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Third Quarter 2016
Volume 1, Issue 3

All Layoffs Are Not Created Equal
The Free-Banking Era: A Lesson for Today?
Banking Trends
Research Update

INSIDE
ISSN: 0007-7011

THIRD QUARTER 2016

Economic Insights is published four times

All Layoffs Are Not Created Equal		1

a year by the Research Department of the
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research-and-data/publications/economic-

More layoffs are intended to be temporary than conventional measures would
suggest. Shigeru Fujita explains how this undercounting occurs and its
surprising implications for today’s problem of long-term unemployment.

The Free-Banking Era: A Lesson for Today?

9

Reaching back to a volatile era in U.S. banking history, Daniel Sanches finds
insight for today’s challenge of ensuring a stable banking system — though
perhaps not the lesson one might expect.

insights.
The Federal Reserve Bank of Philadelphia
helps formulate and implement monetary

Banking Trends:
The Growing Role of CRE Lending

15

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together with the U.S. Federal Reserve

Commercial real estate has grown dramatically as a share of U.S. economic
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and Ryan Johnston provide a primer. First in a series.

Board of Governors, make up the Federal
Reserve System. The Philadelphia Fed
serves eastern Pennsylvania, southern New

Research Update

22

Jersey, and Delaware.

Abstracts of the latest working papers produced by the Federal Reserve Bank
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All Layoffs Are Not Created Equal
U.S. firms use temporary versus permanent layoffs more often than it might appear — a finding
that may suggest a different focus for labor market policy.
BY SHIGERU FUJITA

Finding any new job takes time and resources. Finding
the right job is especially difficult. For workers and employers alike, it is costly to determine whether they will strike a
good match regarding pay, location, schedule, skills, work
environment, and so on. These costs hamper not only individual workers and businesses but also the wider economy.
The greater the amount of search friction, the greater the extent of mismatch across the job market and the less efficiently labor is used throughout the economy, raising unemployment and lowering labor productivity.
An exception to this problem occurs when a worker is
rehired by the same firm for which he or she worked before.
For example, when a manufacturing plant is closed for retooling, as automakers typically do for a couple weeks in July,
workers are let go temporarily and are rehired when the retooling is completed. In such cases, workers and firms know
in advance what to expect from each other, and thus the
usual problem of mismatch, which represents the difficulty of
forming a new employment relationship, becomes moot.
The prevailing view is that temporary layoffs are largely
a thing of the past and that their use is limited to a small
number of industries such as durable goods manufacturing
and construction. Research has indeed suggested that their
use has diminished along with manufacturing jobs since the
mid-1980s.1
In this article, however, I will show that temporary layoffs and recalls actually remain surprisingly common, even
outside manufacturing and construction. Their prevalence
matters because, as we will see, failing to account for them
masks the true extent of mismatch in the labor market. In
particular, their continued pervasive use raises questions

about how much of the lingering unemployment after the
Great Recession has actually been due not to that severe
cyclical downturn but to a deeper structural increase in labor
market mismatch. This distinction is important, because
structural and cyclical unemployment call for quite different
policy actions.
PERMANENT VERSUS TEMPORARY LAYOFFS

When layoffs spike during and after a recession, the
natural focus is on the total number of jobs lost.2 However,
for both individuals and the economy at large, the ramifications are quite different depending on whether layoffs are
temporary or permanent.
As the term implies, a permanent layoff is one in which
the worker has no prospect of returning to that job. A permanent layoff is generally much more costly to the worker.
It takes much more time to find a new job compared with
the length of a typical temporary layoff. Landing a new
job may also require a change in occupation. Given that
workers’ human capital is often tied to their occupational
tenure, switching to a different occupation tends to be accompanied by a large drop in wages.3 In my Business Review
article with Vilas Rao, we studied the experience of workers
who lost their jobs during the
2001 recession and found that
Shigeru Fujita is an
those who switched to a differeconomic advisor and
ent occupation suffered much
economist at the Federal
Reserve Bank of Philadelphia.
larger declines in their wages
The views expressed in this
than those who managed to stay
article are not necessarily
those of the Federal Reserve.
in the same occupation.

Third Quarter 2016 | Federal R eserve Bank of Philadelphia R esearch Department | 1

Workers on temporary layoffs are defined — in the
Census Bureau’s Current Population Survey (CPS) of households, from which the Bureau of Labor Statistics derives the
official unemployment rate — as those who expect to be rehired by the same employer within six months or have been
given an expected recall date. Note that normally, there are
two qualifiers that define unemployment: joblessness and an
active job search. However, workers on temporary layoffs are
exceptions to this definition. Although these workers may
not be actively searching for jobs, given that they expect to
return to their previous employer, they are still counted as
officially unemployed.
In my study with Giuseppe Moscarini, we find that
those who are recalled earn about the same income as
before, whereas those hired elsewhere typically accept a
significantly lower wage than they had earned before they
were laid off. This finding is consistent with the point made
above that occupation switchers experience significant wage
losses. The idea is that wages drop when jobless workers
cannot find jobs where their skills and experience are as
valued as they had been at their previous jobs and so they
reluctantly accept jobs where their skills and experience are
not valued as much. Moreover, a drop in pay is especially
likely when a worker is hired at a new job after a long spell
of unemployment.
Workers on temporary layoffs constitute a significantly
smaller share of the labor force than those on permanent
layoffs (Figure 1). Likewise, among the unemployed, temporarily laid-off workers make up a small slice: In 2015,

37 percent of the unemployed had been let go permanently
— what the Labor Department calls permanent job losers
— whereas 11 percent had been temporarily laid off. (The
remaining 52 percent were counted as unemployed because
they were looking for work either after quitting their jobs or
after being out of the labor force altogether.)4 Thus, within
the group of job losers — the sum of permanent job losers
and those on temporary layoffs — roughly 20 percent had
been temporarily laid off. While one-fifth is a nontrivial
share of total layoffs, it is relatively small. Moreover, this
share had been higher, at around 30 percent, in the 1970s
and 1980s. This declining share of temporary layoffs gives
an impression that the role of temporary layoffs in the labor
market has decreased over time.
However, note that this small share of temporary layoffs is calculated among the pool, or stock, of unemployed
workers at a given point in time. It underestimates how
frequently firms use temporary layoffs to adjust the size of
their workforces. When we compute the share of temporary
layoffs among the flow of workers moving from employment
to unemployment over the course of a month, we discover
that the share is much larger. The share in the flow, instead
of the stock, is a more appropriate measure to gauge how
frequently firms actually use temporary layoffs relative to
permanent layoffs. In the 1980s, almost half of total layoffs
were actually temporary layoffs (Figure 2). Moreover, while
the use of temporary layoffs indeed declined over time, they
still made up more than 40 percent of total layoffs in the
2000s and thus are by no means unimportant.

FIGURE 1

FIGURE 2

Temporary Layoffs Seemingly Diminished
Stock of those on layoff as shares of labor force.

Temporary Layoffs Still Frequently Used
Composition of layoff flows.

Percent

Percent

6

60

5

50

4

40

Permanent

3

Temporary

48%

Permanent
57%

55%

52%
45%

43%

30

2

20

Temporary

1

10

0

0

1976

1982

1988

1994

2000

Source: Bureau of Labor Statistics via Haver Analytics.

2006

2012

1980s

1990s

2000s

Sources: Bureau of Labor Statistics Current Population Survey microdata and
author’s calculations.
Note: Permanent job losers include those who completed temporary jobs.

2 | Federal R eserve Bank of Philadelphia R esearch Department | Third Quarter 2016

The use of temporary layoffs is not only frequent but
also fairly widespread among types of workplaces. When we
look at the flow by industry, we see that the use of temporary
layoffs is hardly limited to manufacturing and construction
(Figure 3). In fact, those two sectors together make up only 37
percent of the overall flow of temporary layoffs. Sixty percent
of temporary layoffs stem from various service industries.5

FIGURE 4

Longer Search Getting Even Longer

Job-finding rates following temporary vs. permanent layoffs.
Percent
60
50

Temporary

40
FIGURE 3

30

Use of Temporary Layoffs Is Widespread

20

Temporary layoffs as shares of total layoff flows.

10

Other services 35%
Construction 25%

Trends

Permanent

0
1978 1982 1986 1990 1994 1998 2002 2006 2010 2014
Sources: Bureau of Labor Statistics Current Population Survey and author’s calculations.
Notes: Expressed as annual averages of monthly rates. Black lines represent third-order
polynomial time trends. Permanent job losers include those who completed temporary jobs.

Education 16%
Manufacturing 12%
Retail/wholesale 8.2%
Agriculture 4.4%
Sources: Bureau of Labor Statistics Current Population Survey microdata and
author’s calculations.

This widespread use raises a question: Why is the share
of temporarily laid-off workers in the stock of unemployed
workers smaller than their share of the separation flow
would suggest? The reason is that those on temporary layoffs
are rehired quickly and thus remain in the unemployment
pool only a short time, while those who are laid off with no
prospect of being recalled tend to spend much more time
looking for new jobs. (See A Tale of Two Types of Layoffs on
page 4.) So, if one looks at the composition of the stock of
unemployed workers at any moment in time, the share of
temporary layoffs will be smaller than what one would expect from the relatively high incidence of furloughs.
This point is verified by the big difference in the jobfinding rates for the two groups of workers (Figure 4). The
job-finding rate for permanent job losers is computed by
dividing the flow of permanent job losers who find a job
in each month by the stock of permanent job losers in the
previous month. The job-finding rate for those on temporary layoffs is calculated similarly. The latter is clearly much
higher than the former. The job-finding rate for those on
temporary layoffs is roughly 50 percent per month. That
means that, on average, half of those who lose their jobs this

month will be reemployed next month. In contrast, permanently laid-off workers find jobs at a much slower pace. This
difference in the rate of finding employment is the reason
behind the small share of temporary layoffs in the stock of
unemployment. Given this large difference in the job-finding rates between the two groups of unemployed workers,
the stock measures do not capture the actual incidence of
temporary layoffs.
EVEN MANY ‘PERMANENT’ LAYOFFS END IN RECALLS

Note that job-finding rates can tell us only how fast
workers are transitioning from unemployment to employment. They do not address two presumptions — one, that
the job-finding rate for those on temporary layoffs measures
the rate at which those workers return to the same employer,
and two, that the job-finding rate for permanent job losers
captures the rate at which they find new jobs. However,
these presumptions are not necessarily correct. The CPS
does not tell us whether the worker is returning to the same
job or finding a new job.6 So in order to know just how prevalent recalls are, we need to ask: Are those on temporary
layoffs indeed rehired by the same firm? And how often do
those who are not on temporary layoffs end up being rehired
by the same firm?
Moscarini and I looked at this issue using an alternative to the CPS data and found that more than 85 percent
of those on temporary layoffs are indeed rehired. Of course,
it is not surprising that not all workers on temporary layoffs

Third Quarter 2016 | Federal R eserve Bank of Philadelphia R esearch Department | 3

A Tale of Two Types of Layoffs
Imagine a mammoth skyscraper that houses every employer
and every worker. In one big room hangs a sign marked
Unemployment. For simplicity, imagine that the only way into the
room is through a door marked Layoffs and the only way out is
through a door marked Hiring.
As people enter the room, a monitor counts them on a clipboard
marked Layoff Flows. He also hands them T-shirts — green if
their company told them it expects to call them back to work by
such-and-such a date, which the entrance monitor records as a
Temporary Layoff, and blue if they have no prospect of returning
to their old job, which the monitor records as a Permanent Layoff.
As people leave (the sooner the better, everyone agrees), an
exit monitor counts them on a clipboard marked Hiring Flows.
He notes how many weeks they’ve spent in the room, which he
records under Duration of Unemployment, and whether they’re
wearing green or blue shirts.
On a set day every month, the building doorman counts the
number of people inside the whole building, including those in the
Unemployment room, and calls that the Labor Force (he ignores
flows into and out of the Labor Force). At some point that same
day, everyone who happens to be in the Unemployment room
poses for a group photo. The photographer counts the number of
people in the picture and calls that the Stock of Unemployment.
She then compares the Stock of Unemployment with the Labor
Force and calls the result the Unemployment Rate.
Also that day, the room monitors compare notes. First, the
entrance monitor compares that month’s Layoff Flow with the
Stock of Employment and calls that number the Separation Rate.
Then the exit monitor compares that month’s Hiring Flow with
the prior month’s Stock of Unemployment and calls the result the
Job-Finding Rate.

are recalled. For example, a furloughed worker in the meantime might land a job with a different employer. What was
more interesting was our finding that even those who did
not expect to be recalled sometimes returned to the same
employer. Specifically, we found that about 15 to 20 percent
of those who did not expect to be recalled were actually rehired by the same employer. Overall, about 40 percent of all
laid-off workers are recalled.
The pervasiveness of recalls highlights the importance
of relationship capital, or attachment, in the workplace. Even
when a firm finds it necessary to let some of its workers go,
it has a strong incentive to rehire those same people when

Sometimes the room gets crowded. Occasionally it stays that way
for months. The entrance monitor is usually the first to predict a
logjam. If the Layoff Flow increases sharply, he knows to give the
exit monitor a heads-up that the Hiring Flow may soon slow down.
And whenever the entrance monitor starts seeing the Layoff Flow
slow, he alerts the exit monitor that the Hiring Flow might be
about to rise.
Over the years, the monitors notice something else: People are
generally spending more time in the room than they used to. Their
records confirm that the average Duration of Unemployment is
longer whether the room is packed or nearly empty.
Curious, they dig deeper. Looking through past photos of the
Stock of Unemployment, the monitors see more blue than
green shirts with each passing year. Temporary Layoffs must be
falling as a share of overall Layoff Flows. But when the entrance
monitor checks his records, he discovers he’s giving out the same
proportions of green and blue shirts these days as always. So
Temporary Layoffs are just as common now as in the past. How
could this be?
The answer comes in the Job-Finding Rate breakdown. Workers
wearing green shirts always leave sooner than those wearing blue
shirts, especially when the overall Hiring Flow slows down. But
in recent years the share of people leaving wearing blue shirts
has been shrinking. As a result, the proportion of blue shirts in
the room on any given day has risen over time and the overall
Duration of Unemployment has lengthened.
Now it’s clear: The Stock of Unemployment snapshot has been
giving an incomplete picture of Temporary Layoffs. Because
they’re as common as ever but the average time in Unemployment
is longer, then anyone on a Permanent Layoff faces a greater
chance than before of a prolonged spell in Unemployment.

business picks up, given that hiring and training new workers would be much more costly.
CYCLICALITY OF TEMPORARY LAYOFFS AND REHIRING

We saw that temporary layoffs account for a significant
share of the flow of workers into and out of unemployment.
Does their share change much as the economy cycles in
and out of recessions and expansions? We can follow what
happens to the hiring flows from the pool of temporarily
laid-off workers as a share of total hiring from the overall
unemployment pool (Figure 5).7 One can see that the share

4 | Federal R eserve Bank of Philadelphia R esearch Department | Third Quarter 2016

2000 (Figure 4). The opposite side of the same phenomenon
is that the median duration of unemployment for permanent
job losers has been on an upward trend over the same period,
whereas that of temporarily laid-off workers has remained
very low, including during the Great Recession (Figure 6). Recall that a permanent layoff is much more costly for a worker
than a temporary layoff, but the divergent trends in jobfinding rates imply that the relative cost of a permanent layoff
has become even bigger in the past 15 years. In other words,
maintaining an attachment to a job and avoiding a permanent layoff have become even more important.

FIGURE 5

Recalls a Larger Share of Recession Hires
Temporarily laid-off share among all unemployed hired.
Percent
35
30
25
20
15
10
5
0

FIGURE 6

1976 1980 1984 1988 1992 1996 2000 2004 2008 2012

Permanent Layoffs Taking Bigger Toll
Median duration of unemployment following layoff.

Source: Bureau of Labor Statistics Current Population Survey microdata.

Weeks

tends to increase during economic downturns, indicated by
the shaded areas, and thus is countercyclical: In a recession,
recalls make up a larger share of the limited hiring that does
occur. So, while the pace of hiring, whether recalls or new
hires, slows down in economic downturns, new hires decline
more and are slower to recover. This pattern was particularly strong during the Great Recession.
This pattern makes sense because creating a new position is more costly, and firms do so only when they are confident about the strength of the economy. By contrast, firms
use temporary layoffs and recalls because of temporary,
often seasonal, changes in demand for their products and
services, so their use of recalls is less influenced by whether
the economy is in a recession.
IMPLICATIONS FOR STRUCTURAL UNEMPLOYMENT

As we saw in Figure 1, the share of temporary layoffs in
the unemployment pool has been falling over time. The flip
side of this trend is that the share of permanent job losers in
the unemployment pool has been rising. In contrast, temporary layoffs as a share of total layoff flows have remained
surprisingly high, despite some declines in recent years
(Figure 2). What do these conflicting trends for the stock
and flow imply? They imply that finding a new job following a permanent layoff has become more and more difficult
over time. In fact, the job-finding rate for temporary layoffs
has always been very high and its trend is flat, whereas the
job-finding rate for permanently laid-off workers has been on
a downward trend for the past 15 years after peaking around

35
30
25
20

Permanent

15

Trends

10
5

Temporary

0
1976 1980 1984 1988 1992 1996 2000 2004 2008 2012
Sources: Bureau of Labor Statistics Current Population Survey and author’s calculations.
Notes: Expressed as annual averages of monthly data. Black lines represent third-order
polynomial time trends. Permanent job losers include those who completed temporary jobs.

Remember also that the post-Great Recession labor
market has been characterized by a higher share of people
caught in long-term unemployment.8 The share of those
who are unemployed more than six months reached 45 percent in 2010 and remained stubbornly high for an extended
period. Although there is no doubt that the Great Recession played a prominent role in this phenomenon, the above
analysis also suggests that the underlying trend had actually
started much earlier, about 15 years ago. And it has been
driven mostly by the longer duration of unemployment experienced by permanent job losers.
A more formal statistical analysis of the overall jobfinding rate over time reached a similar conclusion. By extracting the structural (or trend) component from fluctuations in the job-finding rate without distinguishing between
temporary and permanent layoffs, Murat Tasci found that

Third Quarter 2016 | Federal R eserve Bank of Philadelphia R esearch Department | 5

the trend component of the job-finding rate has been declining for the past 15 years or so.9
GAUGING MISMATCH IN THE LABOR MARKET

Why is it taking longer for permanently laid-off workers
to find new jobs? One possible explanation is greater labor
market mismatch. For instance, skill mismatch arises when
firms cannot find workers with certain skills, even when
jobseekers are plentiful. Geographic mismatch arises when
there is a lack of suitable workers in a firm’s location, even
though qualified workers are located elsewhere.10 Identifying which forms of mismatch are affecting today’s labor
market is beyond the scope of this article, but a simple way
of measuring the extent of overall mismatch is to estimate
the matching function. The matching function captures the
statistical relationship between the job-finding rate and labor market tightness, which is defined as the ratio between
the number of job openings and the number of unemployed
jobseekers; the fewer jobseekers per opening, the tighter
the market. We expect that when this ratio is high, the
labor market is tight, resulting in a higher job-finding rate.
The drawback of the matching function is that it provides
no clarity on whether the underlying reason that jobseekers and job openings are not matching up is largely because
of geographic, skill, or some other form of mismatch. Still,
it is a timely way to gauge current labor market frictions.
Although the job-finding rate and market tightness are
strongly positively correlated, a significant portion of the
variation in the job-finding rate cannot be accounted for by
labor market tightness alone. This “residual” variation can
be considered a measure of mismatch.
To understand the underlying idea behind this residual
measure, consider a situation in which the job-finding rate
remains low, even though there are many job openings
relative to the number of jobseekers in the economy. This
means that workers are not finding jobs as quickly as the
availability of job opportunities would suggest, thus implying
the presence of mismatch.
In estimating mismatch from the matching function, it is important to recall the main theme of this
article, that “all layoffs are not created equal.” The idea
behind the matching function is that searching for a new
job takes time. Thus, in estimating the matching function, one needs to properly account for the prevalence of
recalls. Specifically, those on temporary layoffs may not
be looking for a job, expecting to return to the same job,
and thus need to be excluded from the estimation of the

matching function. The hiring flow associated with recalls
also needs to be excluded. In past studies, this issue has
been largely ignored. In my work with Moscarini, we show
that the failure to take temporary layoffs and recalls into
account results in a significant bias in the estimate of mismatch in the labor market.
MATCHING EFFICIENCY AND THE GREAT RECESSION

The conventional measure of mismatch and our adjusted measure that accounts for temporary layoffs and recalls
tell two different stories (Figure 7).11
We can see that the two measures behaved similarly
overall until around the middle of 2007, although there
were some periods (for example, the mid-1990s) when the
two series moved differently. However, the two series started
diverging right before the Great Recession: The adjusted
matching efficiency series fell sharply immediately before the
Great Recession and then stayed low during the recession
relative to the unadjusted measure.12 In contrast, the decline
in the conventional measure over the same period was much
more modest, and the large drop was concentrated in the
postrecession period.
Their divergence between 2007 and 2009 implies that
the conventional measure underestimated the extent of
mismatch during the Great Recession. The reason for the
underestimate is that, during the Great Recession, new hires
fell much more drastically relative to recalls, as indicated by
the sharp increase in the series in Figure 5. Thus, including
recalls in the hiring totals mistakenly implies that there was

FIGURE 7

Accounting for Recalls Reveals New Story
Matching efficiency with and without recalled workers.
Ratio
0.3
0.2

Adjusted for recalls

0.1
0

Unadjusted

-0.1
-0.2
-0.3
1990

1994

1998

2002

2006

2010

Source: Fujita and Moscarini (2013).
Notes: Four-quarter moving average. See the paper for estimation details.

6 | Federal R eserve Bank of Philadelphia R esearch Department | Third Quarter 2016

less mismatch in the labor market. This episode shows that
to accurately assess mismatch, it is essential to take a proper
account of recalls and temporary layoffs.
SOME CONCLUDING THOUGHTS

An accurate assessment of mismatch in the labor
market is important for sound policy decisions as well.
One may argue that structural unemployment and cyclical unemployment call for different types of policy
responses. For example, monetary and fiscal policies that
seek to increase the demand for goods and services are a
more effective tool for combating cyclical unemployment,
while structural unemployment responds more effectively
to policies such as training programs that promote the

reallocation of jobless workers to industries or locations
where they are in higher demand.
The different experiences facing permanent job losers
and those on temporary layoffs suggest that structural forces
have been playing an important role in shaping unemployment for the past 15 years or so. What exactly are those
structural forces? Research on job polarization provides a
hint on this issue.13 It points out that many middle-class
jobs have evaporated due to global competition and technological advances. If these forces are indeed the underlying
causes of the longer duration of unemployment being experienced by permanent job losers, traditional countercyclical
policies such as monetary and fiscal stimulus measures are
unlikely to be the most effective tools.

NOTES
1

See Erica Groshen and Simon Potter’s 2003 article.

2
Regarding the overall behavior of the jobless rate over the business cycle,
see, for example, the 2009 article that Garey Ramey and I wrote.

3
See, for example, the 2009 paper by Gueorgui Kambourov and Iourii
Manovskii.

4
Note that there are other types of unemployed workers, for example, those
who quit their jobs and those who entered the labor force after graduating
from school. Officially, the CPS gives six types: (1) job losers on temporary
layoffs, (2) permanent job losers, (3) persons who completed temporary jobs,
(4) job leavers, (5) reentrants to the labor force, and (6) new entrants. In this
article, I lump the second and third groups together and call them permanent
layoffs or permanent job losers.

5
Note that the data shown in Figure 3 do not convey how frequently
temporary layoffs are used within each industry. The relatively small share
shown for manufacturing is partly due to that sector’s small share of jobs
among total employment. Similarly, service industries’ large shares are
partly due to their large share of employment. However, the point remains:
Temporary layoffs are not limited to a few industries.

The denominator of the job-finding rate is simply the number of workers
who moved from unemployment to employment and does not specify
whether the worker returned to the same employer or found a job at a
different employer.
6

7
The denominator of this series is all hiring flows from the unemployment
pool, not just the hiring flows of those laid off. That is, it includes hiring flows
of job leavers and entrants. Note also that as mentioned above, the hiring
flow of those on temporary layoff does not exactly correspond to recalls and
new hires, respectively. However, this series gives a good approximation that
is simple to construct.

8
Note that the job-finding rate and the duration of unemployment
are inversely related. The larger share of people caught in long-term
unemployment is reflected in the sharp decline in the job-finding rate in and
after the Great Recession.

9
How do we square this evidence of workers remaining unemployed longer
after permanent layoffs with the fact that the unemployment rate has fallen
fairly quickly in the past three years? It does not necessarily imply that the
underlying structural forces have diminished. Note that the unemployment
rate is affected by the pace of the flow into unemployment (layoffs are one
of the flows) as well as the speed at which these workers find jobs. Our
discussion above concerns the latter. A significant portion of the decline in
the unemployment rate in the past three years is accounted for by a decline
in the former. Although the job-finding rate also recovered over the same
period, it remains low. The above discussion shows that slow job finding is
concentrated among permanent job losers.

10
It is natural to always have some labor market mismatch in the economy.
But here we are interested in changes in the extent of mismatch over time.

11

Our paper details the procedure we used to construct these series.

12
Note that the adjusted matching efficiency series fell somewhat less than
10 log points between 2007 and 2009, whereas during the same period,
the job-finding rate for permanently laid-off workers fell 50 log points,
suggesting that roughly 20 percent of the decline in the job-finding rate
during that period is accounted for by the mismatch in the labor market.

13
See David Autor’s 2010 research for a comprehensive review of job
polarization, written for a broad audience.

Third Quarter 2016 | Federal R eserve Bank of Philadelphia R esearch Department | 7

REFERENCES
Autor, David. “The Polarization of Job Opportunities in the U.S. Labor
Market: Implications for Employment and Earnings,” Center for American
Progress and the Hamilton Project (April 2010).
Fujita, Shigeru, and Garey Ramey. “The Cyclicality of the Separation and JobFinding Rates,” International Economic Review, 50:2 (2009), pp. 415–430.
Fujita, Shigeru, and Giuseppe Moscarini. “Recall and Unemployment,” National
Bureau of Economic Research Working Paper 19640, (November 2013).

Groshen, Erica, and Simon Potter. “Has Structural Change Contributed to a
Jobless Recovery?” Current Issues in Economics and Finance, 9:8 (2003).
Kambourov, Gueorgui, and Iourii Manovskii. “Occupational Specificity of
Human Capital,” International Economic Review, 50:1 (2009), pp. 63–115.
Tasci, Murat. “The Ins and Outs of Unemployment in the Long Run:
Unemployment Flow and the Natural Rate,” Federal Reserve Bank of
Cleveland Working Paper 12–24 (November 2012).

Fujita, Shigeru, and Vilas Rao. “Earnings Losses of Job Losers During the
2001 Economic Downturn,” Federal Reserve Bank of Philadelphia Business
Review (Fourth Quarter 2009).

8 | Federal R eserve Bank of Philadelphia R esearch Department | Third Quarter 2016

The Free-Banking Era: A Lesson for Today?
A volatile episode in U.S. banking history might have something to teach about current
regulatory challenges — though perhaps not the lesson one might expect.
BY DANIEL SANCHES

What would happen if anyone could open a bank at
will? What if you or I could hang a sign in a storefront or
create a website and start attracting borrowers and depositors with competitive interest rates? What if any sort of firm,
big or small, could venture into the banking business in the
U.S. with no official charter required? For a time in U.S.
history, entry into banking in some states was thrown wide
open. The so-called free-banking era from 1837 to 1864 was
also a time of numerous bank failures in those states. But
exactly what lesson does this colorful yet costly period hold
for us today? At a time when too-big-to-fail banks remain a
concern and technology seems to point toward a freewheeling future of “cloud” lending and private electronic currency, insight into how to foster stability in the financial system
is especially relevant. But as I will show, the main lesson of
the free-banking era may not be the one you would think.
WHAT IS FREE BANKING?
A brief history of free banking in the U.S. After the
charter of the Bank of the United States was allowed to expire
in 1836, several states adopted free-banking laws. The widespread adoption of free-banking laws was part of a political
movement led by Jacksonian Democrats to reduce the economic and political power of large banks in the financial centers.
In the 1830s, Michigan, Georgia, and New York adopted free
banking. By 1860, 15 other states had adopted free banking.1
Economic historians largely agree that Michigan’s early
experience was a complete failure and that New York’s
overall experience was a solid success. In Michigan, bank
liability holders suffered large losses in 1837–1838 as a

result of unsound banking practices. In contrast, losses were
negligible in New York over the whole free-banking period
in that state. The available historical data for the other
free-banking states show various degrees of success when it
comes to the stability of the banking system.
Free banking ended in 1864 when Congress passed
legislation that provided bankers with strong incentives
to obtain a national charter. During the debates over the
National Banking Act, proponents cited the large number
of failures of banks with state charters in the free-banking
states and the need to establish a uniform, nationwide currency system.
Free banking didn’t mean no rules. It is important to
keep in mind that free banking is not the same as laissezfaire banking, in which there is no government interference
of any kind. Free banking simply means that no charter or
permission is needed from a government body to start a
bank, unlike the current chartered banking system in the U.S.
The free-banking laws specified that a state banking authority determined the general operating rules and minimum
capital requirement, but no official approval was required to
start a bank.2
An important rule that states imposed on free banks
was the requirement to post collateral in the form of government bonds to back their
banknotes. Unlike modern
Daniel Sanches is an
banks, whose main liabilities are
economic advisor and
deposits, the primary liability
economist at the Federal
Reserve Bank of Philadelphia.
of a typical 19th century bank,
The views expressed in this
regardless of whether it was
article are not necessarily
located in a free-banking state,
those of the Federal Reserve.

Third Quarter 2016 | Federal R eserve Bank of Philadelphia R esearch Department | 9

was its banknotes. These notes were a promise by the bank
to pay a specified amount of gold or silver currency, often
called specie, on demand. For this reason, banknotes were
widely accepted as payment outside the banking sector and
circulated in much the same way that a $5 or $20 bill circulates today. In addition, numerous broker-dealers bought
and sold banknotes for speculative purposes, which helped
develop a secondary market for banknotes.
Only state and federal government bonds were eligible to
be posted as collateral. A typical requirement was for the free
bank to deposit with the state banking authority one dollar’s
worth of eligible bonds for each dollar’s worth of banknotes.
Most of these bonds traded on the New York Stock Exchange,
which helped the state authorities determine the bonds’ market values. However, in a significant departure, some states
allowed free banks to value the bonds securing their notes at
their par or face value instead of their market value. As we
will see, this practice proved consequential.
Requiring banks to post collateral is very similar to capital
requirements today. When a bank fails today, the capital or
equity owned by the bank’s stockholders must be wiped out
before the FDIC or any uninsured depositors lose a cent. In
this sense, bank capital acts as collateral protecting the bank’s
claimants. Allowing free banks to value their bond collateral
at par posed the same kind of risk that arises if banks today are
allowed to value their assets at book value so that their capital
doesn’t fall whenever the market value of the banks’ assets
falls. In both cases, when the market value of a bank’s assets
falls, depositors (or the FDIC) lose some of their protection.3
How free banks operated. To start a free bank, the
owners would typically sell subscriptions — shares of stock
in the bank — and use the proceeds to buy eligible government bonds to deposit with the state authority. If the bonds
were approved, the state authorities would allow the bank to
start issuing banknotes.

The table illustrates how a free bank would open for
business. As we have seen, the first step is to deposit the
minimum capital amount determined by the state authorities.
Suppose that the minimum capital amount in a given state is
$50,000 and that the owners of our fictitious free bank choose
to deposit exactly this amount with the state authority in the
form of gold or silver currency. On the first day, on the liability side of its balance sheet, the bank has $50,000 in capital
and, on the asset side, $50,000 in cash — that is, specie.
Now suppose that on the second day, the owners decide
to use the bank’s cash balance to acquire $30,000 worth of
state government bonds. Then on the third day, the owners
decide to deposit the $30,000 worth of bonds with the state
authority so that they are allowed to issue banknotes. Note
that simply depositing eligible bonds with the state authority
does not alter the bank’s balance sheet. To have any meaningful change in the balance sheet, the bank needs to put at
least some of these banknotes into circulation. How can this
be accomplished?
One way a free bank can put banknotes into circulation is by making loans to households and firms. We saw
that, after depositing the bonds with the state authority,
the bank received $30,000 worth of banknotes at the end
of the third day. Suppose that, on the fourth day, a borrower shows up at the bank and applies for a $25,000 mortgage. If the bank management, after evaluating the borrower’s creditworthiness, decides to approve the loan, then
the bank can give the borrower $25,000 in banknotes in
exchange for a mortgage. As the liability side of the table
shows, the bank now has $50,000 in capital and $25,000 in
outstanding banknotes; on the asset side, it has $20,000 in
cash, $30,000 in government bonds, and $25,000 in outstanding loans. Its assets now total $75,000.
In reality, a free bank would make many loans to households and firms in the form of banknotes. As borrowers

How a Free Bank Increases Its Balance Sheet
ASSETS

LIABILITIES

Composition

Total value

Composition

Total value

Day 1 Deposits capital required by state.

$50,000 cash (specie)

$50,000

$50,000 gold capital

$50,000

Day 2 Buys state bonds with some of its cash.

$20,000 cash
$30,000 bonds

$50,000

$50,000 gold capital

$50,000

$20,000 cash
$30,000 bonds

$50,000

$50,000 gold capital

$50,000

$20,000 cash
$30,000 bonds
$25,000 mortgage

$75,000

$50,000 gold capital
$25,000 banknotes

$75,000

Day 3

Deposits bonds with state so it can issue
banknotes.

Day 4 Circulates banknotes by making loan.

10 | Federal R eserve Bank of Philadelphia R esearch Department | Third Quarter 2016

started spending these notes, they would gain circulation in
the general economy. The notes of a successful bank would
be widely accepted in transactions across the largest possible
geographic area. That way, it would normally take a long
time between the issuance of a banknote and the demand
for its redemption for gold or silver, which would allow the
bank to take advantage of profitable investment opportunities for a longer period.
Early redemption of banknotes could cause problems. Continuing my example, suppose that the annual

interest rate on the mortgage is 10 percent and that the

Putting Banknotes into Circulation

before the mortgage is repaid in full. Recall that the bank
has only $20,000 in cash reserves — not enough to make
good on the banknotes. One option is to borrow $5,000
from another bank to meet the note-holders’ demand. Let
us assume that the bank manages to secure an interbank
loan that must be repaid on the same day the mortgage matures. On the maturity date, the bank receives $27,500 from
the borrower and is able to replenish its cash reserves of
$20,000. The bank also needs to repay the $5,000 interbank
loan plus interest. As a result, its profit is less than $2,500
because the banknotes put into circulation to finance the
mortgage were presented for redemption before the mortgage
was retired and the bank had to find an alternative source of
financing. This example shows that it is best for a free bank
to keep its notes in circulation for as long as possible.
A critical assumption in the previous example was that
the bank had to keep the promise of paying out one dollar
in cash for each dollar’s worth of banknotes presented for
redemption. An important institutional characteristic of the
free-banking era was that state authorities required banks to
redeem banknotes on demand at par value. As we will see,
redemption at par made free banks subject to runs for the
same reason that today’s chartered commercial banks are
inherently fragile.
WHY DID SO MANY FREE BANKS FAIL?
Was it the consequence of unrestricted entry, or
something else? A free bank’s reserves of gold and silver

mortgage matures in one year, when the borrower needs to
pay back the interest and principal. At the end of one year,
the bank receives $27,500 from the borrower, paying off
the mortgage. If the $25,000 worth of banknotes remains
in circulation until the mortgage is repaid in full, then the
bank has more cash than the value of the banknotes it put
into circulation to finance the mortgage. One option for the
bank is to hold $25,000 in cash reserves so it can retire outstanding banknotes when they are eventually presented for
redemption. In this case, the bank’s profit is $2,500.
But now suppose that, for some reason, note-holders
demand the redemption of the $25,000 worth of banknotes

were typically small compared with the par value of its notes
in circulation. Because their gold and silver reserves paid
no interest, banks sought to keep only enough cash in their
vaults to meet that day’s expected redemptions. But because
free banks were required to pay the holders of their banknotes
gold or silver on demand at par value, they were subject to
runs if for some reason an unusually large number of noteholders decided to redeem their notes at the same time.
Normally, one would expect only a small fraction of
outstanding banknotes to return to the issuing bank for redemption within a few days. But should the public suddenly
suspect that the bank is in financial difficulty because, for
instance, it made too many bad loans, an unusually large
number of note-holders might simultaneously choose to redeem their notes, causing a bank run. Sometimes, bank runs
start not necessarily because people believe that the bank
is insolvent but simply because each note-holder believes
that other note-holders will choose to redeem their notes
today and everyone fears being last in line and coming away

Third Quarter 2016 | Federal R eserve Bank of Philadelphia R esearch Department | 11

empty-handed. Alternatively, a run may be triggered when
depositors become worried about the underlying quality of
their banks’ assets.4
Going back to my previous example, assume now that
the bank cannot find a financial institution willing to
lend it $5,000 and is unable to retire, at par value, all the
banknotes presented for redemption. In this case, we say
that the bank is illiquid, which simply means that the value
of its outstanding banknotes exceeds the value of its cash
reserves. The requirement of redemption at par value automatically converted any illiquid bank that did not manage
to secure a loan or quickly sell other assets for cash into an
insolvent bank.
In reality, if a free bank did not have enough cash reserves to retire outstanding notes presented for redemption,
the state banking authority would intervene to unwind the
bank. That is, the government bonds deposited as collateral would be sold and the proceeds would be used to pay
note-holders. In this process, note-holders would receive the
lesser of the proceeds or the notes’ par value.
It is important to keep in mind that note-holders had
no reason to immediately redeem notes that they acquired in
transactions as long as they viewed the bank as healthy. After
all, banknotes were useful payment instruments and could be
readily exchanged for gold or silver in relatively liquid secondary markets. Because it was possible to quickly determine the
market value of most banknotes, they could be easily used as
a means of payment in transactions in lieu of specie.5 In addition, the existence of a liquid secondary market for banknotes
limited note-holders’ incentive to redeem notes.
Furthermore, the continuous market pricing of a bank’s
notes tends to impose some discipline on a bank’s risk-taking. If a bank starts making too many risky loans, investors will believe that such a bank is more likely to become
insolvent and so they will discount its banknotes in the
secondary market to reflect this revised perception, increasing the bank’s cost of external finance. Knowing that any
perception of unsound banking practices will be reflected in
the market price of banknotes, a free bank has an incentive
to limit risk-taking.
These arguments provide good reasons why banknotes
would tend not to be immediately redeemed. Because
banknotes are useful payment instruments and the continuous market pricing of a bank’s notes imposes discipline on
risk-taking, one would expect a stable banking system under
free-banking laws. But the historical data tell us a different
story. So what explains the unusual number of bank failures
in the free-banking states?

Was wildcat banking the main cause of bank failures?

One hypothesis posed by Hugh Rockoff is that free banking
made it possible for bankers to engage in a particularly egregious form of risk-taking known as wildcat banking. In a typical scheme, banks were created to deliberately fail. Because
some states allowed free banks to value the bonds securing
their banknotes at par value even when these bonds were
trading at a discount, a wildcat banker could deposit depreciated bonds with the state authority and issue banknotes at
the higher face value. Once the notes began circulating, the
wildcat banker would close the bank’s doors and leave town
as soon as possible, pocketing the short-term profit.
Let me explain how wildcat banking was profitable
under par valuation of bonds. Suppose that the market value
of an eligible state bond is less than its face value, which can
occur if investors believe that the state might default. For instance, assume that an eligible state bond with a face value
of $100 is traded on the secondary market at $90. In this
case, a wildcat bank can raise $90 from stockholders to acquire state bonds at the market price. Because these bonds
are valued at their face value when deposited as reserves
with the state banking authority, the wildcat bank is allowed to issue $100 worth of banknotes. Then, the bank can
lend out $100 in banknotes, thereby acquiring $100 worth
of assets and sell those assets for cash, absconding with the
proceeds. Note-holders will eventually show up at the bank
to redeem those notes, especially after hearing the news that
the bank owners have disappeared. But the state authority
will be able to sell the state bonds for only $90 and therefore
will be able to pay only 90 cents on the dollar for each note,
resulting in a 10 percent loss for the note-holders, while the
owners of the bank make off with a profit.
The argument that wildcat banking was the main cause
of bank failures was based on two observations. First, free
banks that failed had typically been in existence for less
than a year. Second, failures among free banks were more
common in states that permitted par valuation.
Free entry might increase incentives for risk-taking
and fraud. As we will see, later study identified a different root
cause for the widespread failures. Yet, the notion that free entry into the banking business would encourage risk-taking remains a widely — though not universally — held view among
economists. The franchise value hypothesis holds that the
threat of losing a stream of profits (the bank’s franchise value)
in the event of failure puts a strong damper on risk-taking.
According to this view, a concentrated banking system
— that is, a system with a small number of large banks —
tends to be more stable than a competitive one. Proponents

12 | Federal R eserve Bank of Philadelphia R esearch Department | Third Quarter 2016

of the franchise value hypothesis argue that, holding other
factors constant, excessive competition in the banking system tends to reduce the present value of a bank’s stream of
profits. If several lenders are willing to offer the same kind
of loan to a creditworthy firm or household, it is very likely
that the borrower will get a lower interest rate on the loan.
Increased competition due to free entry made wildcat
banking more attractive in states that allowed par valuation
of bonds when the market prices of bonds were significantly
below the par value. As we have seen, when the bond’s
market price is below the par value, a banker can make a
substantial short-run profit by engaging in wildcat banking.
By doing so, the banker gives up the stream of future profits.
But if the present value of this stream of future profits is
small as a consequence of increased competition, it is more
likely that the banker will prefer the short-run profit associated with wildcat banking. Thus, intense competition leads
to a smaller present value of a free bank’s stream of profits,
making wildcat banking a more attractive choice.
If there are few banks in the banking system because of
strict rules to obtain a bank charter, then banks benefit from
reduced competition by being able to charge higher interest
rates to borrowers and pay lower interest rates to bank liability holders. In this case, the present value of the stream of
profits is relatively large, so there is no reason for a bank to
take on excessive risk. On the contrary, banks will tend to
be more conservative to avoid insolvency and preserve the
franchise value stemming from restricted entry.6
Under a concentrated banking system, wildcat banking
would have been less attractive in states that allowed par
valuation of bonds. Because the present value of the stream
of future profits is larger under a concentrated banking
system, wildcat banking pays off only if there is a very large
difference between a bond’s par and market values.
Falling asset prices led to bank failures. In their
1984 article, Arthur Rolnick and Warren Weber provide
evidence that the market value of the state bonds used as
collateral for banknotes underwent prolonged periods of
decline, reflecting, among other things, the risk of default
by the states that issued them. Their hypothesis was that it
was not wildcat banking but declines in bond prices that led
to bank failures. They argued that if wildcat banking had
been responsible for the large number of free bank failures,
then these failures would have occurred almost exclusively
when state bonds were selling below par and in those states
in which banks were permitted to issue banknotes based on
the book value of their bonds (the two conditions that make
wildcat banking profitable).

Among four free-banking states — Indiana, New York,
Minnesota, and Wisconsin — only in Minnesota were the
failures consistent with the wildcat hypothesis. If the failures
instead had been due to falling bond prices, then the greatest number would have occurred during periods of falling
bond prices, while few, if any, would have occurred when
bond prices were stable or rising. Among the four states, 79
percent of the failures were consistent with the falling bond
price hypothesis.
Importantly, the study demonstrated that the failures in
the free-banking states that were consistent with the falling bond price hypothesis were inconsistent with the wildcat
hypothesis. In the case of Indiana, for example, Rolnick and
Weber show that bank failures were concentrated in January
1855. From 1852 to August 1854, state bond prices remained
very close to par, making wildcat banking unprofitable during
this period. In 1854, Indiana bond prices fell about 26 percent
between August and December. This substantial fall in bond
prices within a short period, combined with the fact that most
failures occurred shortly after bond prices fell in January 1855,
certainly confirms the falling bond price hypothesis. What
makes this episode inconsistent with the wildcat hypothesis
is the fact that all the banks that failed in January 1855 had
been established between 1852 and 1854, a period in which
wildcat banking was not profitable. Similar evidence is provided for New York and Wisconsin free banks.
Because risky bonds backed banknotes that were callable on demand at par value, a typical free bank found it
difficult to maintain the convertibility of its banknotes at
par value, which was, according to Rolnick and Weber, the
main cause of bank failures. Free banks failed because of
substantial declines during tough economic times in the
market value of banks’ portfolios. The collateral restriction
imposed by the state banking authorities artificially increased free banks’ exposure to the risk of default by states.
CONCLUSIONS

This episode in American history suggests that the
problems free banks faced were not very different from those
encountered by banks in other periods and that the regulatory issues were also not so different. What can we learn
from the free-banking episode?
First of all, it is important to be clear about what we
haven’t learned. A close analysis of the free-banking era does
not support the view that egregious risk-taking and fraud
were the primary cause of bank failures. Thus, this historical episode does not support the contention that freer entry

Third Quarter 2016 | Federal R eserve Bank of Philadelphia R esearch Department | 13

necessarily leads to instability. The main cause of the large
number of bank failures under free banking was collateral restrictions that left banks at the mercy of the ups and
downs of state finances and the resulting volatility of state
bond values. If state bonds had truly been riskless, free banks’
note-holders would have been fully protected and the costs
of free bank failures would have been much lower. But like
risky sovereign bonds under the Basel II capital rules, risky
state bonds were treated by banking regulators as if they were
essentially riskless. One lesson for regulators today is that
tying bank safety to the presumed risklessness of a particular

asset class is a risky business.
Since the 2007–2008 financial crisis, regulators
worldwide have rethought their capital requirements for
banks and the collateral requirements for a wide range of
transactions in the shadow banking systems — most of
which are carried out through banks. Regulators now generally believe that more capital for banks — for example,
higher leverage requirements — and a higher degree of
collateralization for many trading activities are the best
guarantee of stability.7

NOTES
1
Charles Calomiris and Stephen Haber provide an interesting analysis of the
political forces that shaped the U.S. banking system in the 19th century.

5
Trade publications known as banknote reporters specialized in reporting the
market value of banknotes in regional markets.

2

It is important to emphasize that many influential economic historians view
the U.S. free-banking experience as fundamentally different from the freebanking systems that developed in other parts of the English-speaking world.
See, for instance, Lawrence White’s book and his articles with George Selgin.

6
The presence of market power in the banking industry implies that market
interest rates will be higher and the number of loans will be lower than if
banking operated in a perfectly competitive environment, resulting in a
trade-off between efficiency and safety.

3
Under current regulatory accounting rules, some assets are carried at their
book values and some assets are carried at their market values. See Ronel
Elul’s article “The Promise and Challenges of Bank Capital Reform,” which
discusses basing capital regulation on book values.

7
Leverage requirements are capital requirements that do not vary with the
risks of a bank’s assets. High leverage requirements are one way to address
the inherent difficulties of assessing the risks of banks’ assets. Also see
Michael Slonkosky’s account of the new regulations governing derivatives
transactions. An overriding goal of all these regulations is to impose higher
collateral requirements on the parties to these transactions.

4
In their 1991 article, Charles Calomiris and Gary Gorton conclude that most
bank runs historically were caused by bad economic news that led depositors
to worry about losses in their banks’ portfolios. For more on the economics
of bank runs, see my 2014 Business Review article, “Shadow Banking and the
Crisis of 2007–08.”

REFERENCES
Calomiris, Charles, and Gary Gorton. “The Origins of Banking Panics:
Models, Facts, and Bank Regulation,” in Hubbard, R. Glenn, ed., Financial
Markets and Financial Crises. Chicago: University of Chicago Press, 1991,
pp. 109–173.
Calomiris, Charles, and Stephen Haber. Fragile by Design: The Political
Origins of Banking Crises and Scarce Credit, Princeton: Princeton University
Press, 2014.
Dwyer, Gerald Jr. “Wildcat Banking, Banking Panics, and Free Banking in the
United States,” Federal Reserve Bank of Atlanta Economic Review, December
1996, pp. 1–20.
Elul, Ronel. “The Promise and Challenges of Bank Capital Reform,” Federal
Reserve Bank of Philadelphia Business Review (Third Quarter 2013).
Rockoff, Hugh. “Free Banking Era: A Reexamination,” Journal of Money,
Credit and Banking, 6 (1974), pp. 141–167.

Rolnick, Arthur, and Warren Weber. “The Causes of Free Bank Failures: A Detailed
Examination,” Journal of Monetary Economics, 14 (1984), pp. 267–291.
Rolnick, Arthur, and Warren Weber. “New Evidence on the Free Banking Era,”
American Economic Review, 73 (1983), pp. 1,080–1,091.
Sanches, Daniel. “Shadow Banking and the Crisis of 2007–08,” Federal Reserve
Bank of Philadelphia Business Review (Second Quarter 2014).
Selgin, George, and Lawrence H. White. “How Would the Invisible Hand Handle
Money?” Journal of Economic Literature, XXXII (1994), pp. 1,718–1,749.
Selgin, George, and Lawrence H. White. “The Evolution of a Free Banking
System,” Economic Inquiry, XXV (1987), pp. 439–457.
Slonkosky, Michael. “Over-the-Counter Swaps: Before and After Reform,” Federal
Reserve Bank of Philadelphia Banking Policy Review (Fourth Quarter 2015).
White, Lawrence H. Free Banking in Britain: Theory, Experience, and Debate,
1800–1845. Cambridge: Cambridge University Press, 1984.

14 | Federal R eserve Bank of Philadelphia R esearch Department | Third Quarter 2016

BANKING TRENDS
The Growing Role of CRE Lending
BY JAMES DISALVO AND RYAN JOHNSTON

Commercial real estate (CRE) has grown rapidly as a
share of total U.S. economic activity and is the largest lending category for banks.1 The growth of CRE loans has been
particularly dramatic for small and medium-sized banks.
CRE is also the riskiest part of bank portfolios, accounting
for a disproportionate share of loan charge-offs and bank
failures.2 In the years leading up to the financial crisis, CRE
lending had climbed steadily, and in the ensuing recession
CRE defaults contributed to a greater than normal number
of bank resolutions and closures. As we will explore, although an array of entities besides banks originate and hold
CRE loans, banks remain especially exposed to their risks
and rewards. In this first in a series of occasional articles
on CRE lending, we provide an initial lay of the land: Who
are the players in the market? What are the various types
of CRE loans? Why is CRE lending increasingly attractive?
What makes it risky? And why is it again on the upswing?
WHAT DISTINGUISHES A CRE LOAN?

A CRE loan is used to build or purchase any incomeproducing property. Although “commercial” real estate implies private property, the same types of CRE loans are used
for privately owned, government, and nonprofit projects.
Thus, it can be said that CRE loans finance anything from
shopping centers to skyscrapers, assisted living facilities to
five-star resorts, even the local pizza parlor. CRE loans are
also used to finance the construction of single-family home
developments, though not the purchase of individual homes.
A developer of a residential tract gets a type of CRE loan
— a construction loan — to build the houses, but then the
individual homebuyers get residential mortgages to purchase
each finished dwelling.
The overriding importance of location is a key factor

that distinguishes CRE lending from other types of bank
lending. The importance of location means that much of the
competition is local, in both the supply of and the demand
for CRE loans. While there are also a number of national
developers and lenders, there are plenty of niche opportunities for developers and lenders to exploit their knowledge
of local market conditions and their local connections.
An example of this local niche industry is a developer in
Philadelphia, AMC Delancey, which specializes in walk-up
apartment buildings, many of which have retail storefronts
on the ground floor. Nearly all of this developer’s properties
are in and around Center City Philadelphia. And as we will
see, small banks have remained competitive in CRE, even
while they have lost market share to large banks in consumer lending and commercial and industrial lending.
Because of this local aspect, CRE is particularly subject
to local and regional economic shocks. For example, a shopping mall near Williamsport, PA, can’t offset a decrease
in sales due to a drop in employment in the local fracking
industry by attracting shoppers from California. Similarly,
real estate is immobile. Unlike a machine, the shopping mall
can’t be moved to suburban Philadelphia. There is a flip side
to this risk, however. Immobility also increases the value of
a CRE asset as collateral. A business in financial distress
might secretly sell a machine or receivables it had put up as
collateral for bank loan. By contrast, land posted as collateral
for a CRE loan can’t be sold out
from under the development
James DiSalvo is a banking
should the developer experistructure specialist and Ryan
Johnston is a banking structure
ence financial distress.
associate in the Research
Another major risk factor, Department of the Federal
Reserve Bank of Philadelphia. The
unrelated to location, is time.
views expressed in this article
Developing property is not
are not necessarily those of the
quick under the best of circum- Federal Reserve.

Third Quarter 2016 | Federal R eserve Bank of Philadelphia R esearch Department | 15

stances, and delays can arise from factors out of the developer’s control. During all this time between when a loan
is made and when a property is ready to be leased or sold
— that is, when it starts producing revenue — economic
conditions can deteriorate, making a once-promising project
not viable. As we will discuss, this risk is especially present
in construction projects.
There are three types of CRE loans, depending on the
project in question and what the collateral is used for: construction and land development (CLD) loans, commercial
mortgages, and multifamily loans. Bank lending across the
three categories is volatile. Although construction lending
currently represents less than 20 percent of bank CRE lending, it has risen to as high as 40 percent of the CRE portfolio
and has averaged 25 percent since the 1980s.3 Commercial
mortgages represent the largest share of CRE lending, currently just under 70 percent and averaging 64 percent since
the 1980s. Multifamily housing loans have traditionally been
the smallest share of banks’ CRE portfolios, approximately 10
percent, but have risen to nearly 20 percent since the Great
Recession, for reasons we discuss below.
Construction and land development loans. CLD loans
cover the cost of acquiring the land, preparing the site,
and constructing the buildings. This is the riskiest type of
CRE lending. To illustrate how a CLD loan is structured
to manage risk, say that a (fictional) developer, Philly Flats
Incorporated, wants to buy an old factory and convert it
to a street-level brewpub, Beer for Lunch, with apartments
above. Building Bank — a specialist in construction lending — provides a three-year line of credit to Philly Flats,
the typical maturity for CLD loans.4 This line of credit carries a balloon payment due when the project is completed.
Building Bank’s loan provides 80 percent of the financing
necessary for the project; this is on the high end of the
usual range. The rest of the debt financing comes from a
mezzanine lender whose loan is unsecured and therefore
carries a higher interest rate. The typical ratio of the loan’s
dollar amount to the market value of the property, or loanto-value ratio (LTV), for a CLD loan varies depending on
the type of project being financed, but the range is about
75 to 85 percent.5
The loan from Building Bank is provided in three stages, with each disbursement subject to Building Bank’s assessment of whether the project is on time and within budget.
This staging of the loan is designed to mitigate Building
Bank’s risk. Stage one is for buying the land. Once the property is acquired, Philly Flats needs approval from a number
of government and quasi-governmental agencies such as the

zoning board, planning commission, and historical review
board. A problem with any one of these entities can derail
the project before it even starts. They can also significantly
increase the development costs by requiring unforeseen
features such as additional parking or green space, and they
can decrease the projected revenue by reducing the number of units. For example, Philly Flats may have planned on
eight floors of apartments but the zoning board allowed only
four. Real-life examples of approval risk are commonplace.
In Philadelphia, for example, City Council members can
exercise their councilmanic prerogative to hold up projects
of concern in their districts.6
The second stage finances the preparation of the site.
Even if the project is in a developed area and much of the
basic infrastructure is already in place, the site may require
substantial improvements such as plumbing connections,
additional sewer access, or additional electrical connections.
Projects in undeveloped areas may require roads and sewers to be built and power and water lines to be run. Each of
these improvements requires dealing with a separate local
utility and increases scheduling risks.
Assuming the project makes it past the first two stages,
the third stage is the actual construction. Anybody who has
renovated his or her home is familiar with at least some of
the risks associated with this stage. Bad weather can delay
outdoor work, supplies sometimes aren’t delivered on time,
and subcontractors don’t always show up when they’re needed, all of which can result in lost time and increased costs.
In a larger, more complicated commercial project, these risks
are magnified. For example, a strike by just one of a number
of construction unions working on the site can shut down
the entire project for weeks or more.
Ultimately, once the project is completed, Building
Bank expects Philly Flats to obtain a commercial mortgage
from another lender to make the balloon payment and pay
off the CLD loan. Until then, though, bad things can and
do happen. Imagine that five other brewpubs open within a
couple of miles of Beer for Lunch, and now no other bank is
willing to take on the financing. This leaves Building Bank
in the position of providing the commercial mortgage itself
— remember that it specializes in CLD loans and has no
expertise in commercial mortgages. It may also have a number of loans in the same area as Beer for Lunch, so another
loan there will increase its portfolio risk and invite greater
regulatory scrutiny.
Commercial mortgages. These loans are used to finance the purchase or partial ownership of existing buildings. A commercial mortgage can be secured by several

16 | Federal R eserve Bank of Philadelphia R esearch Department | Third Quarter 2016

types of properties: retail, office, industrial, hotel, as well
as mixed-use properties.
To illustrate how a commercial mortgage works and the
risks entailed in making one, let’s take the fictional example
of Hometown Bank lending to a local real estate company
to purchase a local mall; let’s call it Big Box Mall. The loan
is for 10 years, the typical length of a commercial mortgage.
At the time the loan is made, the local economy is excellent, the mall is 100 percent occupied, and it has two big
department stores as anchors. Hometown believes that it has
been prudent and designed the loan to mitigate its risk. The
LTV ratio is the industry norm, about 75 percent.7 Thus,
given the state of the local economy, the amount of available space leased, and the terms of the loan, prospects for
the loan being paid in full appear good.
But let’s say that after three years, the parent companies of the two anchor stores agree to merge, and as part
of the deal one of the mall’s anchor stores is closed. Partly
because the regional economy has cooled, no replacement
anchor can be found. The loss of an anchor has ripple effects as mall traffic shrinks and several other tenants close
their stores. The mall’s owners renegotiate the rents of some
other tenants to keep them there and lower the rent on the
vacant spaces to attract new tenants. The resulting loss of
revenue leaves the mall’s owners unable to make their payment to Hometown. Thus, even though the loan appeared
prudent at the time it was made — with a strong borrower, a
good property, and conservative loan terms — Hometown is
faced with a choice: either renegotiate the loan with a lower
revenue stream or push the borrower into default.
Multifamily loans. These loans are used to purchase
residential buildings that house five or more families such
as apartment or condominium complexes. Except for the
type of properties securing them, multifamily loans are very
similar to commercial mortgages. The main contractual
difference is that the maturity of the loan may be longer.
Although the typical maturity for a multifamily loan is 10
years, it can go as high as 40 years.8

national GDP (Figure 1). Indeed, bank regulators have expressed concern about the rapid growth of CRE lending.9
During the past 20 years, a growing source of funding
for CRE has been commercial mortgage-backed securities
(CMBS). (See The Securitization of CRE Loans.) Through securitization, loans are pooled into CMBS and sold to special
purpose vehicles.10 This permits a wide range of investors
to hold CRE loans as part of a diversified portfolio. Commercial mortgage pools now account for around 17 percent
of total commercial mortgage loans outstanding, rising from
nearly zero in the 1980s.
During the recent boom in CRE lending, multifamily loans have been a source of strength, nearly doubling
for banks since the trough (Figure 2). This strong growth is
partly an aftereffect of the Great Recession on the singleFIGURE 1

A Big Part of the Economy
Total CRE loans outstanding.

Sources: Federal Reserve Flow of Funds, Federal Reserve Economic Data (FRED), and
National Bureau of Economic Research.
Note: Loans outstanding are from the Flow of Funds data, which include commercial
and multifamily CRE but not CLD loans.

FIGURE 2

CRE Growth Has Been Strong Recently
CRE loan categories.

HOW AND WHY HAS CRE LENDING GROWN?

CRE had risen strongly during the real estate boom of
the 1990s and 2000s, especially in the years leading up to
the Great Recession. Following the deleveraging that took
place during the downturn and the subsequent recovery, it
has turned around in the past few years. Since the trough
in CRE lending in mid-2012, CRE loans outstanding have
increased to $3.6 trillion and now represent 19.8 percent of

Source: Federal Financial Institutions Examination Council Call Reports.
Note: Data are from the Federal Financial Institutions Examination Council Call Reports,
which include commercial mortgages and multifamily and CLD loans.

Third Quarter 2016 | Federal R eserve Bank of Philadelphia R esearch Department | 17

The Securitization of CRE Loans
Like any loan, a commercial mortgage generates an income stream for the lender. Thus, a third party is often interested in buying
the mortgage to lay claim to the borrower’s promised stream of payments. After originating the loan, the lender can sell it to a
private firm known as a mortgage conduit, or, if the commercial mortgage is for a multifamily property, the lender can sell it to one
of the government-sponsored enterprises (GSEs), Fannie Mae or Freddie Mac.
These buyers then pool the loan with other loans bearing similar risk profiles and maturities to create a commercial mortgagebacked security (CMBS). In turn, the conduit or GSE sells claims to investors on the cash flows from this pool. These claims are
designed to appeal to different types of investors. The original lender often retains the servicing rights — that is, it collects the
mortgage payments and is paid a fee for doing so.

By taking loans off their books through securitization, banks transfer to the holders of the CMBS not just the expected returns but
also the risks inherent in any loan. These risks can include credit risk — the risk that the loan won’t be repaid — and interest rate
risk — the risk that changes in interest rates will result in a decrease in the value of an asset or an increase in the lender’s cost of
funds. In addition, by removing the loans from their books, lenders, at least if they’re depository institutions, have additional funds
to generate more loans, and they eliminate the need to hold capital against the loans.
Large banks securitize about one-fifth of the loans that they originate and account for 84 percent of the loans securitized by banks.
But not all loans are easy to securitize. Smaller loans, complex loans, nonstandard loans, and floating-rate loans are typically held
in portfolio. These loans can be more complicated for investors to evaluate, and there is some evidence that they are more difficult
to renegotiate when trouble arises.

family housing market — tighter lending conditions for
receiving a mortgage; households’ weakened financial position, especially among young and lower-income families; a
slowing in the rate of household formation11 — and partly a
demographic trend toward living in urban areas that have an
abundance of amenities within walking distance.12 Since the
second quarter of 2012, multifamily loans outstanding have
increased 26.7 percent, while loans on one- to four-family
properties have decreased almost 1 percent.13 Homeownership
rates decreased from an all-time high of 69.2 percent in 2004
to 63.8 percent in 2015. At the same time, apartment vacancy
rates decreased from 10 percent to 7 percent, and the median
rent increased from $620 to $850 per month.14 Despite the
recent growth in multifamily lending, there is a lot of uncertainty among economists, real estate developers, and bankers as to how much of this shift from single-family homes to
apartments is temporary and how much is longer term.

WHO BORROWS? WHO LENDS?

The borrowing side of the CRE loan market is highly
fragmented, with borrowers differentiated by geography
and industry. On the lending side, while banks remain the
dominant lenders, the composition of bank lenders and nonbank lenders has changed over time. Over the past 20 years,
banks overall have consistently held about half of all CRE
loans. However, for midsize and small banks, the share of
CRE loans in their portfolios has roughly doubled. Besides
banks, insurers remain a significant player in the CRE lending market, but as we will discuss, their participation has
diminished. Another significant supplier of CRE funding is
the government-sponsored enterprises (GSEs) Fannie Mae
and Freddie Mac, which have a strictly multifamily CRE
niche. Looking at lenders and borrowers in more detail,
some interesting trends emerge.

18 | Federal R eserve Bank of Philadelphia R esearch Department | Third Quarter 2016

Who borrows? The largest class of borrowers taking
out CRE loans consists of noncorporate nonfinancial firms
(Figure 3). This class makes up 75 percent of the borrowers
in the CRE market and includes everything from large real
estate developers to the corner green grocer.
Real estate developers come in a wide range of sizes and
degrees of specialization. They can run part of the commercial project, such as buying raw land, or they can oversee
and manage the entire development process of designing,
preparing, and building the property. For instance, BergerEpstein Associates of Allentown, PA, owns and develops
retail properties mostly in eastern Pennsylvania. Another
example of a smaller real estate developer is New Vistas
Corporation of Mount Laurel, NJ, which develops office,
retail, and multifamily properties in New Jersey.
Large real estate developers can own commercial property all over the world. For example, one of the largest developers of office properties in the country is Hines, a real estate
investment, development, and management firm based in
Houston, TX. It has properties in 182 cities and 20 countries
worldwide with $89.1 billion of assets under management.
Real estate investment trusts (REITs) represent a
steadily increasing share of CRE borrowings and represent
around 6.6 percent of total CRE loans borrowed.15 These
companies own and manage income-producing real estate
and are required to pay at least 90 percent of their earnings
to their investors as a condition for avoiding taxes at the
corporate level. REITs own and manage all types of commercial real estate and tend to specialize in a certain type,
such as hotels, apartments, storage units, offices, malls, or
student housing.16
Other borrowers of CRE loans include nonfinancial
corporate businesses and nonprofit organizations such as
universities, churches, and hospitals. They comprise about
12 percent and 6 percent of CRE borrowings, respectively.
Who lends? Banks are the most significant suppliers of
funds for CRE, holding over half of total CRE loans in their
own portfolios, a share that has been roughly constant for
the past 20 years (Figure 4). By the fourth quarter of 2015,
banks’ holdings of CRE loans totaled $1.98 trillion. This
total actually understates the role that banks play because
they also originate loans that are securitized. Taking loans
that are securitized into account, depository institutions
originate about two-thirds of total CRE loans.17
Large banks held about $775 billion in CRE loans in
the fourth quarter of 2015 (Figure 5) — accounting for
around 40 percent of all CRE loans held by banks — but
they account for the preponderance of CRE loans securi-

FIGURE 3

Noncorporate Nonfinancials Predominate
Major borrowers of CRE loans.

Source: Federal Reserve Flow of Funds.
Note: Shares are from the Flow of Funds, which include commercial and multifamily
CRE but not CLD loans.

FIGURE 4

Banks Still Supply Most CRE Funding
Major holders of CRE loans.

Source: Federal Financial Institutions Examination Council Call Reports.
Note: Loans outstanding are from the Flow of Funds data, which include commercial
and multifamily CRE but not CLD loans.

tized by banks. (See The Securitization of CRE Loans.) The
growth in CRE lending by small and medium-sized banks
has been particularly striking (Figure 5).18 CRE loans account for around 21 percent of all banks’ loan portfolios, but
in the past 20 years they have risen from 15 percent to 30
percent of midsize bank portfolios and from around 20 percent to over 40 percent of small bank loan portfolios (Figure
6). Small banks made approximately $855 billion in CRE
loans while medium-sized banks made approximately $345
billion in CRE loans in the fourth quarter of 2015.19 Small
and medium-sized banks retain most of what they originate in their portfolios. The loans made by Hometown and
Building Bank are good illustrations of the types of loans

Third Quarter 2016 | Federal R eserve Bank of Philadelphia R esearch Department | 19

FIGURE 5

Small Banks Do More CRE Lending
Total CRE loans by banks.

Source: Federal Financial Institutions Examination Council Call Reports.
Note: Data are from the Federal Financial Institutions Examination Council Call Reports,
which include commercial mortgages and multifamily and CLD loans.

FIGURE 6

Small Banks Rely Heavily on CRE
CRE loans as percent of total bank loans.

Source: Federal Reserve Flow of Funds.
Note: Data are from the Federal Financial Institutions Examination Council Call Reports,
which include commercial mortgages and multifamily and CLD loans.

made by small and medium-sized banks.
Insurance companies hold a significant share — about
11 percent — of total CRE loans (Figure 4). This share has
declined from over 20 percent in the 1980s, more or less
mirroring the insurance industry’s declining share of lending
across the board. In CRE markets, insurance companies’
declining share has coincided with the growth of mortgage
pools, which currently make up about 17 percent of CRE
loans outstanding.
The GSEs also directly hold over 7 percent of CRE
loans outstanding, holdings that are composed exclusively of
multifamily loans. As mentioned earlier, the GSEs are also
major players in the CMBS market. Together they held over
$204 billion in CRE loan pools at the end of 2015.
The remaining 15 percent of CRE loans are held by a
range of investors including REITs, private investors, mutual
funds, and pension funds, each specializing in particular
locations, types of loans, and risk profiles.
LOOKING AHEAD

Although financing for commercial development comes
from an array of sources, banks and savings and loans
remain by far the largest originators and holders of CRE assets. Smaller banks’ detailed knowledge of local real estate
markets may now be a more important source of comparative advantage in financing CRE than for other types of
loans.20 Given banks’ critical role in the economy, it is fruitful to explore the extent of their investment in this profitable and volatile industry. In future articles, we will explore
in more detail which lending markets are local and which
are regional or national, who competes with whom, and the
differences between securitized and portfolio loans.

NOTES
1
We refer to depository institutions, a category that includes both
commercial banks and savings and loans, as banks. For the purposes of this
article, small banks are defined as those with assets of less than $10 billion,
medium-sized banks are those with assets totaling $10 billion to $50 billion,
and large banks’ assets total $50 billion or more.
2
For instance, for 2009, banks had net charge-offs on CRE loans of over
$8 billion, representing over 30 percent of all net charge-offs, according to
Federal Financial Institutions Examination Council Call Reports. For smaller
banks, net charge-offs on CRE loans represented over 50 percent.
3
Our data begin in 1984, the first year for which we have reliable Federal
Financial Institutions Examination Council Call Report data.

4
See David Ling and Wayne Archer’s book for a fuller discussion of CRE
contract terms. In addition to having three-year terms, typical CLD loans are
interest-only, with variable interest rates.

By regulation, land development loans cannot have an LTV greater than
75 percent, LTVs for construction loans on commercial and multifamily
properties cannot exceed 80 percent, and those on residential properties
cannot exceed 85 percent.
5

6
See the 2015 Pew Report and the May 7, 2016, article by Jacob Adelman
about an apartment tower and retail mall proposed for Broad Street and
Washington Avenue.

20 | Federal R eserve Bank of Philadelphia R esearch Department | Third Quarter 2016

7
Typical terms on a commercial mortgage are (1) a 10-year term, although
terms can go as low as five and as high as 30 years, (2) an LTV ratio of 65
percent, though it can go as high as 75 percent, and (3) a debt coverage
ratio (the ratio of monthly net operating income to monthly debt payment)
of 1.45 to 1.5 percent, and this can go as low as 1.25 percent. Also, a bank
can require the borrower to set aside a reserve per square foot. The industry
norm is 15 to 20 cents per square foot. However, these reserves can go as
high as 50 cents per square foot depending on the type of property.

Typical terms on a multifamily loan are (1) a 10-year term, though they can
go as low as five and as high as 40, (2) an LTV ratio of 75 percent, though
ratios can go as high as 85 percent, (3) a debt coverage ratio (the ratio of
monthly net operating income to monthly debt payment) of 1.35 percent,
which can go as low as 1.2 percent, and (4) a reserve of about $300 per
unit, though this can go as low as $250 and as high as $750. The size of the
reserve is based on the number of units rather than square feet.
8

14

15
Mortgage loans account for only about 20 percent of REITs’ total liabilities,
which also include bonds, repurchase agreements, and bank lines of credit.
Thus, REITs play a larger role than the 6.6 percent might suggest.
16
There are two basic types of REITS, equity REITs and mortgage REITs.
Equity REITs generate income through the collection of rent on, and from
sale of, the properties they own. Equity REITs make up around 93 percent of
all REITs in the U.S. Mortgage REITs — which have declined in importance
over time — invest in mortgages or mortgage securities and generate their
income through fees and interest.
17
While we have precise numbers for the relative shares of CRE held by
different types of firms, we can provide only estimates of the shares of CRE
loans originated by different types of firms.

9

The Federal Deposit Insurance Corporation, the Federal Reserve, and
the Office of the Comptroller of the Currency put out a joint “Statement
on Prudent Risk Management for Commercial Real Estate Lending” on
December 18, 2015.

18

See Ronel Elul’s Business Review article for a more detailed description of
how securitization works.

10

Census Bureau Housing Vacancies and Homeownership data.

Total loans increased from 60 to 65 percent of total assets at small banks
and from 61 to 67 percent at midsize banks over this period. Total loans as
a percent of assets at small and midsize banks have increased modestly. See
our Third Quarter 2015 Banking Trends article.

12

See Jackelyn Hwang and Jeffrey Lin’s working paper for evidence of this trend.

19
Note that each bank size category’s share of total CRE loans reflects not only
the share of assets committed to CRE by banks in that category, but also that
category’s share of total bank assets. So, the large number of small banks,
each heavily committed to CRE, leads to a large total, even though the assets
of each bank are small. Large banks account for a large share of total assets,
but CRE represents a small portion of each large bank’s portfolio. Middle-size
banks’ loan portfolios look more like those of large banks than small banks.

13

Federal Reserve Flow of Funds data.

20

See Burcu Eyigungor’s Economic Insights article and Paul Flora’s Regional
Spotlight for discussions of these issues.

11

See our Third Quarter 2015 Banking Trends article for evidence of this.

REFERENCES
Adelman, Jacob. “Moratorium on Construction at Blatstein’s Tower Site
Introduced in Council,” Philly.com, May 7, 2016, http://articles.philly.
com/2016-05-07/business/72913170_1_bart-blatstein-tower-site-april-27.

Geltner, David M., Norman G. Miller, Jim Clayton, and Piet Eichholtz.
Commercial Real Estate: Analysis and Investments, second edition, Mason,
OH: Cengage Learning (2007).

Black, Lamont, John Krainer, and Joseph Nichols. “From Origination to
Renegotiation: A Comparison of Portfolio and Securitized Commercial Real
Estate Loans,” Journal of Real Estate Finance and Economics (2016).

Hwang, Jackelyn, and Jeffrey Lin. “What Have We Learned About the Causes
of Recent Gentrification?” Federal Reserve Bank of Philadelphia Working Paper
16–20 (June 2016).

Black, Lamont K., Chenghuan Sean Chu, Andrew Cohen, and Joseph B.
Nichols. “Differences Across Originators in CMBS Loan Underwriting,”
Journal of Financial Services Research, 42:115 (2012).

Lea, Michael J., Achim Dubel, Jacek Laszek, and Loic Chiquier. “The Risks of
Commercial Real Estate Lending,” U.S. Agency for International Development
(1997).

DiSalvo, James, and Ryan Johnston. “Banking Trends: How Our Region
Differs,” Federal Reserve Bank of Philadelphia Business Review (Third
Quarter 2015).

Levitin, Adam J., and Susan M. Wachter. “The Commercial Real Estate
Bubble,” Harvard Business Law Review, 3 (2013).

Elul, Ronel. “The Economics of Asset Securitization,” Federal Reserve Bank of
Philadelphia Business Review (Third Quarter 2005).
Eyigungor, Burcu. “Housing’s Role in the Slow Recovery,” Federal Reserve
Bank of Philadelphia Economic Insights (Second Quarter 2016).

Financial Accounts of the United States: Flow of Funds, Balance Sheets, and
Integrated Macroeconomic Accounts, Board of Governors of the Federal
Reserve System (2015).
Flora, Paul R. “What’s Holding Back Homebuilding?” Federal Reserve Bank
of Philadelphia Regional Spotlight (Second Quarter 2015).

Ling, David C., and Wayne R. Archer. Real Estate Principles: A Value
Approach, Fourth Edition, New York: McGraw-Hill (2012).
Linneman, Peter. Real Estate Finance and Investments: Risks and
Opportunities. Philadelphia: Linneman and Associates, 2004.
Montgomery, Malcolm K., and Lee A. Kuntz. “Commercial Real Estate
Lending in the United States,” Shearman & Sterling L.L.P. (2002).
Pew Charitable Trusts. “Philadelphia’s Councilmanic Prerogative: How It
Works and Why It Matters,” July 2015, http://www.pewtrusts.org/~/media/
assets/2015/07/philadelphia-councilmanic-report--final--web-v2.pdf?la=en.

Third Quarter 2016 | Federal R eserve Bank of Philadelphia R esearch Department | 21

RESEARCH UPDATE
These working papers present preliminary findings of research conducted by Philadelphia Fed economists, analysts, and
visiting scholars. Visit our website for more abstracts and papers.

CONGESTION, AGGLOMERATION, AND
THE STRUCTURE OF CITIES

Congestion costs in urban areas are significant and
clearly represent a negative externality. Nonetheless, economists also recognize the production advantages of urban
density in the form of positive agglomeration externalities.
The long-run equilibrium outcomes in economies with
multiple correlated but offsetting externalities have yet to be
fully explored in the literature. Therefore, the author has developed a spatial equilibrium model of urban structure that
includes both congestion costs and agglomeration externalities. The author then estimates the structural parameters
of the model using a computational algorithm to match the
spatial distribution of employment, population, land use,
land rents, and commute times in the data. Policy simulations based on the estimates suggest that congestion pricing
may have ambiguous consequences for economic welfare.
Working Paper 16–13. Jeffrey C. Brinkman, Federal Reserve Bank of Philadelphia Research Department.
Supersedes Working Paper 13–25.
CREDIT RATINGS, PRIVATE INFORMATION, AND BANK
MONITORING ABILITY

In this paper, the authors use credit rating data from
two large Swedish banks to elicit evidence on banks’ loan
monitoring ability. For these banks, the authors’ tests reveal
that banks’ internal credit ratings indeed include valuable
private information from monitoring, as theory suggests.
Banks’ private information increases with the size of loans.
Working Paper 16–14. Leonard I. Nakamura, Federal
Reserve Bank of Philadelphia Research Department; Kasper
Roszbach, Sveriges Riksbank, University of Groningen.
IS BIGGER NECESSARILY BETTER
IN COMMUNITY BANKING?

The authors investigate the relative performance of
publicly traded community banks (those with assets less
than $10 billion) versus larger banks (those with assets

between $10 billion and $50 billion). A body of research
has shown that community banks have potential advantages in relationship lending compared with large banks,
although newer research suggests that these advantages may
be shrinking. In addition, the burdens placed on community
banks by the regulatory reforms mandated by the DoddFrank Wall Street Reform and Consumer Protection Act
and the need to increase investment in technology, both of
which have fixed-cost components, may have disproportionately raised community banks’ costs. The authors find that,
on average, large banks financially outperform community
banks as a group and are more efficient at credit-risk assessment and monitoring. But within the community bank segment, larger community banks outperform smaller community banks. The authors’ findings, taken as a whole, suggest
that there are incentives for small banks to grow larger to
exploit scale economies and to achieve other scale-related
benefits in terms of credit-risk monitoring. In addition, the
authors find that small business lending is an important
factor in the better performance of large community banks
compared with small community banks. Thus, concern that
small business lending would be adversely affected if small
community banks find it beneficial to increase their scale is
not supported by their results.
Working Paper 16–15. Joseph P. Hughes, Rutgers University; Julapa Jagtiani, Federal Reserve Bank of Philadelphia
Supervision, Regulation, and Credit; Loretta J. Mester, Federal
Reserve Bank of Cleveland, University of Pennsylvania Wharton School.
THE POLITICAL ECONOMY OF UNDERFUNDED
MUNICIPAL PENSION PLANS

The authors analyze the determinants of underfunding of local governments’ pension funds using a politicoeconomic overlapping generations model. They show that
a binding downpayment constraint in the housing market
dampens capitalization of future taxes into current land
prices. Thus, a local government’s pension funding policy

22 | Federal R eserve Bank of Philadelphia R esearch Department | Third Quarter 2016

matters for land prices and the utility of young households.
Underfunding arises in equilibrium if the pension funding
policy is set by the old generation. Young households instead
favor a policy of full funding. Empirical results based on
cross-city comparisons in the magnitude of unfunded liabilities are consistent with the predictions of the model.
Working Paper 16–16. Jeffrey C. Brinkman, Federal
Reserve Bank of Philadelphia Research Department; Daniele
Coen-Pirani, University of Pittsburgh; Holger Sieg, University of
Pennsylvania, National Bureau of Economic Research.
DO GDP FORECASTS RESPOND EFFICIENTLY
TO CHANGES IN INTEREST RATES?

The authors examine and extend the results of Ball and
Croushore (2003) and Rudebusch and Williams (2009), who
show that the output forecasts in the Survey of Professional
Forecasters (SPF) are inefficient. Ball and Croushore show
that the SPF output forecasts are inefficient with respect to
changes in monetary policy, as measured by changes in real
interest rates, while Rudebusch and Williams show that the
forecasts are inefficient with respect to the yield spread. In
this paper, the authors investigate the robustness of both
claims of inefficiency, using real-time data and exploring the
impact of alternative sample periods on the results.
Working Paper 16–17. Dean Croushore, University of
Richmond, Federal Reserve Bank of Philadelphia Research Department Visiting Scholar; Katherine Marsten, Federal Reserve
Board of Governors.
AN EXPERIMENT ON INFORMATION USE IN
COLLEGE STUDENT LOAN DECISIONS

There is ample concern that college students are making ill-informed student loan decisions with potentially negative consequences to themselves and the broader economy.
The author reports the results of a randomized field experiment in which college students are provided salient information about their borrowing choices. The setting is a large
flagship public university in the Midwest, and the sample includes all nongraduating students who previously borrowed
student loan money (~10,000 students). Half of the students
received individually tailored letters with simplified information about future monthly payments, cumulative borrowing, and the typical borrowing of peers; the other half is
the control group that received no additional information.
There are at most modest effects of the letter overall, which
suggests that information alone is not sufficient to drive
systematically different borrowing choices among students.

However, some key student subgroups changed their borrowing in response to the letter, particularly those with low
GPAs. There is also evidence of intended (more contact
with financial aid professionals) and unintended (lower Pell
Grant receipt) consequences of the letter.
Working Paper 16–18. Rajeev Darolia, University of Missouri, Federal Reserve Bank of Philadelphia Payment Cards
Center Visiting Scholar.
THE CAUSES OF HOUSEHOLD BANKRUPTCY:
THE INTERACTION OF INCOME SHOCKS AND
BALANCE SHEETS

The authors examine how household balance sheets
and income statements interact to affect bankruptcy decisions following an exogenous income shock. For identification, they exploit government payments in one but not any
other Canadian province that varied exogenously based
on family size. Receiving a larger income shock from the
payment (relative to household income) reduces the count
of bankruptcies, with fewer remaining filers having higher
net balance sheet benefits of bankruptcy (unsecured debt
discharged minus liquidated assets forgone). Receiving an
income shock thus causes households that would receive
lower net balance sheet benefits under bankruptcy law to
select out of bankruptcy.
Working Paper 16–19. Vyacheslav Mikhed, Federal Reserve
Bank of Philadelphia Payment Cards Center; Barry Scholnick,
University of Alberta School of Business.
Supersedes Working Paper 14–17.
WHAT HAVE WE LEARNED ABOUT THE CAUSES OF
RECENT GENTRIFICATION?

Since 2000, strengthening gentrification in an expanding section of cities and neighborhoods has renewed interest
from policymakers, researchers, and the public in the causes
of gentrification. The identification of causal factors can
help inform analyses of welfare, policy responses, and forecasts of future neighborhood change. The authors highlight
some features of recent gentrification that popular understandings often do not emphasize, and they review progress
on identifying some causal factors. However, a complete
account of the relative contribution of many factors is still
elusive. The authors suggest questions and opportunities for
future research.
Working Paper 16–20. Jackelyn Hwang, Princeton University; Jeffrey Lin, Federal Reserve Bank of Philadelphia Research
Department.

Third Quarter 2016 | Federal R eserve Bank of Philadelphia R esearch Department | 23

ASSESSING BANKRUPTCY REFORM IN A MODEL WITH
TEMPTATION AND EQUILIBRIUM DEFAULT

DISTRIBUTIONAL INCENTIVES IN AN EQUILIBRIUM
MODEL OF DOMESTIC SOVEREIGN DEFAULT

A life-cycle model with equilibrium default in which
agents with and without temptation coexist is constructed
to evaluate the 2005 bankruptcy law reform. The calibrated
model indicates that the 2005 reform reduces bankruptcies,
as seen in the data, and improves welfare, as lower default
premia allows better consumption smoothing. A counterfactual reform of changing income garnishment rate is also
investigated. Interesting contrasting welfare effects between
two types of agents emerge. Agents with temptation prefer a
lower garnishment rate as tighter borrowing constraint prevents them from over-borrowing, while those without prefer
better consumption smoothing enabled by a higher garnishment rate.
Working Paper 16–21. Makoto Nakajima, Federal Reserve
Bank of Philadelphia Research Department.

Europe’s debt crisis resembles historical episodes of
outright default on domestic public debt about which little
research exists. This paper proposes a theory of domestic
sovereign default based on distributional incentives affecting the welfare of risk-averse debt and non-debtholders. A
utilitarian government cannot sustain debt if default is costless. If default is costly, debt with default risk is sustainable,
and debt falls as the concentration of debt ownership rises.
A government favoring bondholders can also sustain debt,
with debt rising as ownership becomes more concentrated.
These results are robust to adding foreign investors, redistributive taxes, or a second asset.
Working Paper 16–23. Pablo D’Erasmo, Federal Reserve
Bank of Philadelphia Research Department; Enrique G. Mendoza, University of Pennsylvania, National Bureau of Economic
Research, Penn Institute for Economic Research.

THE CONSEQUENCES OF GENTRIFICATION: A FOCUS ON
RESIDENTS’ FINANCIAL HEALTH IN PHILADELPHIA

There has been considerable debate and controversy
about the effects of gentrification on neighborhoods and the
people residing in them. This paper draws on a unique largescale consumer credit database to examine the relationship
between gentrification and the credit scores of residents in
the City of Philadelphia from 2002 to 2014. The authors
find that gentrification is positively associated with changes
in residents’ credit scores on average for those who stay, and
this relationship is stronger for residents in neighborhoods in
the more advanced stages of gentrification. Gentrification is
also positively associated with credit score changes for less
advantaged residents (low credit score, older, or longer term
residents, and those without mortgages) if they do not move,
though the magnitude of this positive association is smaller
than for their more advantaged counterparts. Nonetheless,
moving from gentrifying neighborhoods is negatively associated with credit score changes for less advantaged residents,
residents who move to lower-income neighborhoods, and
residents who move to any other neighborhoods within the
city (instead of outside the city) relative to those who stay.
The results demonstrate how the association between gentrification and residents’ financial health is uneven, especially for less advantaged residents.
Working Paper 16–22. Lei Ding, Federal Reserve Bank of
Philadelphia Community Development Studies & Education
Department; Jackelyn Hwang, Princeton University.

24 | Federal R eserve Bank of Philadelphia R esearch Department | Third Quarter 2016

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