Brooking's Metro Monitor Report

 

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

T

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-

T

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 ●

●

●

● ● ●

● ●● ● ●

● ● ● ●

● ● ●●  ● ●

● ● ● ●● ●● ●● ●● ● ● ● ● ● ●● ● ● ●● ● ●   ● ● ● ● ● ● ● ● ●● ● ●

●

●

● ●

●

●

● ●

 

●

●

●

●

●

● ● ●   ● ● ●

●● ● ● ● ● ●● ● ● ● ●

●

●

● ● ● ●●● ● ●●

●

●

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 ination, 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 signicant at the 90 percent condence 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 signicant at the 90 percent condence 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 nonprot 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 reect 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 reect this commitment.

B ROOKI N GS METROPOLITAN POLICY PROGRAM

28

 

BROOKINGS

1775 Massachusetts Avenue, NW Washington D.C. 20036-2188 telephone 202.797 202.797.6000 .6000 fax 202.797.6004 web site www.brookings.edu

telephone 202.797 202.797.6139 .6139 fax 202.797.2965 web site www.brookings.edu/metro