May 20, 2013
Economic Commentary
'Urban Decline in Rust-Belt Cities'
Author: Daniel Hartley.
The author is a research economist at the Federal Reserve Bank of Cleveland. The views expressed are his owns and not necessarily those of the Federal Reserve Bank of Cleveland or the Board of Governors of the Federal Reserve System or its staff..
Summary: Many Rust-Belt cities have seen almost half their
populations move from inside the city borders to the surrounding suburbs
and elsewhere since the 1970s. As populations shifted, neighborhoods
changed—in their average income, educational profile, and housing
prices. But the shift did not happen in every neighborhood at the same
rate. Recent research has uncovered some of the patterns characterizing
the process.
Complete research report:
Most major Rust-Belt cities have seen their populations
shrink since their heydays, and with that decline, the average income of
the remaining residents has fallen as well. Cities such as Buffalo,
Cleveland, Detroit, and Pittsburgh have each lost more than 40 percent
of their populations over the last four decades. However, the losses
have not been uniform across neighborhoods. Some neighborhoods have
declined more rapidly than others.
The uneven population decline across neighborhoods implies that the
distributions of income, house prices, and human capital have also
shifted within cities and larger metropolitan areas over time. While the
challenges posed by the decline in overall population are well
recognized, the movement of the population across neighborhoods within
these Rust-Belt cities creates additional challenges. Policymakers and
city planners need to understand how such neighborhood dynamics evolve
and, ultimately, how the underlying dynamics interact with the provision
of public services and infrastructure.
Recent research on population and income dynamics in four Rust-Belt
cities shows that neighborhoods with the lowest housing prices are the
ones that experience the steepest declines in population, but that
income falls more sharply in neighborhoods with middle-tier house
prices. These patterns are the reverse of a gentrification process. Both
processes involve the borders of poor and rich neighborhoods. But where
gentrification typically leads to an outward expansion of high-income
neighborhoods into low-income neighborhoods, reverse gentrification
involves an inward contraction of high-income neighborhoods, as the
border areas become low-income.
This
Commentary describes the reverse gentrification process
and its consequences in four cities—Buffalo, Cleveland, Detroit, and
Pittsburgh—from 1970 to 2006. While reverse gentrification occurred to
some degree in all four cities, there are distinct differences across
them. In addition, to show how neighborhood dynamics in the central city
influence the surrounding suburbs, the Cleveland-Akron metropolitan
area is explored more closely, focusing on changes in the inner-ring and
outer-ring suburbs.
Patterns of Urban Decline in Rust-Belt Cities.
Cleveland, Detroit, Buffalo, and Pittsburgh are alike in many ways.
All lie within close proximity to one another, and all were centers of
manufacturing activity and still relatively large in 1970. Remarkably,
from 1970 to 2006 all four of these cities lost about 45 percent of
their population (see table 1). Median household incomes fell in all of
them (in real terms), though less in Buffalo and Pittsburgh. Incomes in
Cleveland and Detroit fell by about 30 percent, Buffalo by 20 percent,
and Pittsburgh by 10 percent.
1
Median home prices have not changed much in any of these cities. In
fact, in Cleveland the median price of a home changed almost exactly 0
percent from 1970 to 2006.
Table 1. Comparison of Population, Income, House Prices, and
Education in Cleveland, Detroit, Buffalo, and Pittsburgh in 1970 and
2006
|
Buffalo |
Pittsburgh |
|
1970 |
2006 |
Change (%) |
1970 |
2006 |
Change (%) |
| Population |
462,783 |
257,758 |
−44 |
520,167 |
297,061 |
−43 |
| Median household income (2009 dollars) |
38,395 |
29,637 |
−23 |
37,477 |
33,818 |
−10 |
| Median home value (2009 dollars) |
71,477 |
64,702 |
−9 |
69,570 |
78,749 |
13 |
| Fraction with college or higher degree |
6.7 |
20.4 |
13.7 |
9.0 |
31.3 |
22.3 |
|
Cleveland |
Detroit |
|
1970 |
2006 |
Change(%) |
1970 |
2006 |
Change(%) |
| Population |
751,046 |
406,427 |
−46 |
1,511,336 |
834,116 |
−45 |
| Median household income (2009 dollars) |
41,674 |
28,238 |
−32 |
46,438 |
30,184 |
−35 |
| Median home value (2009 dollars) |
92,826 |
92,477 |
0 |
86,108 |
93,966 |
9 |
| Fraction with college or higher degree |
4.4 |
12.0 |
7.6 |
6.2 |
11.3 |
5.1 |
Sources: U.S. Census Bureau, 1970 Census and 2006 American Community Survey.
One area in which the cities have differed more is educational
attainment—a measure of what economists call “human capital.” Cleveland
and Detroit had the lowest proportion of residents over the age of 25
with a college degree or higher in 1970 (4 percent and 6 percent,
respectively), and both experienced relatively small gains in this share
by 2006, leaving both at about 12 percent. In contrast, Buffalo and
Pittsburgh were slightly more highly educated in 1970 (7 percent and 9
percent, respectively) but are now much more highly educated (20 percent
and 31 percent, respectively).
To examine how the population has shifted across neighborhoods over
time, and how these changes have affected other neighborhood
characteristics like income, housing prices, and educational attainment,
I looked at groups of neighborhoods based on their home prices in 1970.
I used home prices because they provide a summary measure of the
amenities and characteristics of the neighborhoods. To create the
groups, I ranked the census tracts in each city by their median home
price and then divided each city’s set of tracts into 10 similarly sized
groups. (I label these deciles 1 through 10, ordered from the lowest to
the highest median home price in 1970).
In terms of population changes within the city, Cleveland displays a
pattern similar to that of Detroit, Pittsburgh, and Buffalo (figure 1).
While population dropped in tracts all across the city, it dropped the
most in the initially low-price tracts and the least in the
highest-price tracts.
With respect to income growth, Cleveland and Detroit are again
similar; both saw the steepest drops in income in the middle deciles
(figure 2). The highest deciles do not drop in income by that much, but
the next-highest deciles experience a big drop in income as lower-income
residents move in. These trends can be described as a shrinking of the
high-income neighborhoods inward toward their core.
In Buffalo and Pittsburgh the overall pattern is the same, but growth
rates in most neighborhoods are higher than in Cleveland and Detroit.
It is worth noting that in Pittsburgh and Buffalo, incomes surge ahead
in the highest-home-price neighborhoods between 1970 and 2006—by almost
50 percent in Pittsburgh and 20 percent in Buffalo—a phenomenon that is
not present in Cleveland or Detroit. This reflects the fact that these
neighborhoods are situated near centers of higher education, which have
attracted highly skilled residents. By contrast, some of the
neighborhoods closest to Cleveland’s major higher education institutions
are outside the city limits.
The top decile neighborhoods of Pittsburgh and Buffalo have also
experienced sizable gains in educational attainment (figure 3). By
contrast, gains in educational attainment in Cleveland and Detroit are
much more modest and somewhat flat across the neighborhood price
deciles. Even the lowest-decile neighborhoods in Pittsburgh saw a
dramatic increase in educational attainment. This change is consistent
with the high-income growth that occurred in these areas and suggests
that there is some degree of gentrification occurring in Pittsburgh.
Home-price growth in Cleveland and Detroit is very small in all
deciles except for the two lowest-price deciles (figure 4). Some of the
price increases in the lowest-price deciles may be attributable to what
statisticians call “mean reversion.” Mean reversion—the return to a
long-run trend—might occur due to measurement error or transient local
shocks. Either way, the more interesting part of the figure is seen in
the difference in growth rates between Cleveland and Detroit and
Pittsburgh and Buffalo. While Cleveland and Detroit show less than 20
percent growth in all of the upper five deciles, Pittsburgh and Buffalo
show much stronger growth rates in the top deciles (especially in the
top decile). The relatively stronger home-price growth rates in
Pittsburgh and Buffalo’s top deciles may be driven by increases in
educational attainment in neighborhoods close to these cities’ major
higher education institutions.
Overall, Cleveland experienced similar, although less severe,
patterns to those found in Detroit. Population declines were steepest in
the lowest-price tracts, while incomes fell most sharply in tracts in
the middle deciles. At the same time, none of the neighborhood deciles
in either city saw large increases in educational attainment.
These patterns are consistent with the patterns of urban decline (or
reverse gentrification) described in recent research by Veronica
Guerrieri, Daniel Hartley, and Erik Hurst. These researchers show that
this type of urban decline occurs when low (citywide) housing demand
leads to population loss in the lowest-price neighborhoods, and falling
prices allow lower-income households to move into formerly middle income
neighborhoods. As this happens, housing prices in those middle
neighborhoods fall (or rise less than in the other neighborhoods).
In contrast, despite similar declines in population across the
distribution of neighborhoods in Pittsburgh and Buffalo, these cities
experienced income growth in the top three housing-price deciles.
Underlying that achievement are large gains in educational attainment in
these neighborhoods. As a result, these neighborhoods also experienced
increases in home prices. These price increases may be due to the
increasing desirability of these neighborhoods as the neighborhood
residents become more highly educated (possibly influencing school
quality and other local public goods).
A Closer Look at the Cleveland Metropolitan Area.
For the remaining part of my analysis, I broaden the geographical
scope to look at the entire metropolitan statistical area (MSA), the
region around a city (or cities) that, practically speaking, is seen as
part of the same economic and social community. I limit my focus to
Cleveland, so that I can present maps of the area which reveal more of
the spatial details regarding how neighborhoods have changed in this
larger region from 1970 to the present. While the City of Cleveland has
been losing population since 1950, the combined population of the seven
counties of the MSA—Cuyahoga, Geauga, Lake, Medina, Portage, and
Summit—has been relatively stable. It dropped from about 3 million
residents in 1970 to 2.75 million in 1990 and went back up to 2.84
million in 2000. (I omit Ashtabula County, which is part of the
present-day Cleveland-Akron-Elyria combined statistical area, because
tract-level data are not available for Ashtabula in 1970.)
Figures 5–8 show how different variables are distributed across the
census tracts of the Cleveland-Akron-Elyria MSA. Each variable is broken
into 20 bins ranging from lowest to highest, dividing the set of census
tracts into 20 ranking groups based on the value of the variable.
In 1970 home prices in the City of Cleveland were uniformly lowest in
the neighborhoods closest to the center of the city and then a bit
higher in the neighborhoods that were farthest away from downtown
(figure 5). Prices generally rose as one crossed the border into the
inner-ring suburbs. In 1970 there were three groupings of
high-home-price census tracts: one in the western suburbs, one in the
southern suburbs, and one in the eastern suburbs.
By the time data was collected for the 2005–2009 American Community
Surveys, the high-housing-price areas had pushed outward a bit farther
from downtown Cleveland (figure 6). At the same time, the home-price
rankings of census tracts in a number of the inner-ring suburbs had
fallen dramatically. These changes are most striking in a group of
southeastern suburbs: Highland Hills, North Randall, Warrensville
Heights, Bedford Heights, Bedford, and Maple Heights. Less striking, but
similar patterns can be seen to the southwest in Parma, Parma Heights,
Brooklyn, Brook Park, Middleburg Heights, North Olmsted, Berea, Fairview
Park, and to the northeast in Euclid, South Euclid, East Cleveland, the
northern half of Cleveland Heights, Richmond Heights, Willowick, and
Wickliffe.
The same sets of suburbs that experienced a drop in home-price
ranking over this period also tended to experience large drops in their
household-income ranking (figure 7). In general, it appears that the
boundaries of the high-income areas that were present in 1970 have
pulled outward, away from downtown Cleveland.
A few notable exceptions to this pattern can be found in the southern
part of Cleveland Heights and in parts of Shaker Heights, possibly
bolstered by their proximity to cultural attractions in University
Circle and the Case Western Reserve University campus. A few other
pockets where housing prices and income rankings have not fallen by as
much as other places with similar proximity to downtown Cleveland
include Bratenahl and the northern part of Lakewood (which have the
amenity of being situated on the Lake Erie coastline), and Independence
and Valley View (situated along the Cuyahoga Valley National Park).
The Importance of Amenities.
Why do housing prices rise in neighborhoods where the average income
of the residents rises, and fall where income declines? One possibility
is that the housing stock in these areas changes. When higher-income
residents move in, for example, they might make improvements to the
housing stock, or when lower-income residents move in, they may be more
likely to defer home maintenance when finances are tight.
However, the change in housing prices might have more to do with
other kinds of neighborhood characteristics that change when the income
of the residents goes up or down. In the same way that natural amenities
like ocean views or pleasant weather conditions make an area more
desirable, living near high-income neighbors offers amenities that
affect the demand for housing in the neighborhood as well—good schools,
lower crime, greater entertainment options, and so on.
One way to explore how much those amenities are influencing housing
prices is to construct a measure that can tease out changes in home
prices which are not due to changes in the housing stock (and thus
reflect changes in land values). Figure 8 shows such a measure. It
controls for changes in the structural characteristics of the homes in
each census tract, such as the fraction that are single-family detached
houses, the number of bedrooms, and the average age of homes. Comparing
the map of changes in income to the map of changes in this land-value
measure reveals similarities in many places. In fact, at the
tract-level, the change in household income and the change in the
land-value measure have a correlation of 65 percent.
This correlation suggests that it is likely that changes in land
values are driven by changes in the features of neighborhoods that are
associated with the income of the residents, such as school quality,
crime rates, restaurants, and entertainment options. It is also
noteworthy that the maps of changes in income and land values also show
the retreat of the high-income areas deeper into the suburbs, but they
also indicate a little bit of gentrification in the Tremont, Ohio City,
and Edgewater neighborhoods, close to downtown Cleveland.
On the whole, the Cleveland MSA shows spatial patterns of urban
decline that are similar to other cities that have been affected by
large drops in labor demand, such as the retreating boundaries of the
high income areas. However, there do seem to be signs of gentrification
in a few neighborhoods, and resiliency to urban decline in another set
of neighborhoods. It also appears that high-income households have moved
further out into the countryside during this period.
Some of this movement may be due to households sorting into
jurisdictions that provide the mix of public goods and tax levels that
they prefer. Since the City of Cleveland has a relatively small
geographic footprint and there are many small cities and towns nearby,
different bundles of taxes and public good provision are readily
available.
Footnote
References
“Endogenous Gentrification and Housing-Price Dynamics,” Veronica Guerrieri, Daniel Hartley, and Erik Hurst, 2013.
Journal of Public Economics.
“Within-City Variation in Urban Decline: The Case of Detroit,” Veronica Guerrieri, Daniel Hartley, and Erik Hurst, 2012.
American Economic Review, 102:3.
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Common Stock Repurchases during the Financial Crisis
Summary: Large bank holding companies (BHCs) continued to pay dividends to their shareholders well after the onset of the recent financial crisis. Academics, industry analysts, and policymakers have noted that these payments reduced capital at these firms at a time when there was considerable uncertainty about the full extent of losses facing individual banks and the banking industry. But dividends are not the only means to return capital to shareholders; stock repurchases serve much the same function. In this post, I examine common stock repurchases by large BHCs during the financial crisis and show that they behaved very differently from common stock dividends during the same period. While dividends remained relatively constant through late 2008, common stock repurchases dropped quickly after the beginning of the financial crisis, consistent with their historically tighter sensitivity to current performance and financial conditions.
BHC Dividends during the Financial Crisis
Many analysts and researchers have noted that large BHCs did not reduce common stock dividends until the financial crisis was well under way. For instance, in a study examining capital at large U.S. and European banks, securities firms, and U.S. government-sponsored enterprises, Acharya, Gujral, Kulkarni, and Shin show that dividends at these firms did not decrease significantly until early 2009. In an October 2008 New York Times op-ed piece, Scharfstein and Stein argued that dividend payments by the largest U.S. BHCs would “redirect more than $25 billion of the $125 billion [in TARP capital] to shareholders in the next year alone.” Both sets of authors argued that continued high dividend payments undercut the capitalization of the U.S. banking industry during a time of stress. In 2011, the Federal Reserve implemented the Comprehensive Capital Analysis and Review (CCAR) to review planned dividend payments and other capital distributions by large BHCs to ensure that they would retain sufficient capital to withstand stressed economic and financial market conditions even after making such distributions to shareholders (see my earlier post for a description of how the CCAR addresses this objective).
Regulatory report data confirm the findings about dividends from these earlier studies. The first chart (below) shows the quarterly history of dividends declared by large U.S. BHCs—those with at least $10 billion in assets—from 2005 to the end of 2009. This period starts two years before the onset of the crisis in mid-2007 and extends until the beginning stages of the recovery at the end of 2009. (For consistency over the period, the sample excludes the large nonbank financial firms that became BHCs in early 2009.) As the chart shows, large BHCs made dividend payments in the range of $9 billion to $12 billion per quarter from 2005 to 2007, and while dividends declined over the course of 2008, they did not fall significantly below this level until early 2009, more than a year into the financial crisis.
Dividends Are Not the Whole Story
Focusing just on dividends misses an important part of the story, however. Stock repurchases—when a company buys its own common stock in public or private markets or by tender offer—are another important way that a firm can return capital to shareholders. Like dividend payments, stock repurchases disperse cash from the company to shareholders. Moreover, repurchases reduce the amount of common stock outstanding one-for-one, just as dividend payments do. Dividend payments reduce retained earnings and thus reduce (potential) common equity, while stock repurchases are a direct reduction in the outstanding amount of common equity.
The second chart (below) updates the first one to include common stock repurchases for the sample of large BHCs. Both dividend and repurchase information come from the quarterly FR Y-9C regulatory reports, which contain balance sheet and income statement information for BHCs. While the Y-9C reports collect dividends declared as a distinct line item, repurchases are not reported directly and must be inferred from other information contained in the report. For the second chart, I’ve used BHC purchases of treasury stock—common stock issued but not held by the public—as a proxy for common stock repurchases. This is a noisy measure of repurchases, as it may omit some repurchase activity that is reported as part of other Y-9C line items. However, it is a reasonable proxy that should capture the broad movements in repurchase activity.
The second chart illustrates several notable aspects of repurchase activity by large BHCs. First, in the period leading up to the financial crisis, stock repurchases were significant, averaging $7.5 billion per quarter and peaking at $12 billion in the first quarter of 2007. Stock repurchases were about two-thirds the size of dividend payments over this period, meaning that total distributions to shareholders were substantially higher than indicated by considering dividends alone. This is not something new in the banking industry. Some of my earlier research, which examined BHC stock repurchases during the 1990s, also found that stock repurchases rivaled dividends as a way for BHCs to return capital to shareholders. Second, share repurchases dropped sharply during the early phases of the financial crisis, several quarters before dividends were significantly reduced. Stock repurchases by large BHCs fell from their peak of $12 billion in the first quarter of 2007 to about $2 billion during the first quarter of 2008, and were at negligible levels after the middle of that year. As noted above, dividends did not decrease significantly until early 2009.
Because of the decline in repurchases, large BHCs’ overall capital distributions to shareholders declined steadily over the course of 2007 and 2008, a somewhat different picture than the one that emerges by looking at dividends alone. By the beginning of 2008, overall capital distributions had fallen below the levels that prevailed during the pre-crisis period. Even so, as the second chart illustrates, it was not until early 2009, when dividends also declined sharply, that overall distributions fell to the very low levels that ultimately prevailed for the remainder of the financial crisis and the period that followed.
Why Are Repurchases Different?
Why did stock repurchases fall earlier and more sharply than dividend payments? Part of the explanation is likely owing to the differing nature of dividends and share repurchases. Dividends are publicly visible actions requiring regular authorization by a firm’s board of directors. In the banking industry, large BHCs typically declare dividends quarterly and announced them publicly in press releases. In contrast, for all firms, stock repurchases are much less transparent. Firms have the ability to select the timing and amount of repurchases flexibly over time, subject to the details of their repurchase programs. Research on nonfinancial firms has documented that stock repurchases generally vary more over time than dividends, with repurchases used more frequently by firms with volatile earnings, especially following periods of higher-than-expected profitability. My earlier research on repurchases in the banking industry in the 1990s also found that repurchases seemed to rise following periods of higher-than-average financial performance. In contrast, dividends tend to be interpreted as signals of long-term profitability, decreasing only when profits seem likely to fall to a lower level for a sustained period of time.
Much further research is needed to come to a full understanding of the decisions BHCs made regarding dividend and repurchase activity during the financial crisis. The charts in this post and the results of previous research provide some insight, but there is significant room to explore issues such as concerns about signaling financial weakness during a time of uncertainty, the role of herding behavior in the timing and extent of dividend reductions, and the relative impact of market-wide versus firm-specific factors in decisions to cut back on stock repurchases. And, looking ahead, supervisory oversight via the CCAR and the adoption of new regulatory capital standards that explicitly require reductions in capital distributions as regulatory capital ratios fall below certain trigger points will significantly affect BHCs’ decisions about capital distributions. In sum, it is important to consider both dividends and stock repurchases in order to understand the impact of capital distributions on the banking industry, since large BHCs actively use both to manage their capital and distribute cash to shareholders.
Disclaimer
The views expressed in this post are those of the author and do not necessarily reflect the position of the Federal Reserve Bank of New York or the Federal Reserve System. Any errors or omissions are the responsibility of the author.