METROMONITOR METRO MONITOR 2 0 1 6
T R A C K I N G G R O W T H, P R O S P E R I T Y, A N D I N C L U S I O N I N T H E 10 0 L A R G E S T U . S . M E T R O P O L I TA N A R E A S
METROMONITOR MONITOR 2 0 METRO 1 6
T R A C K I N G G R O W T H, P R O S P E R I T Y, A N D I N C L U S I O N I N T H E 10 0 L A R G E S T U . S . M E T R O P O L I TA N A R E A S
BY RICHARD SHEARER, JOHN NG, ALAN BERUBE, AND ALEC FRIEDHOFF
JANUARY 2016
T H E B ROOKI N GS I N ST I T UT I ON | ME T ROPOLIT A N POLICY PROGRA M | 2 0 16
SUMMARY he slow and uneven recovery from the Great Recession of 2007 to 2009 has prompted leaders in the nation’s metropolitan areas to reexamine their economic development goals in the fac face e of fresh challenges. Successful Success ful economic development should put a metropolitan economy
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on a higher trajectory of long-run growth by improving the productivity of individuals and firms in order to raise local standar standards ds of living for all people. This means that, at least over the long term, metropolita metropolitan n areas should seek to achieve growth that also increase in creasess prosperit and inclusion. This report launches a new Metro prosperity y and Monitor that examines indicators within each of these three categories for the 100 largest U.S. metropolitan metropolitan areas, primarily from 2009 to 2014 during the economic recovery from the Great Recession. The Metro Monitor aims to advance new ways of measuring economic success in metropolita metropolitan n America, and provides provides criteria and data to help local and regional leaders understand whether economic development is yielding better outcomes. It finds that: 1. Economic growth was widespread but uneven among metropolitan areas during the economic
across metropolitan areas as increases in
From 2009 to 2014, 95 of the 100 largest recovery. From recovery.
economic growth. From 2009 to 2014, 63 of the
metropolitan areas saw increases in gross metro-
nation’s 100 largest metropolitan areas saw gains
politan product, jobs, and aggregate wages, and
in productivity, the average annual wage, and the
every large metropolitan area saw gains on at least
standard of living. Metropolitan areas with fast-
one of these three measures of economic growth.
growing technology sectors and those that special-
However, some places boomed while others grew barely at all. Metropolitan areas that specialize
ize in professional professional services saw especially large gains in these measures of prosperity. Metropolitan
in information technology, professional services,
areas in Central and Southern California, the
energy, and manufacturing saw especially strong
Intermountain Intermountai n West, and Florida, ranked among
growth. Growth was weaker over the course of the
the weakest performers on prosperity during the
recovery for metropolitan areas in the Sun Belt hit
economic recovery.
especially hard by the housing crisis and for most m ost metropolitan metropolit an areas in the Northeast.
B ROOKI N GS METROPOLITAN POLICY PROGRAM
2
2. Increases in prosperity were not as widespread
3. Compared to outcomes in growth and prosperity prosperity,,
prosperous by increasing productivity and aver-
improvements in inclusion proved more elusive
age wages. Few saw notable gains in both jobs
during the economic recovery recovery.. Only eight of the
and prosperity. And in most metropolitan areas,
nation’s 100 largest metropolitan areas registered
improvements improvemen ts in growth and prosperity did not
increases in their median wage and employment
coincide with better outcomes for middle- and low-
rate, and decreases in their relative income pov-
wage workers. Where they did, whites usually fared
erty rate, from 2009 to 2014. The median wage
better than people of color.
declined in 80 of the nation’s 100 largest metropolitan areas during this period. Even in metropolitan
This edition of the Metro Monitor advances new ways
areas where outcomes for middle- and low-wage
of defining and tracking economic success in metm et-
workers improved, improved, disparities between whites and
ropolitan America. It finds that most metropolitan
people of color often widened.
areas achieved robust growth during the economic recovery. However, economic growth alone, even
4. During the economic recovery thus far, few
growth that produces rising living standards, was not
metropolitan areas have achieved gains across
enough to assure better outcomes for all groups in a
METRO MONITOR:
From 2009 to growth, prosperity, and inclusion. inclusion. From
metropolitan metropolit an area during this period. If metropolitan metropolitan
TRACKING
2014, only nine large metropolit metropolitan an areas performed
leaders wish to sustain growth and further improve
GROWTH,
better than the large-metropolitan area average on
living standards, their growth strategies must incor-
PROSPERITY,
growth, prosperity, overall inclusion, and inclusion
porate deliberate efforts to ensure more people are
AND INCLUSION
by race. This suggests that places have followed different economic trajectories during the recov-
able to share in the benefits of economic growth and prosperity.
IN THE 100 LARGEST U.S.
ery. Some metropolitan economies grew larger by
METROPOLITAN
adding workers and jobs while w hile others grew more
AREAS
3
INTRODUCTION s 2016 begins, the state of the U.S. economy is strong in many respects. Output is expanding at a solid, though not spectacular, pace. Employers have added an average of more than 200,000 jobs per month over the past five years—the longest stretch of private-sector
A
job growth in the nation’s nation’s hist history ory.. As a result, the unemplo unemployment yment rat rate e has fallen tto o 5 percent. And home prices are up 25 percent from from their nadir in late 2011, a signifi-
cant rebound from one of the Great Recession’s most adverse shocks. Yet the work to rebuild the economy in the wake of the
Program has charted the geographica geographically lly uneven
global financial crisis and Great Recession is far from
nature of the recession and recovery through its
complete. Jobs remain short of pre-recession levels,
quarterly Metro Monitor, Monitor, which has illuminated quar-
after accounting for population growth. The share of
terly trends in output, jobs, unemployment, and home
adults in work is at a 30-year low. Poverty remains
prices in the nation’s largest metropolitan areas. This
high, wages have stagnated, and earnings for blacks and Latinos are lower than before the recession.
newly expanded edition of the Metro Monitor charts the performance of metropolit m etropolitan an areas across indicators in three broad categories: growth, prosperity, and
Metropolitan areas—the areas—the engines of the U.S. economy—
inclusion. And because progress toward many of these
have navigated this slow and uneven reco recovery very amid
outcomes happens over years rather than months, we
broader headwinds of globalization, technologic technological al
examine these trends in metropolitan areas over the
change, demographic change, and an increasingly
long, medium, and short terms of 10 years, five years,
constrained federal government.
and one year.
The events of the past several years have prompted
What follows is an initial exploration of the trends in
leaders in the nation’s metropolitan areas to ask
these three categories within and among the nation’s
tough questions about how best to grow their regional
100 largest metropolitan areas, a broad analysis that
economies. Faced with persistent economic and social
we intend to update annually. Throughout the year,
challenges in their communities, leaders are reexam-
the Metro Monitor series will feature more in-depth
ining the objectives of their economic development
analyses of the trends revealed here, including how
efforts.1 They know that in order to generate growth,
industry and demographic dynamics shape outcomes
their firms and industries must have the ability to
on these and other areas of metropolitan areas’ eco-
compete in a global economy. But ultimately, that
nomic performance. Maps, charts, and data from the
growth must deliver tangible results for workers, fami-
Metro Monitor are available through a web interac-
lies, and communities. And so leaders are searching
tive that allows users to explore these trends across
for new strategies that harness the unique industrial
metropolitan metropolit an areas and over time.
and social structures of their local economies to promote prosperity and inclusion, in addition to growth. To help inform these leaders’ efforts to shape an B ROOKI N GS METROPOLITAN POLICY PROGRAM
4
advanced economy that works for all, the Brookings Metropolitan Policy Program Program is launching a new series that examines metropolitan areas’ progress toward these goals.2 Since 2009, the Metropolitan Policy
C AT AT E G O R I E S A N D I N D I C A AT TORS he Metro Monitor measures the performance of the nation’s major met-
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ropolitan economies in three critical areas for economic development: growth, prosperity, and inclusion. 3 Successful economic developmen developmentt
should put a metropolitan econom economy y on a higher trajectory of long-run
growth (growth) by improving the productivity of individuals and firms in order to raise local standards of living ( prosperity prosperity ) for all people (inclusion).4 This Metro Monitor examines indicators indicators within each of these categories that help assess metropolitan areas’ progress toward shaping an advanced economy that works for all. While leaders can use the Metro Monitor as a guide to understanding the success of economic development efforts, efforts, it does not attempt to address all relevant dimensions of economic well-being (e (e.g., .g., public health outcomes or within-metro disparities by place) nor does it track critical inputs to that well-being (e (e.g., .g., educational attainment or access to capital) that often appear in regional indicators indicators.. METRO MONITOR:
This Metro Monitor, like its predecessor series, focuses
we measure that progress here. Thus, the largest,
TRACKING
on measuring the rate of change in these indicators
wealthiest,, or most inclusive metropolitan economies wealthiest
GROWTH,
over time in metropolit m etropolitan an areas, rather than their
may not top the Metro Monitor rankings if they are
PROSPERITY,
initial or final levels. Metropolitan areas differ greatly
not improving their performance in those categories
AND INCLUSION
in their overall economic size, the standards of living their residents enjoy, enjoy, and the disparities they exhibit
relative to their peers over the periods examined here: 10 years, five years, and one year. These time
IN THE 100 LARGEST U.S.
by race and income. Economic development seeks
periods are meant to capture progre progress ss over the long,
METROPOLITAN
to effect change in these levels over time; hence
medium, and short terms. 5
AREAS
5
GROWTH
➤
divided by the total number of jobs, from above,
Growth indicators capture net change in the total size
gives average average GMP per job, which is a crude mea-
of a metropolitan area’s economy. As a metropolitan
sure of a metropolitan economy’s productivity.
economy grows, it creates new opportunities for individuals and can become more efficient as it grows larger. The Metro Monitor measures growth in gross
➤
Change in gross metropolitan product (GMP)— Change
Similar to the national measure of gross domestic
of jobs, from above, gives the average annual wage per job in a metropolitan economy. ➤
capita, which reflects a metropolita metropolitan n economy’s
and services produced in a metropolitan econom economy y
average standard of living.
in constant dollars, including aggregate wages
➤
Change in aggregate wages—Aggregate wages Change
measures the total value of wages, salaries, and benefits paid to all workers in a metropolitan economy in constant dollars. ➤
Change in the number of jobs—Jobs measure Change
Change in the standard of living—GMP, from Change
above, divided by total population gives GMP per
product, GMP measures the total value of goods
paid to workers and the profits of firms.
Change in the average annual wage—Aggregate Change
wages, from above, divided by the total number
product, number of jobs, and aggregate wages paid to workers. ➤
—GMP, from above, Change in productivity —GMP, Change
Changes in these indicators are measured as the percent change in values from the initial to final year of analysis. Change in dollar-denominated indicator indicatorss is measured in real terms. Data on GMP, jobs, and aggregate income come from Moody’s Analytics. Data on population come from the U.S. Census Bureau’ Bureau’ss Population Estimates Program.
the total number of occupied full- and part-time employment positions in a metropolitan economy.
INCLUSION Changes in these indicators are measured as the percent change in values from the initial to final year of analysis. Change in dollar-denominated indicators is measured in real terms. Data on GMP, jobs, and aggregate wages come from Moody’s Analytics.
Inclusion indicators indicators measure how the benefits of growth and prosperity in a metropolitan economy— specifically,, employment and income—ar specifically income—are e distributed among people. Inclusive growth enables more people to invest in their skills and to purchase more goods and services.6 Thus, inclusive growth can increase human capital and raise the amount of demand,
PROSPERITY Here, prosperity refers to the wealth and income produced by an economy on a per-capita p er-capita or per-worker basis. When a metropolitan area grow growss by increasing the productivity of its workers, through innovation or by upgrading workers’ skills, for example, the value
boosting both prosperity and growth. Ensuring that all people can contribute to and benefit from growth and prosperity also helps sustain widespread support for the policies on which growth and prosperity depend.7 ➤
Change in the median wage—Median wage meaChange
sures the annual wage earned by the person in
of those workers’ labor rises. As the value of labor
the very middle of a metropolitan area’s income
rises, so can workers’ wages. Increases in productivity
distribution (among people at least 16 years old
and wages are ultimately what improve the economic
who have earned income in the last year).
well-being of workers and families. In these ways, prosperity indicators indicators together capture the quality of a B ROOKI N GS METROPOLITAN POLICY PROGRAM
6
metropolitan area’s economic growth from the standpoint of its workers and residents.
➤
Change in the relative income poverty rate— Change
Commonly used to measure poverty in other
countries, relative income poverty measures the share of people in a metropolitan economy who
➤
earned less than half of the local median wage
each of the inclusion indicator indicatorss are provided on the
(among people at least 16 years old who have
Metro Monitor website for each race and ethnicity
earned income in the last year).
noted above.
Change in the employment rate—The employChange
ment-to-population ment-to-populati on ratio measures the share of individuals aged 18 to 65 who are currently employed.8
COMPOSITE RANKS Metropolitan areas are assigned composite ranks for each category: growth, prosperity, inclusion, and
Change in median wage is measured as the percent
inclusion by race. Composite ranks are determined by
change, in real terms, in values from the initial to final
converting conv erting the change for each indicator in a category
year of analysis. Changes in relative income poverty
into a standard score. Standard scores measure how
and employment rates are measured as the percent
a given value varies from the average of a sample. A
change in the rates from the initial to final year of
metropolitan area’s scores on each indicator in a cat-
analysis. Data for inclusion indicators indicators come from
egory are summed, and the rank of the sum becomes
the Census Public-Use Microdata Series (PUMS) for
the composite rank for the category. Change for each
the 2000 Decennial Census and the 2006 to 2014
indicator is measured over three periods of time to
American Community Survey (ACS) 1-year estimates.
produce three composite ranks for each category:
Estimates derived from survey data come with
one year (2013–2014), five years (2009–2014), and
estimates of survey error, which are reported on the Metro Monitor website.
10 years (2004–2014). Because of data availability, inclusion and inclusion by race are ranked on 15 years of change from 1999 and 2014 rather than 10, as explained in the appendix. The sections below focus
INCLUSION BY RACE/ ETHNICITY
primarily on medium-term change in metropolitan metropolitan areas, the five-year period roughly corresponding to the economic recovery, while offering some analysis
These same inclusion indicators are also used to
of how metropolitan performance in these areas var-
assess differences in outcomes by race and ethnic-
ies across the three periods.
ity. The values of each of the three inclusion indicators were estimated separately for non-Hispanic whites and for people of color, a group that includes Hispanics, non-Hispanic blacks, non-Hispanic Asians, and people of other races or two or more races. The inclusion by race/ethnicity indicators measure the absolute difference between the estimates for each group on each inclusion indicator (median wage, relative income poverty rate, and employment rate), and metropolitan areas are ranked according to the percent change in those differences. For example, racial disparity in the median wage equals the absolute difference between the median wage among whites and the median wage among people of color. The Metro Monitor thus measures and ranks the percent change in this absolute difference across metropolitan areas
“Successful economic development should put a metropolitan economy on a higher trajectory of long-run growth (growth) by improving the productivity productivit y of individuals and firms in order to raise local standards of living (prosperity) for all people (inclusion).”
METRO MONITOR:
TRACKING GROWTH, PROSPERITY, AND INCLUSION
over time. This method does not capture differences in inclusion outcomes among individual racial and
IN THE 100 LARGEST U.S.
ethnic groups, because survey data are insufficient
METROPOLITAN
for many metropolitan areas. However, estimates for
AREAS
7
GROWTH conomic growth was widespread but uneven among metropolitan m etropolitan areas during the recovery from the Great Recession. Over the five years from 2009 to 2014, 95 of the 100 largest metropolitan area areass saw growth in
E
GMP, jobs, and aggregate wages. And every large metropolitan area saw
growth on at least one of these indicators. Howe However ver,, some places boomed while oth-
ers grew barely at all. Twenty metropolitan areas saw double-digit job growth rates from 2009 to 2014. In Austin, jobs grew by nearly 19 percent. But 10 metropolitan
areas saw job growth of less than 2 percent. Two of these, Wichita and Albuquerque, actually saw jobs decline. Trends in GMP and aggregate wage growth were similar. The unevenness of the recovery shows some notable
Tucson. In the central United States, the trade and
geographic and industry patterns. Metropolitan Metropolitan areas
distribution-oriented distribution-orient ed economies of Jackson, Memphis,
that specialize in information technology, professional services, energy, or certain types of manufacturing,
and St. Louis were some of the recovery’s weakestperforming metropolitan areas on growth measures.
like automotive or other high value-added durable
The manufacturing economies of the eastern Great
goods, ranked highly across growth measures from
Lakes, like those in Northeast Ohio or Upstate New
2009 to 2014 (Figure 1). In the West, coastal metro-
York, also saw weak recoveries. In most cases, the
politan areas like Seattle, Portland, San Francisco, and
slower growth of places in the Northeast reflects the
San Jose, and Intermountain West metropolitan areas
region’s longer-run growth trends rather than specific
like Provo and Denver, were among the nation’s stron-
post-recession post-rec ession dynamics.
gest performers on measures of growth during the recovery. These, along with other strong performers
For For the most part, these geographic trends in growth
in the West, such as Salt Lake City, Ogden, and Boise,
hold for each of the three time periods examined
have large information technology sectors, broadly
here: 10 years, five years, and one year. Only in Florida
defined. Energy- and information technology-focused
and California has the relative performance of met-
metropolitan areas in Texas also performed well on
ropolitan growth varied varied markedly from one period
growth measures. Several other strong-performing strong-performing
to another. Metropolitan areas in California’s Central
metropolitan areas contain large education or health
Valley and throughout Florida saw weak net growth
care sectors, such as Columbus, Louisville, Louisville, Madison,
over the 10 years from 2004 to 2014 but strong
and Nashville; others boast large manufacturing sec-
growth in more recent years during the recovery.
tors, like Grand Rapids, Indianapolis, and Detroit. To what extent these industrial specializations or other
The highest-ranking metropolitan areas on overall
factors ultimately drove above-average growth in
growth performance typically typically perform well on each of
these metropolitan areas deserves further study.
the three growth indicators: GMP, aggregate wages, and jobs. Places with strong job growth tend to see
B ROOKI N GS METROPOLITAN POLICY PROGRAM
8
Growth was weaker over the course of the recovery
strong wage growth, and places with strong wage
for many metropolitan areas areas in the Sun Belt and most
growth tend to see strong GMP growth. Metropolitan
of those in the Northeast. In Florida, Lakeland, Palm Bay, and Orlando—which were hit hard by the housing
areas that fit this pattern include those mentioned above with specializations in information technology,
bust—continued to struggle through the recovery. A
energy, or professional services. This reflects in part
similar pattern affected Albuquerque, Las Vegas, and
how growth indicators are mechanically related to one
Figure 1. Composite growth rankings among the largest 100 U.S. metropolitan areas, 2009-2014 ●
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Top 20
●
Upper 20
●
Middle 20
●
Lower 20
●
Bottom 20
Figure 2. Change in jobs and GMP across the 100 largest U.S. metropolitan areas, 2009-2014 35%
30%
P M G n i e g n a h c t n e c r e P
25%
20%
15%
10%
5%
0%
METRO MONITOR:
TRACKING -5%
GROWTH, -5%
0%
5%
10%
15%
20%
25%
Percent change in number of jobs Source: Brookings analysis of Moody’s Analytics estimates
30%
35%
PROSPERITY, AND INCLUSION IN THE 100 LARGEST U.S. METROPOLITAN AREAS
9
Table 1. Best- and worst worst-performing -performing metropolitan areas by change in growth, 2009–2014 Change in: Rank
MSA
GMP
Agg. Wages
Change in: Number of jobs
Rank
Top 20 1
San Jose, CA
2
Austin, TX
3
Houston, TX
4
Provo, UT
5
Nashville, TN
6
Grand Rapids, MI
7
Dallas, TX
8
MSA
Agg. Wages
Number of jobs
3.4%
4.7%
3.5%
4.5%
4.8%
2.7%
4.7%
2.8%
3.6%
GMP
Bottom 20
29.1%
38 3 8.5%
15 1 5.7%
81
Jackson, MS
31.6%
24 24.5%
1 18 8.8%
82
Philadelphia, PA-NJ-DE
26.6%
23 2 3.7%
1 14 4.1%
83
New Haven, CT
19.0%
21 21.1%
1 18 8.6%
84
Stockton, CA
2.4%
2.8%
5.1%
24.2%
18 1 8.8%
1 5. 5.7%
85
Rochester, NY
4.0%
3.5%
3.5%
1 17 7.7%
18.7%
15.0%
86
Las Vegas, NV
1.1%
1.4%
6.8%
22.8%
16 16.8%
1 11 1.9%
87
Deltona, FL
2.5%
4.2%
3.9%
San Antonio, TX
2 2. 2.7%
16.4%
12.1%
88
Harrisburg, PA
4.2%
6.4%
1.3%
9
San Francisco, CA
1 14 4.3%
22.4%
11.1%
89
Hartford, CT
1.7%
5.9%
3.2%
10
Charlotte, NC-SC
1 15 5.6%
18.1%
11.3%
90
St. Louis, MO-IL
5.4%
4.0%
1.7%
11
Charleston, SC
16.1%
14.6%
12.3%
91
Scranton, PA
4.5%
4.1%
1.6%
12
Cape Coral, FL
10.0%
13.7%
16.1%
92
Greensboro, NC
1.9%
5.3%
2.3%
13
Raleigh, NC
11.8%
18 18.2%
1 11 1.9%
93
Memphis, TN-MS-AR
2.1%
4.0%
2.0%
14
Denver, CO
13.0%
15 15.9%
1 12 2.1%
94
Tucson, AZ
5.9%
0.3%
0.8%
15
Portland, OR-WA
16 16.4%
15 1 5.5%
9.7%
95
Syracuse, NY
4.6%
1.1%
1.1%
16
Seattle, WA
14.7%
17.9%
8.9%
96
Lakeland, FL
-2.1%
4.0%
2.1%
17
Oklahoma City, OK
16.9%
16.3%
8.5%
97
Virginia Beach, VA-NC
1.7%
-0.5%
1.8%
18
McAllen, TX
18.8%
11 11.4%
1 10 0.2%
98
Wichita, KS
1.5%
1.5%
-0.8%
19
Bakersfield, CA
3.6%
18.8%
15 15.2%
99
Albuquerque, NM
2.5%
-2.3%
-0.4%
20
Columbus, OH
15.6%
13 13.9%
9.8%
100
Palm Bay, FL
-0.7%
-4.4%
0.4%
Source: Brookings analysis of Moody’s Analytics estimates
another: More jobs mean more wages paid to workers;
this period, but ranked 84th on GMP growth. Orlando,
and wages are a chief contributor to GMP. However, as
North Port, and Miami registered similar growth pat-
Figure 2 shows, there are exceptions.
terns. Meanwhile, Pittsburgh and Akron experienced the opposite: weak job growth but relatively strong
B ROOKI N GS METROPOLITAN POLICY PROGRAM
10
Metropolitan areas that ranked low on the composite
growth in GMP and aggregate wages. These differ-
growth rankings did not necessarily perform poorly
ences in performance on alternative measures of
on each indicator. Metropolitan areas in California’s
growth demonstrate that metropolitan areas experi-
Central Valley saw average growth in jobs and aggre-
ence different paths to growth. Prosperity indicators
gate wages from 2009 and 2014 but weak growth in GMP. Bakersfield, for instance, ranked sixth on
explored below reveal that some metropolitan areas, like Pittsburgh, grew their GMP by becoming more
job growth and seventh seventh on aggrega aggregate te wage gro growth wth
productive.. Other metropolitan areas increased GMP productive
among the 100 largest metropolit metropolitan an areas during
and aggregate wages by increasing the average wage.
PROSPERITY hile every large metropolitan area experienced experienced at least some modest growth in GMP, aggregate wages, or jobs, increases in prosperity were not as widespread. From 2009 to 2014, 63 of the nation’s
W
100 largest metropolitan areas saw gains in productivity, the
average annual wage, and the standard of living. Seven large metropolitan areas, by contrast, saw declines on all three indicators. Productivity increased almost 12 percent in San Jose. In Pittsburgh and Akron, where output grew ffast ast but jobs grew slowly during the recovery, productivity rose about 6 percent. Meanwhile, in Las Vegas, both productivity and the average wage fell by more than 5 percent. Bakersfield’s productivity fell by more than 10 percent. As with growth, metropolitan performance on pros-
and wage gains. Further north, Virginia Beach and
perity exhibits strong regional and industry patterns (Figure 3). Fast-growing technology strongholds such
Washington, D.C. saw declines on all three prosperity indicators during the recovery, which may reflect the
as San Francisco, San Jose, Seattle, and Portland
effects of recent pullbacks in government spending in
ranked similarly high on prosperity. Pittsburgh and
those metro areas.
Boston saw large gains on each prosperity indicator as well. These places also tend to specialize in profes-
Whereas metropolitan areas’ performance on growth
sional services, a sector that grew during the recession
was fairly consistent across the three periods (10 years,
and recovery and pays relatively well. Metropolitan
five years, and one year), their performance on pros-
areas in Texas and Oklahoma also saw strong gains
perity indicators often differed. Metropolitan areas in
in prosperity, indicating that gains from the energy
Texas and Oklahoma, along with Seattle, Portland, San
boom—particularly in the high value-added service
Jose, San Francisco, Boston, and Pittsburgh consis-
sectors supporting that boom—may have helped fuel
tently ranked among the strongest prosperity perform-
rising productivity and standards of living. While few of
ers in each window. Stockton, Las Vegas, Augusta, Palm
the traditional manufacturing strongholds of the Great
Bay,, Lakeland, and Cape Coral consistently ranked Bay
Lakes region ranked highly on measures of growth
among the weakest. However, outside of those places,
during the economic recovery, many did post relatively
metropolitan areas’ relative performance on prosperity
strong gains in prosperity. A similar pattern prevailed
shifted from one period to another. Continuous, com-
in mid-sized Northeastern metropolitan areas such as
prehensive improvements in prosperity were uncom-
Albany, Providence, Springfield, and Worcester.
mon. Only 37 of the nation’s 100 largest metropolitan areas posted improvements in all three prosperity
Metropolitan areas in the Sun Belt, especially Central
indicators across all three time periods.
and Southern California California,, the Intermountai Intermountain n West, and
METRO MONITOR:
TRACKING
Florida, ranked among the weakest performers on
A metropolitan area’s improvement on one measure
GROWTH,
prosperity during the economic recovery, reflecting
of prosperity was often accompanied by an improve-
PROSPERITY,
their difficulties in shifting from consumption- and
ment on another, at least over the medium to long
AND INCLUSION
housing-oriented economies towar toward d higher-value growth. Other places in the Southeast such as
run. From 2009 to 2014, productivity increased in 75 large metropolitan areas. Of these, 72 also saw
IN THE 100 LARGEST U.S.
Atlanta, Charleston, Charleston, and Raleigh that performed well
increases in the local standard of living—an indication
METROPOLITAN
on growth experienced more lackluster productivit productivity y
that rising productivity is linked to rising standards of
AREAS
11
Figure 3. Composite prosperity rankings among the largest 100 U.S. metropolitan areas, 2009-2014 ●
●
●
● ● ●
● ●● ● ●
● ● ● ●
● ●● ● ●
● ● ● ●● ●● ●● ●● ● ● ● ● ● ●● ●● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ●
●
●
●
●
● ●
●
● ●
●● ● ● ● ● ●● ● ● ● ●
●
● ●
●
●
●
● ● ● ● ● ●
●
●
●
Top 20
●
Upper 20
●
Middle 20
●
Lower 20
●
Bottom 20
● ● ●● ●● ● ●●
Figure 4. Change in productivity and average wage across the 100 largest U.S. metropolitan areas, 2009–2014 25% e g a w l a u n a e g a r e v a n i e g n a h c t n e c r e P
20%
15%
10%
5%
0%
-5%
-10% -15%
B ROOKI N GS METROPOLITAN POLICY PROGRAM
12
-10%
-5%
0%
5%
Percent change in productivit productivity y Source: Brookings analysis of Moody’s Analytics estimates
10%
15%
Table 2. Best- a nd worst-performing metropolitan areas by ch ange in prosperity prosperity,, 2009–2014 Change in:
Rank
Productivity
MSA
Avg. annual wage
Change in: Standard of living
Rank
Top 20
Avg. annual wage
Standard of living
-1.3%
0.4%
1.5%
0.4%
-1.4%
2.0%
2.9%
-1.9%
-0.7%
Productivity
MSA
Bottom 20
1
San Jose, CA
11.6%
19 1 9.7%
20 2 0.3%
81
Oxnard, CA
2
Houston, TX
10.9%
8.4%
13.6%
82
Columbia, SC
3
Austin, TX
10.8%
4.8%
14.0%
83
Albuquerque, NM
4
Detroit, MI
8.3%
1.7%
1 18 8.5%
84
Indianapolis, IN
-1.7%
0.4%
1.7%
5
Dallas, TX
9.7%
4.4%
12 1 2.0%
85
Jacksonville, FL
-1.4%
1.0%
-1.0%
6
Pittsburgh, PA
7.5%
6.2%
11.3%
86
Miami, FL
-2.1%
0.9%
-0.4%
7
El Paso, TX
9.7%
4.5%
10 1 0.7%
87
Orlando, FL
-1.8%
0.6%
-0.6%
8
Oklahoma City, OK
7.8%
7.2%
8.3%
88
Deltona, FL
-1.4%
0.3%
-1.0%
9
San Antonio, TX
9 .5% 9.
3.8%
11.0%
89
Augusta, GA-SC
-0.3%
-1.7%
0.1%
10
Nashville, TN
7.4%
2.7%
14.6%
90
Virginia Beach, VA-NC
-0 0..1%
-2 2..2%
-0. 0.9 9%
11
San Francisco, CA
10.1%
7.0%
91
Washington, DC-VA-MD
-0 0..3%
-0. 0.2% 2%
-3. 3.9% 9%
12
Seattle, WA
5.3%
8.2%
6.7%
92
North Port, FL
-2.5%
-2.2%
0.7%
13
Portland, OR-WA
6.1%
5.3%
9.4%
93
Fresno, CA
-3.7%
1.0%
-3.0%
14
Cleveland, OH
5.8%
4.6%
10.5%
94
Bakersfield, CA
-10.1%
3.1%
-1.7%
15
Madison, WI
5.9%
6.4%
7.3%
95
Lakeland, FL
-4.1%
1.9%
-7.7%
16
Boston, MA-NH
5 .9% 5.
5.7%
7.9%
96
Stockton, CA
-2 2..6%
-2. 2.2% 2%
-3. 3.1% 1%
17
Des Moines, IA
8.0%
3.0%
7.4%
97
Cape Coral, FL
-5 5..3%
-2. 2.1% 1%
-0. 0.9% 9%
18
Cincinnati, OH-KY-IN
6.1%
3.4%
9.3%
98
New Orleans, LA
-3 3..7%
-1 1..7%
-5. 5.1 1%
19
Columbus, OH
5.3%
3.8%
9.4%
99
Palm Bay, FL
-1 1..2%
-4. 4.8% 8%
-3. 3.4% 4%
20
Akron, OH
6.3%
2.6%
10.0%
100
Las Vegas, NV
-5 5..3%
-5. 5.0% 0%
-5. 5.3% 3%
2.9%
Source: Brookings analysis of Moody’s Analytics estimates
living. Only six metropolit metropolitan an areas saw the standard of living increase without an increase in productivity. Average wage gains tended to accompany larger increases in productivity. Of the 75 places that saw productivity increase during the recovery, 65 also saw the average wage increase (the upper right-hand quadrant of Figure 4). At the same time, the average wage rose in 16 of the 25 places that saw productivity fall, suggesting that, at least over the recovery, improvementss in pay were possible w improvement without ithout improvements in productivity.
“Whereas metropolitan areas’ performance on growth was fairly consistent across the three periods , their performance on prosperity indicators often differed.”
METRO MONITOR:
TRACKING GROWTH, PROSPERITY, AND INCLUSION IN THE 100 LARGEST U.S. METROPOLITAN AREAS
13
INCLUSION ompared to growth and prosperity, sustained improvements in inclusion proved more elusive during the economic recovery. In fact, only eight of the nation’s 100 largest metropolitan areas saw across-the-board improvements in the median wage, relative income poverty rate, and
C
Compared to their performance on growth and pros-
areas.11 However, this may reflect more of a bounce-
perity, metropolitan areas’ performance on inclusion
back from the devastating effects of the downturn
appears more idiosyncratic, and possibly driven by
than a surging ahead. Their longer-run performance
demographics as much as industry dynamics (Figure
on inclusion (1999 to 2014) was relatively weak.
employment rate from 2009 to 2014: Charleston, Chicago, Dayton, Denver, Provo, Salt Lake City, San Jose, and Tulsa.9 And only Baton Rouge, Honolulu, New Orleans, and Tulsa achieved achieved similar improv improvements ements over the full period from 1999 to 2014.10
5). During the recovery, for instance, metropolitan areas in the Great Lakes region that saw notable
On inclusion, a high ranking does not necessarily indi-
improvementss in prosperity also performed well on improvement
cate that a metropolitan area is becoming more inclu-
inclusion. They registered some of the largest increases
sive; indeed, it may simply not have fallen as far or as
in the employment rate and the largest decreases in
fast as its peers. From 2009 to 2014, the median wage
the relative poverty rate among large metropolitan
declined in 80 of the nation’s 100 largest metropolitan
Figure 5. Composite inclusion rankings among the largest 100 U.S. metropolitan areas, 2009–2014 ●
●
●
● ● ●
● ●● ● ●
● ● ● ●
● ● ● ● ● ●
● ●
●
●
● ●
● ● ● ● ●
POLICY PROGRAM
14
●● ● ● ● ● ●● ● ● ● ●
●
● ●
●
●
●
B ROOKI N GS METROPOLITAN
● ● ●● ● ● ●● ● ● ● ●● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ●● ● ●
●
●
●
●
●
●
Top 20
●
Upper 20
●
Middle 20
●
Lower 20
●
Bottom 20
● ● ●● ●● ● ●●
Figure 6. Change in median wage and relative income poverty across the 100 largest U.S. metropolitan areas, 2009–2014 20%
y t r e o v p e
15%
m 10% o c n i 5% e v i t a l 0% e r n i e -5% g n a h c -10% t n e c r -15% e P -20% -15%
-10%
-5%
0%
5%
10%
Percent change in median wage Source: Brookings analysis of American Community Survey microdata Note: A handful of metropolitan areas share a median wage change of -7 -7.5 percent. This clustering occurs because the American Community Community Surv Survey ey reports wages wages in rou rounded nded income c categories ategories.. Median wa wages ges calculat calculated ed from this d data ata also fall into these discrete categories. In some cases metropolitan areas that experienced only a small change in wage levels will have median wages that fall within the same income category in multiple years—essentially registering no change in median wages in nominal dollar terms. Once adjusted for ination, this apparent lack of change shows up as a decline of -7.5 percent over the ve-year period 2009-2014.
areas. The rate of relative income poverty increased
region such as Des Moines, St. Louis, and Wichita.16 In
in 53.12 And although 69 large metropolitan areas saw
California,, several places performed well on inclusion California
the employment rate increase from 2009 to 2014,
overall from 1999 to 2014 but lost ground from 2009
only 23 saw it increase from 1999 to 2014.13 Some 17
to 2014. Meanwhile, in the Southwest, Las Vegas,
metropolitan areas saw outcomes worsen on all three
Phoenix, Tucson, Albuquerque, and Colorado Springs
indicators from 2009 to 2014, and the same was true
consistently ranked among the bottom half of metro-
in fully 57 metropolitan areas from 1999 to 2014. 14
politan areas on inclusion outcomes.17
With even high-ranking metros struggling with
Trends in each of the three inclusion indicators at the
inclusivity, the outcomes in metropolitan areas that
metropolitan metropolit an level typically bear little relationship
ranked among the lowest were especially troubling.
to trends in the other indicators. An increase in the
The median wage declined, the relative poverty rate
median wage, which should indicate rising middle-
METRO MONITOR:
increased, and the employment rate fell between
class wages, seems to have little association with
TRACKING
2009 and 2014 in eight large Southern metro-
changes in the share of workers in relative income
GROWTH,
politan areas: Augusta, Birmingham, Chattanooga,
poverty,, who by definition earn less than half the poverty
PROSPERITY,
Greensboro, Jacksonville, Knoxville, Little Rock,
median wage (Figure 6). The relative income poverty
AND INCLUSION
and Winston-Salem. Winston-Salem. Kansas City also saw acrossthe-board declines on inclusion indicators during
rate fell in only 8 of the 20 large metropolitan areas that saw the median wage increase from 2009 to
IN THE 100 LARGEST U.S.
the recovery. Performance was not much better in
2014.18 Among the other 80 8 0 large metropolitan areas
METROPOLITAN
neighboring metropolitan areas in the Great Plains
that saw the median wage decline, 39 saw relative
AREAS
15
15
Table 3. Best- and worst-performing metropolitan areas by change in inclusion, 2009–2014 Change in:
Rank
Median Wage
MSA
Relative Income Poverty
Change in: Emp. Rate
Rank
MSA
Top 20
Emp. Rate
-0.4%
4.5%
-2.5%
-7.5%*
-4.9%
-2.7%*
-9.2%*
1.1%
0.9%
--6 6.9%*
1.3%
-0.7%
-7.5%*
1.5%
-0.3%
-4.3%
5.1%
-0.8%
-4.4%*
8.8%*
0.9%
-0.9%
3.5%
-3.7%*
Bottom 20
1
Tulsa, OK
2.8%
-1 -12.8%*
6.0%*
81
Chattanooga, TN-GA
2
Springfield, MA
-0.9%
-17.8%*
5.4%*
82
New Haven, CT
3
San Jose, CA
3.8%
-2.1%
5.4%*
83
Raleigh, NC
4
Grand Rapids, MI
-6.4%*
5.5%*
84
Sacramento, CA
5
Detroit, MI
-1.4%
-2.4%
7.7%*
85
Winston, NC
6
Charleston, SC
6.7%
-0.9%
3.5%*
86
Syracuse, NY
7
Denver, CO
5.9%*
--3 3.5%
2.4%*
87
Phoenix, AZ
8
Jackson, MS
-0.9%
-1 -11.1%*
2.9%
88
Little Rock, AR
9
Toledo, OH
-0.1%
-0.0%
7.4%*
89
Spokane, WA
-4.1%
-2.2%
-4.5%*
10
North Port, FL
- 0.4%
-4.9%
5.0%*
90
Riverside, CA
-7.9%*
-1.5%
-2.1%*
11 12
Provo, UT Greenville, SC
1.7% --0 0.1%
-3.7% 0.7%
3.9%* 6.5%*
91 92
Palm Bay, FL Des Moines, IA
-3.6% 3.7%
1.9% 16.2%*
-3.4% -1.3%
13
Baton Rouge, LA
-0.9%
-6.0%
2.6%
93
Colorado Springs, CO
-7.5%*
1.2%
-2.3%
14
Dayton, OH
2.8%
-6.3%*
0.1%
94
Wichita, KS
-7 7..5%* 5%*
-1 1..0%
-3.9% 3.9%**
15
Boise City, ID
3.6%
1.7%
3.0%
95
Jacksonville, Jacksonvil le, F FL L
- 7. 7.5%*
1.0%
-3.8%*
16
Cleveland, OH
-2.7%
-4.7%
3.7%*
96
Birmingham, AL
- 7. 7.5%*
5.5%
-2.5%*
17
Ogden, UT
-4.3%
-5.2%
3.8%
97
Las Vegas, NV
8.5%*
-1.1%
18
Oklahoma City, OK
0.2%
-0.6%
98
Columbia, SC
-13.9%* -1
3.4%
0.0%
19
Cincinnati, OH-KY-IN
-1.4%
-2.4%
3.0%*
99
Augusta, GA-SC
-4 4..0%
14. 14. 9% 9%*
-3.1% 3.1%
20
Youngstown, OH-PA
-4.1%
-5.0%
3.2%
100
Albuquerque, NM
1.4%
-6.6%*
-0.4%
Relative Income Poverty
Median Wage
6.7%*
-7.5%*
-10.1%*
* Denotes change that is statistically signicant at the 90 percent condence level. Source: Brookings analysis of Moody’s Analytics estimates
income poverty rates fall.19 Likewise, in only a little
less-experienced less-experien ced people earning relatively low wages
more than half (37 of 69) of metropolitan areas where
at entry level jobs. This could explain outcomes in
the employment rate rose during the recovery recovery did the
some Sun Belt metropolit m etropolitan an areas that are becoming
relative income poverty rate fall. 20
younger and more diverse. On the other hand, metropolitan areas where a rising portion of the workforce
B ROOKI N GS METROPOLITAN POLICY PROGRAM
16
Demographic factors as well as economic factors can
is well-educated may see a rising median wage and a
affect a metropolitan area’s performance on inclu-
falling rate of relative income poverty. This may help
sion indicators. For example, a metropolitan area that
explain the stronger performance of metropolitan
sees rising employment rates could also see a falling
areas such as Boise, Denver, Ogden, Provo, and Salt
median wage and a rising relative inco income me poverty
Lake City on inclusion indicators.
rate, if its rising employment is driven by younger,
INCLUSION BY RACE/ETHNICITY
ace is an important dimension of inclusion outcomes. Gaps in the median wage, relative poverty rate, and the employment rate among different racial and ethnic groups can indicate whether access to
R
opportunity is broadly shared throughout a metropolita metropolitan n area.
Disparities between whites and other groups widened
margin on all three indicators.24 On the other hand,
in most metropolitan areas during the recovery. The
just 19 metropolitan metropolitan areas e experienced xperienced widening gaps
median wage gap between whites and people of color
between whites and people of color across all three
grew in 58 of the nation’s 100 largest metropolitan
indicators. 25 Most metropolitan areas saw a combi-
areas from 2009 to 2014. 21 Similarly, the relative
nation of growing and shrinking gaps on racial and
income poverty rate gap between whites and people
ethnic inclusion.
22
of color grew in 69 large metropolitan areas. The gap between the share of working-age whites versus
Trends in the three racial inclusion indicators varied
working-age people of color who are employed grew
greatly across metropolitan areas. From 2009 to 2014,
in 33 large metropolitan areas. areas.
23
the gap between the median wage among whites ver-
As these trends suggest, relatively few large met-
sus people of color shrank by one-third in Salt Lake City, from $10,800 to $7,300. Meanwhile, in Madison,
ropolitan areas (21 overall) saw disparities between
that gap more than doubled, from $6,500 to $16,100 $16,100..
whites and other groups narrow by a significant
On rates of relative income poverty, the gap between
Figure 7. Composite racial inclusion rankings among the largest 100 U.S. metropolitan areas, 2009–2014 ●
●
●
● ● ●
● ●● ● ●
● ● ● ●
● ● ●● ● ●
● ● ● ● ●● ● ●● ● ●● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ●
●
●
● ●
●
●
● ●
●
●
●
●
● ● ● ● ●
●● ● ● ● ● ●● ● ● ● ●
●
●
● ●
●
METRO MONITOR:
● ● ●● ●● ● ●●
TRACKING GROWTH, PROSPERITY,
●
Top 20
●
Upper 20
AND INCLUSION
● ●
Middle 20 Lower 20
IN THE 100 LARGEST U.S.
●
Bottom 20
METROPOLITAN AREAS
17
Figure 8. Change in median wages among whites and people of color across the 100 largest U.S. metropolitan areas, 2009-2014 40%
g n o m a
30%
e g 20% a w r n l o a c i d o 10% e f m o e n l i p e o 0% g e n p a h c -10% t n e c r e -20% P -30% -20%
-15%
-10%
-5%
0%
5%
10%
15%
Percent change in median wage among whites
Source: Brookings analysis of Moody’s Analytics estimates
whites and people of color shrank by more than half
of color are most evident in median wage growth
in Chattanooga, from 14 to 6 percentage points.
(Figure 8). In Cleveland, the white median wage rose
But in San Diego, the same gap increased by nearly
8 percent between 2009 and 2014, but fell 7 percent
two-thirds, from 5 to 9 percentage points. Ogden
among people of color.27 Other metropolitan metropolitan areas
and Bakersfield had nearly closed the gap in employ-
that saw headline improvements in overall inclusion,
ment rates among races by 2014 after decreasing the
like Detroit and Columbus, also saw similar wage splits
disparity from 10 and 6 percentage points, respec-
between whites and people of color. 28
tively, to 1 percentage point each. In Washington, D.C., Meanwhile, gaps between whites and people of color
by contrast, that employment rate gap increased by 26
more than one-third, from 4 to 6 percentage points.
often shrank in metropolitan areas where overall inclusion outcomes deteriorated especially fast.
Surprisingly, many of the metropolitan areas that
This usually indicated that economic outcomes for
achieved the best outcomes in overall inclusion from
whites worsened more than those for people of
2009 to 2014 posted the worst outcomes in racial
color. Metropolitan areas like Bakersfield, Las Vegas,
and ethnic inclusion. This suggests that in metropoli-
McAllen, Oxnard, and Riverside-San Bernardino per-
tan areas where inclusion outcomes were relatively
formed poorly on overall inclusion during the recovrecov-
stable or improving, whites often benefited most. For
ery, yet posted strong showings on racial inclusion
example, metropolitan areas in the Great Lakes region
in each time period. In Bakers Bakersfield field and McAllen, the
that performed relatively well on overall inclusion
median wage among people of color rose even as the
saw stable or increasing median wage and employment rates for whites, but a falling median wage
median wage for whites remained flat. In Oxnard, the median wage fell 12 percent among whites and 8
and a falling employment rate for people of color.
percent among people of color, narrowing the consid-
The divergent outcomes between whites and people
erable gap from $19,600 in 2009 to $14,100 in 2014. 30
29
B ROOKI N GS METROPOLITAN POLICY PROGRAM
18
Table 4. Best- and worst-performing metropolitan areas by change in racial inclusion, 2009-2014 Change in:
Rank
Median Wage
MSA
Relative Income Poverty
Change in:
Emp. R Ra ate
Rank
MSA
Top 20 1
Cape Coral, FL
2
Las Vegas, NV
3
Bakersfield, CA
4
Chattanooga, Chattanoo ga, TN-GA
5
Salt Lake City, UT
6
Boise City, ID
-15.9%
7
Jackson, MS
-26.0%*
8
North Port, FL
9
McAllen, TX
10
Oxnard, CA
11
Indianapolis, IN
12
El Paso, TX
13
Atlanta, GA
14
Greenville, SC
15
Memphis, TN-MS-AR
16
Columbia, SC
17
Houston, TX
18
Jacksonville, FL
19
Palm Bay, FL
20
Tulsa, OK
Relative Income Poverty
Median Wage
Emp. Ra Rate
Bottom 20
-22.8%
-96.3%*
-88.2%
81
Cincinnati, OH-KY-IN
-7.5%
-50.2%*
-76.6%*
82
Cleveland, OH
-7.5%
-9.7%
-78.4%*
83
Springfield, MA
-19.6%
-54.9%*
-53.5%*
84
Colorado Springs, CO
-20.4%
-31.6%
85
Syracuse, NY
-46.6%
86
Columbus, OH
-30.0%
87
Portland, OR-WA
-0.3%
2.7%
96.3%
29.5%
17.8%
67.4%
54.1%
120.0%
22.5%
78.6%
85.9%
-9.4%
85.0%
8.4%
-9.8%
3.9%
34.2%
119.7%
45.3%
138.3%
78.3%
- 32.7%* -3
-26.4% -26.1%
45.3%* 45
99.6%
-17.5%
42.8%*
27.4%
-2.1%
20.2%
117.2%
32.7%
29.5%
171.2%
18.3%
10.0%
-3.0%
65.2%
58. 58.5% 5%**
114. 14. 1 1% %*
-1 12 2. 7% 7%
-19.1%
-49.0%
-38.4%
88
Worcester, MA-CT
-28.1%
-55.6%
-22.5%
89
Knoxville, TN
-18.4%
-31.7%
-36.8%
90
Youngstown, OH-PA
-19.6%*
-36.8%*
-34.4%*
91
Dayton, OH
-31.9%
36.4%
-20.9%
92
Greensboro, NC
-19.9%*
-32.4%*
-31.3%*
93
Harrisburg, PA
2.8%
14.7%
-69.4%*
94
Akron, OH
66.8%*
1 14 49.4%
45.8%
-14.6%
4.6%
-37.6%*
95
Madison, WI
146. 146.6% 6%**
210. 210.4% 4%
- 58. 58.4% 4%**
-20.0%
-0.6%
-17.8%
96
Allentown, PA-NJ
67.8%*
1371.7%
22.3%
1.7%
16.0%
-52.0%*
97
Spokane, WA
131.2%
12 21 1.4%
46.9%
4.0%
9.0%
-51.9%*
98
Deltona, FL
42.3%
23 37 7.5%
214.3%
4.8%
214.4%
-68.9%
99
Augusta, GA-SC
73.4%*
200.7%
249.3%
-7.5%
-46.8%
-27.0%
100
Lakeland, FL
5 52 202.8%
-32.0%
26.1%
* Denotes change that is statistically signicant at the 90 percent condence level. Source: Brookings analysis of Moody’s Analytics estimates
As with the overall inclusion indicators, relationships
rate but saw the gap in the relative poverty rate grow
among the three racial inclusion indicator indicatorss appear
between whites and people of color. Different factors
weak. As noted above, fewer than half of the nation’s
appear to influence outcomes for different racial and
100 largest metropolitan areas saw across-the-board
ethnic groups across the three economic inclusion
increases or decreases in indicator indicatorss of racial inclusion.
indicatorss in each metropolitan area. indicator
METRO MONITOR:
Many metropolitan areas exhibit strong performance
TRACKING
on one indicator of racial inclusion and weak perfor-
GROWTH,
mance on another. Tampa ranked eighth on reducing
PROSPERITY,
the gap in the employment rate betw between een whites and
AND INCLUSION
people of color from 2009 to 2014, but its sizable increase in the median wage gap ranked it 85th on
IN THE 100 LARGEST U.S.
that indicator. Dallas saw no significant change in
METROPOLITAN
racial disparities in the median wage or employment
AREAS
19
C A N M E T R O A R E A S A C H I E V E S U S TA TA I N A B L E GROWTH, PROSPERITY, AND INCLUSION?
R
ecent trends suggest that metropolitan areas can make progress toward growth, prosperity and inclusion at the same time. However, strong performance on all three outcomes at once is exceptional. From 2009 to 2014, only nine large metropolitan areas performed above
the average of all large metropolitan areas taken together on growth, prosperity, 31
overall inclusion, and inclusion by race overall race.. Four were in Texas and Oklahoma: Dallas, Houston, Oklahoma City, and San Antonio. Two were on the West Coast: San Jose and Seattle. And three were located in the Midwest: Grand Rapids, Rapids, Minneapolis St. Paul, and Louisville.
B ROOKI N GS METROPOLITAN POLICY PROGRAM
20
Metropolitan areas that sustained above-average
While few metropolitan areas performed consistently
performance on all these outcomes over the short,
above average on growth, prosperity, and inclusion
medium, and long terms were more exceptional still.
over time, few performed consistently below average
Over the one year from 2013 to 2014, nine metro-
as well. Over the year from 2013 to 2014, eight metro-
politan areas performed above average on all four
politan areas performed below the large metropolit metropolitan an
dimensions, and 14 did so over the long-term (2004
average aver age in all four areas: Baltimore Baltimore,, Birmingham,
to 2014 for growth and prosperity, and 1999 to 2014 for inclusion). But only two performed above average
Bridgeport, Colorado Springs, Knoxville, Madison, New Haven, and Washington, D.C. During the recovery
over the short term, the medium term, and the long
from 2009 to 2014, 12 places did. And over the long
term: Houston and San Jose.
term, 18 metro areas performed below average in all
Table 5a. Metropolitan areas that performed above the large metro average across every composite category, 2009-2014 Rankings MSA
Growth
Prosperity
Inclusion
Inclusion by Race
Dallas, TX
7
5
44
58
Grand Rapids, MI
6
22 22
4
42
Houston, TX
3
2
35
17
Louisville, KY-IN
33
30 30
45
28
Minneapolis, MN-WI
29
26 26
24
30
Oklahoma City, OK
17
8
18
35
San Antonio, TX
8
9
22
24
San Jose, CA
1
1
3
60
Seattle, WA
16
12 12
30
62
Source: Brookings analysis of Moody’s Analytics, Census population, and American Community Survey data
Table 5b. Metropolitan areas that performed below the large metro average across every composite category, 2009-2014 Rankings MSA
Albuquerque, NM
Augusta, GA-SC Baltimore, MD
Colorado Springs, CO
Greensboro, NC
Growth
Prosperity
Inclusion
Inclusion by Race
99
83
100
74
73
89
99
99
51
52
55
73
58
75
93
84
92
77
50
92
Knoxville, TN
55
54
69
89
Lakeland, FL
96
95
54
100
Richmond, VA
59
66
51
72
Spokane, WA
76
55
89
97
Syracuse, NY
95
57
86
85
Virginia Beach, VA-NC
97
90
78
69
Washington, DC-V DC-VA-MD A-MD
71
91
72
77
Source: Brookings analysis of Moody’s Analytics, Census population, and American Community Survey data
METRO MONITOR:
four categories. Yet only two large metropolitan areas
largest metropolitan areas saw either above-average
TRACKING
performed below-average in all four categories over
or below-average performance in all four categories.
GROWTH,
the short-, medium-, and long-term periods: Colorado
The other 79 metropolitan areas performed above
PROSPERITY,
Springs and Knoxville Knoxville..
average aver age in at least one category but below average
AND INCLUSION
These trends suggest that metropolitan areas typi-
in at least one other. And metropolitan areas’ performance tended to be similarly mixed over the short-
IN THE 100 LARGEST U.S.
cally saw mixed degrees of success on these different
and longer-term periods.
METROPOLITAN
outcomes. From 2009 to 2014, 21 of the nation’s 100
AREAS
21
Moreover, the statistical relationships between
increases in productivity or the average wage. So
metropolitan areas’ performance across categories
although more people became employed em ployed from 2009
were relatively weak. A metropolitan area that saw
and 2014 in Bakersfield, residents did not become
strong gains on growth, relative to its peers, did not
much more prosperous, on average. Other metropoli-
necessarily see similarly strong gains on prosperity prosperity..
tan areas achieved notable gains in prosperity despite
Similarly,, metropolit Similarly metropolitan an performance on prosperity
not adding many jobs. Pittsburgh ranked 73rd on job
did not tend to be associated with its performance
growth among the 100 largest metropolit metropolitan an areas
on inclusion.
from 2009 to 2014 but 30th on output growth, driven by rising average wages. Meanwhile, Akron’s above-
For example, 41 of the nation’s largest 100 metropoli-
average output growth was driven by increases in
tan areas performed above the average of their peers
both productivity and the average wage. 32
on growth during the recov recovery ery period. While most of these 41 also performed above-aver above-average age on inclusion
Regardless of whether a metropolitan economy grew
by race, only a little more than half out-performed
by adding workers and jobs or by becoming more
metropolitan averages on prosperity and overall inclu-
productive,, the gains from these outcomes in terms productive
sion. Likewise, 48 of the nation’s 100 largest metro-
of new employment and income often failed to boost
politan areas performed above average on prosperity
inclusion, the hardest outcome to achieve and sustain.
but only about half of these also performed above
The modest increases in prosperity, specifically in the
average on growth at the same time. About two-thirds
average annual wage, that most metropolitan areas
of those metropolitan areas performed better-thanaverage on overall inclusion, but their performance on
posted during the economic recovery seem to have disproportionately disproportionat ely benefited higher earners rather
growth and inclusion by race was more mixed.
than middle-or low-wage workers. Of the 81 metropolitan areas that saw an increase in the average
That metropolitan areas exhibited mixed degrees of
wage during the recovery, only one-fourth (20) saw
success on these different outcomes suggests that
the median wage rise as well, and fewer than half
they followed different paths toward their growth,
(38) achieved decreases in the relative poverty rate.
prosperity, and inclusion outcomes. Some, like
Even in places where outcomes in overall inclusion
Bakersfield, added workers. However, Bakersfield’s
improved, gaps between races often widened.
impressive job growth wasn’t accompanied by notable
“From 2009 to 2014, only nine large metropolitan areas performed above the average of all large metropolitan areas taken together on growth, prosperity, overall inclusion, and inclusion by race.”
B ROOKI N GS METROPOLITAN POLICY PROGRAM
22
CONCLUSION
conomic growth that improves standards standards of living for all people iiss pos-
E
sible, but not as common as one might hope. This new Metro Monitor finds that metropolitan economies can simultaneously achieve a higher trajectory traject ory of long-run growth, improve the productivity of individuals
and firms, raise local standards of living for all people and close gaps by race and income. However, only two of the nation’s 100 largest metropolitan areas consistently met that standar standard d over time, although several other metropolitan areas made progress on different timelines. These results suggest that economic growth alone,
use the Metro Monitor data platform to measure their
even growth that produces rising living standards,
current progress progress against past trends to better under-
does not reliably assure better outcomes for all
stand if they are succeeding at putting their metro-
groups in a metropolitan area. At the same time,
politan economies on a “higher trajectory of growth.”
some metropolitan areas have managed progress on prosperity and inclusion outcomes in the absence of
Over the next several months, the Brookings
robust growth, a path that merits deeper scrutiny,
Metropolitan Metropolit an Policy Program w will ill publish additional
especially for slower-growing areas of the country.
analyses as part of the Metro Monitor series to help metropolitan leaders explore whether they are
METRO MONITOR:
Above all, this Metro Monitor aims to advance new
improving the trajectory of their local economy. These
TRACKING
ways of measuring economic success in metropolitan
analyses will seek to help these leaders understand in
GROWTH,
America, and its interactive website offers new tools
greater depth the factors and trends that contribute
PROSPERITY,
for helping leaders chart their progress. This analysis
to or hinder progress toward continuously increas-
AND INCLUSION
provides metropolitan metropolitan leaders with ways of benchmarking the economic progress of their place against
ing growth, prosperity, and inclusion in metropolitan America, and how new models of economic develop-
IN THE 100
peers over three time periods. However, this is not the
ment can help deliver an advanced economy that
METROPOLITAN
only lens that matters. Metropo Metropolitan litan leaders can also
works for all.
AREAS
LARGEST U.S.
23
APPENDIX his study uses Census Bureau microdata to examine inclusion outcomes in metropolitan areas, including by race. It uses microdata from the 2000 Decennial Census from the University of Minnesota’s Integrated
T
Public Use Microdata Series (IPUMS). 33 Data from the 2000 Decennial
Census were collected in 1999 and all estimates refer to that year. It also uses microdata from the 2006 to 2014 American Community Survey (ACS (ACS), ), which come from the Census Bureau’s ACS Public Use Microdata Sample (PUMS) files.34 Data from the ACS 1-year estimates were collected throughout the course of the year in question but refer to the survey respondent’s employment status and wages during the last 12 months.
GEOGRAPHIES
SAMPLING ERRORS
Each observation in the microdata from the Decennial
As a survey of a sample of the U.S. population, the
Census and ACS is assigned to a unit of geography
ACS is subject to sampling error. Moreover, to avoid
called a Public Use Microdata Area (PUMA). PUMAs
disclosing the identities of survey respondents, the
represent the smallest, most detailed level of geog-
Census Bureau releases a subset of the full ACS
raphy available available in the public use files, with each
sample for public use. This means that the PUMS-
PUMA covering an area of at least 100,000 residents
based estimates are doubly subject to sampling error error..
to preserve survey respondents’ anonymity. PUMAs
Measures of this error were computed as part of this
do not overlap; they fully partition each state into
study to assess statistical significance of estimates.
contiguous areas. Depending on the population in Population and wage variables required different
a region, PUMAs can encompass entire counties 35
and groups of counties or cover part of a county.
methods of calculating standard errors. For the
As such, PUMAs can be grouped into near (but not always perfect) approximations of metropolitan areas.
employment-to-population employment-t o-population ratio and relative income poverty rate, standard errors were calculated using
This can be achieved by assigning PUMAs to counties,
Census-provided replicate weights. Standard errors
and counties to metro areas. PUMAs were assigned
for the median wage were calculated using the Census
to metropolitan areas for this study using the Office
Bureau’s design factors methodology.
of Management and Budget’s Budget’s 2013 metropolita metropolitan n area
B ROOKI N GS METROPOLITAN POLICY PROGRAM
24
definitions. The Census Bureau changes its PUMA
Each observation in the ACS microdata stand in for
definitions ever few years. For each year of data, we
a variable number of people, depending on demo-
assigned PUMAs to metropolitan areas using the
graphic characteristics characteristics of the individuals sampled.
Office of Management and Budget’s 2013 metropoli-
Weights are assigned to each respondent that repre-
tan area definitions.
sent the number of people for whom he or she stands
in. The ACS microdata files come with 80 sets of these weights, each of which is an alternativ alternative e weight. These replicate weight estimates often differ from estimates computed using the main weights. To calculate standard errors, we computed estimates for each replicate weight, in addition to the reported estimate calculated using the main set of weights. We then find the variability between the reported estimate and the 80 replicate estimates to compute a standard error for the metric.36 Replicate weights generally provide approximations of standard errors that are more accurate than weights derived using the design factors methodology. However, replicate weight standard errors for the median wage can sometimes take on a value of zero due to rounding in the wage levels reported in the ACS. To circumvent this, we use the design factors methodology to calculate standard errors for the median wage. The design factors method for the median wage is a multiple-step procedu procedure re that begins with computing an initial estimate of the standard error and confidence interval based on inputs such as the number of people in a demographic group and a “design factor” constant that is specific to geography and year. Income levels and their corresponding distributional percentiles percentiles matching the upper and lower bounds of the confidence interval are then used to arrive at the final standard error. 37 We then transform standard errors for median wage levels to compute the appropriate standard errors for the percent change and mean absolute differ difference ence in the median wage.38
METRO MONITOR:
TRACKING GROWTH, PROSPERITY, AND INCLUSION IN THE 100 LARGEST U.S. METROPOLITAN AREAS
25
education or well-paying jobs, peoples’ health can suffer. In a 2015 study, economists Anne Case and Angus Deaton argue that the shrinking employment opportunities and low incomes that are part and parcel of the nation’s increasing inequality have led to the rising morbidity and mortality rates observed among lower-educated middle-aged non-Hispanic whites. The authors show that these deteriorating health outcomes have contributed to declining employment rates and costly public fiscal transfers. Some economists have also suggested that inequality can decrease consumption or, worse, lead to unsustainable borrowing that threatens financial stability. Economists at the Federal Reserve Bank of St. Louis and Washington University in St. Louis argue in a 2014 study, “Inequality, the Great Recession, and slow recovery,” that slow income growth and rising inequality prompted excessive borrowing by many Americans in the years leading up to the Great Recession, and that this borrowing was a contributing cause of the recession and slow recovery.
ENDNOTES 1.
Brookings Brookings’’ Metro Metro Solutions website contains stories, lessons, and resources from metropolitan metropolitan areas that are advancing the things that matter: making investments, building networks, and launching and stewarding stewarding initiatives that create an advanced economy that fuels economic growth, income, and opportunity. It is available at http://www.brookings.edu/research/ reports2/2016/01/metropolitan-solutions-map .
2.
For more information about the need to build an advanced economy that works for all, see “Achieving an Advanced Economy that Works for All: The Brookings Metropolitan Policy Program in 2016 and Beyond,” available at http://www. brookings.edu/research/papers/2016/01/06-advancedeconomy-for-all-metropolit economy-f or-all-metropolitan-policy-progr an-policy-program-berube am-berube.
3.
The Metro Monitor uses the U.S. Office of Management Manageme nt and Budget’s 2013 Metropolitan Statistical Area definitions for the entire period of analysis and identifies the 100 largest U.S. metropolitan areas based on their population in 2010 as reported in the 2010 Decennial Census.
4.
This definiti definition on of “successful economic development” development ” is adapted from arguments put forward in a 2014 report to the U.S. Economic Development Administration authored by Maryann Feldman and others titled, “Economic Development: A Definition and Model for Investment.” It is also influenced by Michael Spence’s discussion of the economic and political dynamics of growth and development in his 2012 book, “The Next Convergence: the Future of Economic Growth in a Multispeed World.” The definition used here, however, is our own.
5.
As with any analysis o off change change ove overr time, this Metro Monitor analysis is sensitive to the choice of the start and end dates. Our choice of 2014 as the end year for the analysis reflects availability of the most recent, complete data for most of the indicators used here. Our choice of start years was influenced by a desire to assess progress not from one month or one quarter to the next, but over the longer periods of time that capture broader economic transformation. However, using fixed 10-, five-, and one-year increments does not allow us to capture the differentt timing and impact of business cycles upon metropolitan differen economies’ performance. For instance, metropolitan areas that reached their economic low point in 2009 may look stronger over the 2009 to 2014 period relative to metropolitan areas that bottomed out either before or after 2009. Similarly, the 2004 to 2014 period begins at some metropolitan areas’ pre-reces pre-recession sion high point, like Detroit and New Orleans, which may make their 10-year growth look more modest relative to metropolitan areas that reached their peaks later on. The Metro Monitor series website contains a more detailed look at metropolitan areas’ economic progress progress within and across these time periods.
6.
B ROOKI N GS METROPOLITAN POLICY PROGRAM
26
Most economists reason that some inequality is necessary to provide incentives and rewards for the innovation and entrepreneurship that propel growth. However, many recent studies suggest that inequality can impair growth if incomes among a large enough segment of society become so low that individuals cannot make the necessary investments in themselves to stay healthy and productive. If an individual does not have access to the education required to be productive in a wellpaying job, he or she will have to accept a lower-paying job or no job at all. If many people lack this access, the economy as a whole might face imbalances in the supply of skills and flow of incomes. In their book, “The Race between Education and Technology,” economists Claudia Goldin and Lawrence Katz find that a slowdown in the growth of educational attainment after 1980 limited growth in the supply of skills in the United States, leading to a surplus of low-skilled workers, a dearth of higherskilled ones, and a rise in wage polarization. Goldin and Katz blame this slowdown on limited financial access to increasingly expensive post-secondary education required by so many jobs in today’s economy, among other factors. Without access to
7.
Economic inclusion may be important to sustain both politica politicall and fiscal support for growth-oriented policies. International Monetary Fund economists Andrew Berg and Jonathan Ostry, in a paper entitled, “Inequality and unsustainable growth: Two sides of the same coin?” find a positive relationship between a country’s level of income inequality and the likelihood that its economic expansion will end, and point to several political channels that could mediate that relationship. A 2014 report by the credit rating agency Standard and Poor’s titled, “How increasing income inequality is dampening U.S. economic growth, and possible ways to change the tide,” found that increasing income inequality inequality in the United States poses a risk to some states’ Thethat Case and Deaton study mentioned the prior notefinances. also shows the deteriorating health of less-in educated middle-aged Americans—which the authors attribute to rising inequality—can contribute contribute to rising government expendituress on Medicare, Medicaid, and Social Security expenditure Disability Insurance. Insurance.
8.
We refer to this indicator—the indicator— the employment-to-populati employment-to- population on ratio— as the “employment rate” in the text, for narrative ease. In labor market economics, the term “employment rate” is used to indicate the share of the labor force in work, and is thus different from the employment-t employment-to-population o-population ratio.
9.
Due to sample siz size e limitations limitations in the American American C Community ommunity Survey data, margins of error for inclusion and inclusion by race/ethnicity measures can be large for some metropolitan areas. In such cases, changes over time are not statistically significant and so cannot be stated with certainty. Of the eight metropolitan areas that experienced improvements in all three inclusion indicators, none experienced statistically significant improvements improvemen ts across the board at the 90 percent confidence level.
10. Of the four four metropolitan areas that saw improvements improvements across the three inclusion measures, improvements improvements were statistically significant only in Tulsa and Honolulu. 11.
Out of the 16 metropolitan areas in the Great Lakes region, region, 15 experienced improvements in their employment rates between 2009 and 2014. These improvements were statistically significant in eight cases. Similarly, nine metropolitan areas in the Great Lakes region saw decreases in the relative income poverty rate; these decreases were statistically significant in two cases.
12. Of the 80 metropolitan areas that saw saw a decline decline in the median wage, the decline was statistically significant in 28 cases. Of the 53 metropolitan areas that saw an increase in the relative income poverty rate, the increase was statistically significant in nine cases. 13.
Of the 69 69 metropolit metropolitan an areas that saw a an n increase increase in the employment rate between 2009 and 2014, the increase was statistically significant in 25 cases. Of the 23 metropolitan areas that saw an increase in the employment rate between 1999 and 2014, the increase was statistically significant in 18 cases.
14. Of the 23 metropolitan areas in which outcomes declined across across all three inclusion indicators between 2009 and 2014, none experienced statistically significant deteriorations across all indicators.. Of the 57 metropolitan areas that saw outcomes indicators worsen across all indicators between 1999 and 2014, 23 saw statistically significant deteriorations in all three indicators. 15. The decline in median wages was was statistically significant in in Birmingham, Jacksonville, and Winston-Salem. The Increase in the relative income poverty rate was statistically significant in Augusta. The decline in employment rate was statistically significant in Birmingham, Jacksonville, and Little Rock. 16. Wichita an and d St. Louis Louis saw statistically significant declines declines in median wages. Des Moines experienced a statistically significant increase in the relative income poverty rate. Wichita saw a statistically significant decrease in its employment rate rate.. 17.
Albuquerqu e, Colorado Springs, Las Vegas, and Phoenix all saw statistically significant declines in median wages. Las Vegas and Phoenix experienced a statistically significant increase in the relative income poverty rate. Albuquerque saw a statistically significant decline in its employment rate while Tucson saw a statistically significant improvemen improvement. t.
18. Of the 20 metropolitan areas that saw an increase in median wages, three saw a statistically significant increase increase.. In none of the eight metropolitan areas that saw both an increase in median wages and a decline in relative income poverty wer were e the changes statistically significant on both counts. 19. Of 80 metropolitan areas that saw in median decline, declin thethe decline was statistically significant 28 of wages them. Of the e, 39 metropolitan areas that experienced both declining median wages and relative income poverty rates, two experienced statistically significant declines in both indicators. 20. Of the 69 metropolitan areas that saw employment rates increase, 25 experienced a statistically significant increase. Of the 37 metropolitan areas that experienced both increasing employment rates and declining relative income poverty rates, three experienced statistically significant changes in both indicators. 21.
Nine of these 58 metropolitan areas sho showed wed a st statistically atistically significant increase in racial disparities in median wage.
22. Seven of these 69 metropolita metropolitan n areas showed a statistically statisti cally significant increase in racial disparities in relative income poverty. 23. One of these 33 metr metropolitan opolitan areas sho showed wed a statistically significant increase in racial disparity in the employment rate. 24. Only two of these 21 metropolita metropolitan n areas saw statistically significant decreases across all three racial inclusion measures.
30. The decrease in white white median wages was was statistically significant significant in Oxnard; the decrease in median wages for people of color was not statistically significant in this metropolitan area. 31.
In this Metro Monitor Monitor,, “above-average performance” refers to composite scores that are greater than zero in a given category. As explained in the section on categories and indicators, composite ranks are determined by calculating the standard score on each indicator in a category and then summing the scores. Standard scores measure a value’s variance or “distance” from the average of a sample. In this analysis, a weighted average for all large metropolitan areas is used to calculate standard scores for each indicator. Thus, a standard score of zero for a given indicator would mean that a metropolitan area’s performance performance was identical to that of all 100 large metropolitan areas taken together. By summing the standard scores across indicators indicators in a category and comparing that sum to zero to determine above- or below-average performance, we are generalizing about performance across indicators. A metropolitan area could have a standard score of less than zero on one indicator in a category but a composite score for the category that is greater than zero.
32. This analysis of how productivity and average wages contributed to GMP growth decomposes nominal changes in productivity and average wages into what they would have been absent job growth, growth, and then assesses assesses the contribution contribution of each subcomponent, including job growth, to nominal changes in GMP. 33. Integrated Public-Use Microdata Microdata Series provided provided by the Minnesota Population Center at the University of Minnesota, available at https://www.ipums.org / (accessed October 2015). 34. U.S. Census Census Bureau American Community Survey Public Use Microdata Sample, available at https://www.census.gov/ programs-surveys/acs/data/pums.html (accessed October 2015). 35. For more information, see https://www.census.gov/programssurveys/acs/technical-documentation/pums/about. html and https://usa.ipums.org/usa-action/variables/ html PUMA#description_section 36. For a detailed description of the replicate weights methodology, see pages 12–14 in http://www2.census.gov/programs-surveys/ acs/tech_docs/pums/accuracy/2014AccuracyPUMS.pdf 37 37.. For a detailed description of the design factors factors methodology as applied to estimates of a median, see pages 16–17 in http:// www2.census.gov/programs-surveys/acs/tech_docs/pums/ accuracy/2014AccuracyPUMS.pdf 38. For instructi instructions ons on transforming standard errors for derivative derivat ive measures, see http://www2.census.gov/programs-surveys/ acs/tech_docs/statistical_testing/2014StatisticalTesting1y ear.pdf
25. None of these 19 me metropolitan tropolitan are areas as saw a statistically significant increase across all three racial inclusion measures. 26. All instances o off changes in this par paragraph agraph were statistically statistically significant. 27. 27. The increase in the median wage ffor or whites was statistically significant; the decrease for people of color was not statistically significant.
METRO MONITOR:
TRACKING 28. The increas increase e in white median wage wagess was statistically signifi significant cant in Detroit but not Columbus; the decrease in median wages for people of color was statistically significant in Columbus but not Detroit.
GROWTH, PROSPERITY, AND INCLUSION
29. Neither changes in median wages for whites nor for people of color were statistically significant in Bakersfield and McAllen.
IN THE 100 LARGEST U.S. METROPOLITAN AREAS
27
ACKNOWLEDGMENTS This publication has been made possible thanks to the commitment and financial support of The Ford Foundation. Fou ndation. The authors thank their colleagues at the Brookings Metropolitan Policy Program for their input on the design of this analysis and their comments on an earlier draft of this report. The authors also thank Elena Casanovas and Johnathan Guy for their excellent research assistance.
F O R M O R E I N F O R M AT AT I O N Richard Shearer Senior Research Analyst and Senior Project Manager 202.741.6597
[email protected] Alan Berube Senior Fellow and Deputy Director 202.797.6075
[email protected]
ABOUT TH E METRO POLITAN POLICY PROGRA M AT B R O O K I N G S The Metropolitan Policy Program at Brookings delivers research and solutions to help metropolitan metropolitan leaders build an advanced economy that works for all. To learn more visit www.brookings.edu/metro www.brookings.edu/metro.. The Brookings Institution is a nonprot organization devoted to independent research and policy solutions. Its mission is to conduct high-quality, independent research and, based on that research, to provide innovative, practicall recom practica recommendations mendations ffor or policymak policymakers ers and the pu public. blic. The co conclusions nclusions and recomm recommendations endations o off any Brookings publication are solely those of its author(s), and do not reect the views of the Institution, its man agement, or its other scholars. Brookings recognizes that the value it provides is in its absolute commitment to quality, independence, and impact. Activities supported by its donors reect this commitment.
B ROOKI N GS METROPOLITAN POLICY PROGRAM
28
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