2 percentage point of the gap of -1.1 percentage
points). In contrast, slightly more than one-third of the relatively
slower growth following the 2001 recession was attributable to the
slowing of long-term real GDP growth (-0.5 percentage point of the gap
of -1.3 percentage points).
Stock and Watson (2012) also examined reasons why the current
expansion has been slower than previous postwar recoveries. They
focused on the first eight quarters of the recovery and estimated that
80 percent of the slower growth in real GDP, relative to the post-1960
average for recov�eries, reflected a slowdown in the long-term trend
growth rate rather than cyclical factors.

8 This calculation includes the 12 quarters after all troughs, so that
the 1980 and 1982 recoveries overlap. Alternatively, if the 12 quarters
following the trough in the fourth quarter of 1982 are dropped, 63
percent of the slower than average growth in real GDP is attributable
to a slowdown in trend growth. If instead the 12 quarters following the
trough in the third quarter of 1980 are dropped, 47 percent of the
slower growth in real GDP is attributable to a slowdown in trend

Box 2-4: Implications of Demographic Trends
for Household Consumption

The aging of the U.S. population has two implications for patterns
of consumption. First, people purchase different things at different
ages; for example, younger households spend more on child care services
and clothing, while older households spend relatively more on health
care. Second, empirical research suggests that families' total amount
of spending changes over time as priorities evolve. Because the age
distribution of the population will change over the coming decade as
the baby boom generation moves into retirement, these changes in
household-level consumption will lead to aggregate changes in the
types of goods consumed and, potentially, to changes in the fraction of
income spent.
One way to forecast how demographic changes will affect
consumption is to use data on a sample of households today to estimate
average household consumption within spending categories (clothing,
health care, and so on), for each subset of the population defined by
age, race, sex, and ethnicity of the household head. Then, one can
aggregate these averages using the projected future population for each
subset to produce an overall estimate for all households. The Council
of Economic Advisers undertook this exercise using consumption data
from the Consumer Expenditure Survey and demographic projections from
the Census Bureau. As the figure below indicates, demographic changes
suggest that a greater share of household income will be spent on
health care and housing, and a reduced share on education. In
percentage terms, however, these changes are likely to be small.
Households' total consumption also varies over their lifetime. In
Milton Friedman's (1957) permanent income hypothesis model of
consumption, individuals smooth consumption to match their lifetime
income, but doing so requires the ability to borrow against future
income, as well as considerable planning and discipline. As an
empirical matter, on average, household consumption rises as children
grow up and then declines as parents enter into retirement (Attanasio
et al 1999; Fernandez-Villaverde and Krueger 2007; Bullard and
Feigenbaum 2007).1 Consistent with this research, CEA projects that the
aging population will lead average household consumption to decline
over the next decade, with an implied reduction in the growth rate of
consumer spending of perhaps 0.1 percentage point a year, relative to a
benchmark in which demographics are held constant.

1 One reason for the decline in consumption upon retirement, at least
for some households, is reduced work-related spending such as commuting
costs and uniforms, which are counted as consumption expenditures, but
such declining work-related expenses do not fully account for this

Many factors other than demographics will also influence future
consumer spending. These factors include technological improvements,
changes in income and wealth, and changes in the composition of
households within demographic groups. In addition, changes in relative
prices will affect the composition of spending. For example, if the
price of health care increases relative to other areas, and if the
demand for health care is insensitive to its price, then the share of
spending on health care might be larger than these projections suggest.


In summary, these estimates of the share of the relatively slower
growth in real GDP during this recovery which is attributable to a
slowdown in long-term trends range from 53 percent, shown in Table 2-2,
to 80 percent according to Stock and Watson (2012). This fairly wide
range of estimates reflects both inherent difficulties in calculating
trend growth rates and conceptual differences among these approaches.9
Taken together, however, these studies suggest that most of the
relatively slower growth in real GDP during the current
recovery--two-thirds, using the CBO (2012d) estimate, which is also the
midpoint of these estimates--has been attributable to the slowdown in
long-term trend growth, which, in turn, has been driven largely by
demographic changes in the U.S. workforce.

Reasons for the Slower Cyclical Component

If two-thirds of the slower growth in real GDP during the current
recovery relative to growth in previous postwar recessions is
attributable to the slowdown in underlying long-term trends, then the
remaining one-third can be attributed to cyclical factors that are
specific to this recovery. This section summarizes four complementary
attempts to quantify those cyclical factors: the 2012 CBO study
discussed above, an analysis undertaken here of the sources of forecast
errors during the recovery, work done on this question by the Federal
Reserve as reported by Bernanke (2012b) and Yellen (2013), and the
study by Stock and Watson (2012).
The CBO (2012d) study approaches the question of why the cyclical
part of this recovery has been relatively slow by identifying those
components of GDP that have exhibited unusually slow growth relative to
their cyclical pattern. In decreasing order of importance, CBO found
that the cyclical contributions to GDP of State and local government
purchases, Federal government purchases (primarily defense spending),
residential investment, and consumer spending were all weaker than
their respective historical averages during the first 12 quarters of
this recovery. In turn, CBO attributed the weakness in these components
to several underlying factors. For instance, the CBO study highlighted
the extraordinary weakness in housing markets during the current
recovery. CBO associated the sharp

9 In CBO's framework, the increase in long-term unemployment associated
with the recession could result in skill deterioration and thereby a
decline in potential GDP growth; this general point is also made by
Federal Reserve Chairman Ben Bernanke (Bernanke 2012b). Because such
declines in potential GDP are an indirect result of the recession, they
may be better understood as cyclical rather than long-term trends. The
trend estimates in Table 2-2 and in Stock and Watson (2012) are instead
based on long-term weighted moving averages; because the resulting
estimates are comparable with CBO's, one can infer that this further
distinction of a cyclical change in the growth rate of potential GDP is
secondary to the long-term demographic and technological trends that
drive the growth slowdown.

fall in house prices with reductions in State and local property tax
revenues and the persistent glut of vacant and foreclosed homes with
the weakness in residential construction. Similarly, CBO noted that, in
contrast to previous postwar recoveries, the ability of monetary policy
to spur economic activity has been constrained by the zero lower bound
on the Federal Reserve's main policy interest rate during this
expansion. The CBO analysis also pointed to low consumer confidence and
heightened uncertainty as additional factors that have restrained
aggregate demand since the second quarter of 2009.
A second approach to the question of why the cyclical component of
this recovery has been slower than that of the postwar average is to
examine whether the expansion has been hindered by unexpected events
and forces. Specifically, this approach contrasts the actual, realized
values for each com�ponent of GDP from the corresponding estimates that
were forecast at the start of the recovery. Whereas CBO's approach
identifies which components of GDP grew more slowly than their
historical average, the approach used here is to identify the
components that grew either more slowly or more rapidly than was
forecast, thereby identifying the unexpected, or unforecast, sources of
the slow growth.
Implementing this method of forecast error analysis requires a
quantitative model of the U.S. economy. The one used here is developed
and maintained by Macroeconomic Advisers (MA). This model is used to
decompose the Administration's economic forecast for the FY 2011
Budget, which was made in November 2009. The MA model uses quarterly
data to forecast hundreds of macroeconomic variables. By partitioning
the variables into groups, it is possible to see how the forecast
errors for each group contributed to the forecast errors for GDP. The
variables were divided into five categories: international (foreign
GDP, exchange rates, oil prices), fiscal (both Federal and State and
local), financial and monetary (financial prices, house prices,
monetary indicators, credit flows), housing activity, and other.
That Administration forecast overpredicted output growth by a
small amount in 2010 and by larger amounts in 2011 and the first half
of 2012; in this sense, the recovery was slower than expected. The
forecast error decomposition sheds light on the sources of this
unexpectedly slow recovery. During the first part of the recovery, the
housing sector was weaker than anticipated, and this unexpected
weakness more than accounts for the total GDP forecast error in 2010.
Early in the recovery, financial and monetary factors buoyed economic
activity relative to the forecast, presumably because the forecast did
not fully capture the stimulative effect of nonstandard monetary
policy, which was unprecedented and thus difficult to incorporate
quantitatively into the forecast. Moving farther out in the forecast,
however, the outlook for consumption turned overly optimistic, possibly
reflecting an underestimation of the degree of deleveraging as
households reduced the amount of new debt they took on and paid down
existing debt. This shift in the consumption outlook explains a
substantial part of the overall forecast error for both 2011 as well as
the first half of 2012. Finally, deteriorating international
conditions, largely owing to events unfolding in Europe, added further
unanticipated drag in 2011 and especially in the first half of 2012.
These results complement Chairman Bernanke's (2012b) and Vice
Chair Yellen's (2013) analyses of the relatively slow growth in the
cyclical component of GDP during this recovery. In particular,
Chairman Bernanke pointed to unexpected headwinds from the prolonged
recovery of the housing sector, the lingering effects of the financial
crisis, and the fiscal and financial problems in Europe. Yellen also
noted the restraint on consumer spending from the large loss of wealth
during the recession. Both emphasized the unexpectedly large declines
in the State and local government sector. Indeed, Yellen estimates
that, once the drag from the State and local government sector is
included, the net fiscal stimulus to the economy was less in the
current recovery than it was on average for prior postwar recoveries.
Stock and Watson (2012) also addressed the question of why the
cyclical component of the recovery has been slower than the postwar
average. In contrast to the two approaches discussed above, Stock and
Watson focused on the forecasts of eight-quarter GDP growth from the
vantage point of the trough. They found that these forecasts predicted
slower-than-average cyclical growth during this expansion. These slow
growth forecasts stem from the shocks that produced the recession,
which they identify as primarily financial factors (such as borrowing
constraints) and uncertainty. Thus, the Stock and Watson analysis is
consistent with the Reinhart and Rogoff (2009) view that recoveries
following financial recessions typically exhibit slower growth than
those following other kinds of recessions. In contrast to Stock and
Watson's approach, Hall (2012) used a stylized macroeconomic model to
distinguish between the deleveraging effect of cutting back on
consumption to rebuild wealth and the liquidity effect of higher
borrowing costs, which would arise from tightened lending standards. He
concluded that both effects were important during the recession, but
that the deleveraging effect was short-lived, whereas the liquidity
effect has been more persistent and continues to restrain investment
and to contribute to the slow cyclical component of GDP.
Although the CBO analysis, the forecast error decomposition, the
analyses by Bernanke and by Yellen, the study by Stock and Watson, and
the study by Hall produced different numerical estimates of the causes
of the relatively slow recovery, these analyses point to a common
understanding of why the cyclical component of the current expansion
was slow relative to previous recessions: a financial crisis that led
to reductions in the ability of households and small businesses to
borrow, spend, and invest; a weak recovery of the housing sector as a
result of the excess inventory of vacant, foreclosed, and distressed
properties; a decline in State and local spending and employment;
monetary policy restrained by the zero lower bound on the Federal
Reserve's main policy interest rate; and in more recent stages of the
recovery, the detrimental effects of a global slowdown on U.S. economic
activity. Against all of these headwinds, the stimulus from Federal
fiscal policy actions and aggressive unconventional monetary policy
contributed positively to the cyclical component of the recovery.

Outlook for 2013 and Beyond

The Administration's economic forecast was finalized in
mid-November 2012, a schedule that is dictated by its role in
supporting the Administration's outlook for the FY 2014 Budget, and
will be released later this year in conjunction with the Budget.
Consensus-based forecasts--that is, forecasts that combine
multiple, survey-based individual forecasts (e.g., the mean or
median)--typically outperform the constituent individual private
forecasters' forecasts of macroeconomic variables such as GDP and the
unemployment rate (Clemen 1989; Aiolfi, Capistran, and Timmerman 2011).
Consensus forecasts are thus worth following. In February 2013 the
Blue Chip consensus of professional forecasters projected that real
GDP would increase 2.4 percent over the four quarters of 2013, faster
than the 1.6 percent gain recorded in 2012. The Philadelphia Federal
Reserve Bank's Survey of Professional Forecasters (SPF) also projected
a 2.4 percent increase in 2013. For 2014, the Blue Chip consensus and
the SPF consensus forecast that the economy will continue to strengthen
and that year-over-year real GDP growth will increase to a 2.8 percent
Looking further ahead, the Survey of Professional Forecasters
expects year-over-year growth will pick up to a 2.9 percent pace in
2015 and a 3.0 percent pace in 2016. With these rates of growth, the
unemployment rate, which was 7.8 percent during the fourth quarter of
2012, is projected to edge down slowly to 6.3 percent in 2016.
Importantly, most private sector forecasts reflected in the
consensus forecast have not incorporated an effect for the
across-the-board budget cuts, known as sequestration, which took effect
on March 1.10 These cuts will severely reduce both Federal defense and
nondefense discretionary spending, with ripple effects throughout the
economy. The Congressional Budget Office (2013) and Macroeconomic
Advisers (2013) have estimated that, if sequestration were to remain in
effect for the rest of the calendar year, it would reduce real GDP
growth by 0.6 percentage point during the four quarters of 2013,
relative to its path without the sequester. Moody's Analytics (2013)
has estimated a reduction in real GDP growth by 0.5 percentage point.
Additionally, CBO (2013) has estimated that sequestration would
lead to the loss of 750,000 lost jobs due to the sequester by the end
of 2013 compared with a path without sequestration.11 From this
perspective, by the end of this year sequestration would set back the
recovery by four to five months at a time when the unemployment rate
remains unacceptably high. As President Obama has stated, ``The longer
these cuts remain in place, the greater the damage to our economy--a
slow grind that will intensify with every passing day.''


While much work remains, the economy is healing and moving in the
right direction. The permanent extension of middle-class tax cuts and
the increase in rates on the highest-income taxpayers through the
enactment of the American Taxpayer Relief Act resolved the uncertainty
about future tax rates that overshadowed the economy in 2012 and helped
move the U.S. budget toward a more sustainable course. Some of the
other headwinds that have restrained the economy during the recovery
are also easing, most

10 In February, 77 percent of Blue Chip panelists reported that their
forecasts did not reflect the effects of full sequestration.
11 The Bipartisan Policy Center (2012) estimates that over two years
the effect would be 1 million jobs lost compared with the
no-sequestration alternative.

notably in the housing sector. While risks remain, these indicators
suggest a continued strengthening of the recovery, which in turn
provides an increasingly resilient framework for continued progress
toward fiscal sustainability and a more durable economy that works for
the broad middle class.