This benchmarking study, developed by the Brookings Metropolitan Policy Program, provides the Greater Charlotte region with a framework and data to better understand its performance and position in the global economy, offering information and insights to help leaders more actively shape the region’s economic strategy.

1. GREATER CHARLOTTE IN
THE GLOBAL ECONOMY
BENCHMARKING THE REGION’S GLOBAL
COMPETITIVENESS ASSETS
1
Brookings Metropolitan Policy Program
March 23, 2016

2. Major forces necessitate global economic engagement
2
Intensifying Globalization
The cross-border flow of goods,
capital and services has exploded
in recent decades…
1980 2012
$26 trillion
$3 trillion
36% of
global GDP
Significant Global Demand
…and foreign markets continue to
drive global economic growth
86%of global economic growth will occur
outside the United States from 2015
to 2020
Sources: James Manyika and others, “Global Flows in a Digital Age,” McKinsey Global Institute, 2014; World Economic Outlook, International Monetary Fund, 2016.

3. Metropolitan economies must compete globally
3
Taking part in global markets is no longer a choice for metropolitan leaders.
City and regional leaders can either seize the opportunities afforded by the
global dynamics or risk falling victim to the downsides of globalization.
This benchmarking study analyzes Greater Charlotte’s competitive position
through four factors—trade and investment, innovation, talent, and
infrastructure—compared to 19 other city-regions that most closely resemble
Greater Charlotte’s size, wealth, productivity, industrial structure, and
competitiveness factors.
Trade Innovation Talent Infrastructure
Regional Competitiveness Framework

4. 4
Melbourne
Peer metro areas
Birmingham
Frankfurt
San Antonio
Minneapolis
Dallas
Kansas City
Indianapolis
Cleveland
Atlanta
Montreal
Hamburg
Stockholm
Copenhagen
Zurich
Munich
Denver
Phoenix Austin

5. Bottom Line – Charlotte’s competitive position
5
Economic performance: Overall economic growth has been robust over the past
decade, but on metrics of inclusion Greater Charlotte has lagged.
Trade and Investment: Greater Charlotte is very globally-oriented. Exports and
foreign direct investment account for a disproportionate share of the regional
economy, led by tradable anchors like machinery, transportation equipment, and
financial services.
But the region is at risk of losing ground to peer metropolitan economies unless it
shores up its competitive drivers:
• Innovation: Build up very low levels of research and development, technology
commercialization, and venture capital investment;
• Talent: Help employers overcome challenges in filling job vacancies, especially
occupations that require STEM skills; and
• Infrastructure: Address lagging broadband speeds and disparities in broadband
access by income.

6. 1 | Economic Performance

7. Greater Charlotte is a wealthy region
7
$126.2 billion
Metropolitan GDP per Capita
61st wealthiest metro in the world
$53,142
Metropolitan GDP
107th largest metro in the world
Definition: 10-county
metropolitan statistical area
2.4
million
Source: Brookings analysis of Moody’s Analytics data.

8. Metro Monitor: 3 elements of economic performance
8
Growth indicators capture net change in the total size of a metropolitan area’s economy.
We measure growth through the change in total jobs, change in gross metropolitan
product (GMP), and change in aggregate wages.
Inclusion indicators measure how the benefits of growth and prosperity in a metropolitan
economy—specifically, employment and income—are distributed among people. We
measure inclusion by the change in the median change, change in the relative income
poverty rate, and the change in the employment-to-population ratio.
Prosperity refers to the wealth and income produced by an economy on a per-capita or
per-worker basis. We measure prosperity through the change in GMP per job, change in
the average annual wage, and change in GMP per capita.
Source: Richard Shearer and others, “Metro Monitor 2016” (Washington: Brookings Institution, 2016).

9. Greater Charlotte’s economy has grown rapidly
9
1 year
Source: Brookings Metro Monitor.
5 years 10 years
Jobs
(100 metro rank)
+3.6% (13th)
Gross Metro
Product
(GMP)
(100 metro rank)
+3.0% (22nd)
Aggregate
Wages
(100 metro rank)
+5.1% (17th)
OVERALL
GROWTH
(100 metro rank)
+11.3% (14th)
+15.6% (17th)
+18.1% (10th)
+15.3% (16th)
+23.5% (18th)
+23.3% (20th)
10th17th 18th

10. But growth in prosperity metrics has slowed
10
1 year
Source: Brookings Metro Monitor.
5 years 10 years
Average
Wage
(100 metro rank)
+1.4% (50th)
GMP Per
Capita
(100 metro rank)
+1.1% (51st)
GMP Per
Worker
(100 metro rank)
-0.6% (74th)
OVERALL
PROSPERITY
(100 metro rank)
+6.1% (8th)
+6.6% (35th)
+3.9% (36th)
+6.9% (34th)
-2.5% (73rd)
+7.1% (33rd)
21st59th 50th

11. And growth has not necessarily been inclusive
11
1 year
Source: Brookings Metro Monitor.
5 years 10 years
Employment/
Population
(100 metro rank)
+1.4% (39th)
Median
Wage
(100 metro rank)
-1.3% (68th)
Rel. Poverty
Rate
(100 metro rank)
+1.2% (73rd)
OVERALL
INCLUSION
(100 metro rank)
+1.2% (44th)
-7.5% (84th)
-2.0% (36th)
-4.6% (82nd)
-10.0% (86th)
+12.9% (92nd)
59th65th 95th

12. Bottom Line – Economic performance
12
Growth has been strong. Since 2004 and in the aftermath of the recession,
overall growth in jobs, output, and aggregate wages has been among the top fifth
of U.S. metropolitan areas.
Prosperity has improved as well, but not as rapidly as overall growth. Output
per capita, output per worker, and average yearly wages have all expanded, but
less so in the past year.
Inclusive growth remains elusive, however. Over the past ten years, the
employment-to-population ratio and the median wage have both declined, and the
relative income poverty rate has increased.

13. 2 | Global Trade and Investment

14. Two components of global economic orientation
Exports are sales of goods and services to foreign
entities (people or companies).
14
1
2 Foreign direct investment arises when a foreign entity
invests in a business enterprise in the United States.
Source: Emilia Istrate and Nicholas Marchio, “Export Nation 2012: How U.S. Metropolitan Areas are Driving National Growth” (Washington: Brookings Institution, 2012).; Dwight Perkins, Steven Radelet, and
David Lindauer, “Investment, Productivity, and Growth.” In Economics of Development: Sixth Edition. (New York: W.W. Norton & Company, 2006).

15. Why exports matter
15
Exports are driving economic growth and wage gains.
Share of
Job Growth
‘09-’14
Share of GDP
Growth ‘09-
’14
8.1%
27.0%
Services
Trade
Wage
Premium
Manuf. Trade
Wage
Premium
20.0%
17.0%
Middle market firms benefit from exports.
More likely to grow revenue (76 percent of exporters vs. 64 percent of non-
exporters)
More likely to add employees (51 percent of exporters vs. 39 percent of non-
exporters).
Source: Moody’s Analytics; Brookings, “Export Nation,” 2014. J. Bradford Jensen, “Global Trade in Services,” Petersen Institute for international Economics, 2011; David Riker, “Do Jobs in Export Industries
Still Pay More?”, International Trade Administration, 2010. Brookings, National Association for the Middle Market, “Accelerating Exports in the Middle Market,” 2014. The Middle Market is defined as
companies with annual revenues between $10 million and $1 billion.

16. Greater Charlotte’s economy is export-intensive
Greater Charlotte relies upon exports for a greater share (14 percent) of its
economic output than any U.S. peer metro area, as exports have grown faster
than the economy as a whole since 2003. Exports supported more than 110,000
jobs in 2014.
16
Exports, GDP, and jobs, Greater Charlotte and peer regions
Metro Area
Export share of
GDP, 2014
Change in Export
Share GDP, 2003-
2014
Gross exports
(USD billion),
2014
Annualized
Export Growth,
2003-14
Annualized GDP
Growth, 2003-14
Total Jobs
Supported by
Exports, 2014
Change Total
Export Jobs,
2003-2014
Charlotte 14.0% 5.1% 17.7 5.7% 2.3% 110,043 40,973
Indianapolis 13.3% 4.0% 15.0 4.1% 1.7% 81,619 18,693
Dallas 13.2% 4.3% 54.9 7.0% 3.0% 315,544 106,507
Cleveland 11.7% 3.2% 13.6 2.6% 0.5% 81,371 9,007
Kansas City 9.6% 3.4% 10.2 4.8% 1.1% 64,588 18,235
Minneapolis 9.6% 2.5% 20.3 4.0% 1.1% 132,698 21,655
Austin 9.2% -0.7% 10.0 6.3% 4.2% 62,113 10,956
Atlanta 9.0% 3.1% 26.6 4.6% 1.3% 188,807 56,222
San Antonio 8.9% 4.1% 9.2 8.2% 2.8% 57,160 26,061
Phoenix 8.9% -1.6% 18.4 1.4% 1.7% 123,392 -18,814
Denver 8.0% 2.7% 13.6 5.6% 2.2% 94,701 29,740
Source: Brookings analysis of data from Census, BEA, Moody’s analytics, BLS, NAFSA, IRS, EIA, and Sabre.

17. Adv. manufacturing/financial services drive exports
Machinery, chemicals, transportation equipment, and financial services,
contributed 63 percent of export growth between 2008 and 2014.
17
Greater Charlotte exports by sector, 2014, and contribution to export growth, 2008-2014
Source: Brookings analysis of data from Census, BEA,
Moody’s analytics, BLS, NAFSA, IRS, EIA, and Sabre.

18. Why foreign direct investment matters
18
Global investment flows are growing. Worldwide foreign direct investment has
increased from just over $200 billion in 1990 to $1.2 trillion in 2014.
Foreign-owned firms pay higher wages. Average wages in foreign-owned firms
are $77,000 versus $60,000 in domestic firms.
U.S.
workers
U.S. goods
exports
5.0%
20.3%
Foreign-owned firms contribute disproportionately to export and innovation
capacity by transmitting new technologies and corporate best practices.
U.S.
corporate
R&D
18.9%
Foreign firms
share of:
Source: Brookings analysis of UNCTAD, WTO and ITC, based on Eurostat, OECD, IMF, UNSD, and other international and national sources; Bureau of Economic Analysis.

19. Greater Charlotte’s economy is FDI-intensive
Greater Charlotte relies upon foreign firms for a greater share (6.8 percent) of its
employment base than any peer metro area. However, Charlotte is one of only
two U.S. peer metros where FDI’s share of employment has declined since 1991.
19
Jobs in foreign-owned establishments (FOEs),
Greater Charlotte and peer regions, 2011
Metro Area
Share of
Jobs in
FOEs Jobs in FOEs
Charlotte 6.8% 48,810
Atlanta 6.8% 134,611
Indianapolis 6.5% 49,910
Kansas City 5.6% 47,371
Dallas 5.2% 134,111
Minneapolis 5.0% 75,593
Denver 4.8% 50,099
Austin 4.6% 29,180
Cleveland 3.9% 34,010
Phoenix 3.7% 55,742
San Antonio 3.0% 21,576
Change in share of jobs in foreign-owned establishments
(FOEs), Greater Charlotte and peer regions, 1991-2011
Charlotte 8.2%
6.8%
Atlanta 5.6%
6.8%
Indianapolis
3.7%
6.5%
Kansas City
3.2%
5.6%
Dallas 4.8%
5.2%
Minneapolis
4.2%
5.0%
Denver 4.5%
4.8%
Austin 2.7%
4.6%
Cleveland 5.6%
3.9%
Phoenix 3.8% 3.7%
San Antonio
2.4%
3.0%
1991 2011
Source: Brookings analysis of D&B / NETS, BEA, and Moody’s Analytics data

20. FDI mainly arrives thru new establishments (Greenfield)
20
New establishment openings (e.g. Greenfield) accounts for one-third of Greater
Charlotte’s FDI, the second highest share among peer U.S. peer metro areas. Nearly
half (48 percent) of FDI comes from just four European countries, led by Germany.
17.7%
24.4%
25.4%
26.3%
26.9%
27.0%
28.0%
29.4%
29.8%
33.3%
36.9%
26.8%
39.0%
25.8%
36.5%
30.1%
28.4%
30.2%
37.7%
32.1%
27.8%
28.2%
55.5%
36.5%
48.8%
37.1%
43.0%
44.5%
41.8%
33.0%
38.2%
39.0%
35.0%
Minneapolis
Atlanta
Austin
Dallas
Cincinnati
Indianapolis
Kansas City
Phoenix
Denver
San Antonio
Greenfield M&A Before 1991
Share of FOE jobs by mode of entry, Greater
Charlotte and peer regions, 1991-2011
FOE jobs by source country, thousands, Greater Charlotte,
2011
Charlotte
7.8%
8.3%
10.9%
12.9%
15.4%
0 2000 4000 6000 8000
Canada
France
Belgium
England
Germany
Total FOE Jobs
Share of
FOE Jobs
Source: Brookings analysis of D&B / NETS, BEA, and Moody’s Analytics data

21. $386
$443
$567
$603
$673
$787
$882
$896
$1,065
$1,170
$1,348
$1,456
$1,662
$1,688
$1,887
$2,462
$2,614
$2,867
$3,563
$5,511
Cleveland
Minneapolis
Denver
Phoenix
Kansas City
Dallas
Hamburg
Indianapolis
San Antonio
Munich
Copenhagen
Atlanta
Stockholm
Frankfurt
Montreal
Zurich
Melbourne
Birmingham (UK)
Austin
But recent FDI flows are about average
21
Since 2009, Charlotte ranks tenth of 20 global metros in total Greenfield FDI
flows per capita, led by sectors such as automotive, engines/turbines, industrial
machinery, renewable energy, and textiles.
Greenfield foreign direct investment per person, Greater Charlotte and peer regions, 2009-2015
Charlotte
Automotive
16%
Turbines
11%
Machinery
8%
Renewables
8%
Textiles 7%
Rest 50%
Greenfield FDI, Top Sectors, 2009-2015
Source: Brookings analysis of fDi Intelligence data.

22. Bottom Line – Trade and Investment
22
Exports and foreign direct investment account for a significant share of Greater
Charlotte’s economy. The region is the most export-intensive and FDI-intensive metro area
among its U.S. peer group.
Key traded sectors like financial services, management consulting, and advanced
manufacturing anchor exports and FDI.
However, in the global competition for Greenfield FDI, Greater Charlotte is about average
compared to all its global peer metro economies.
Greater Charlotte’s unique reliance on global markets demands a sharp focus on the assets that
determine global competitiveness: innovation, talent, and infrastructure.
Lower Higher
Trade and Investment CLT ATL ATN BIR CLE CPN DAL DEN FRT HAM IND KC MEL MPLS MON MUN PHX SA STK ZUR
Export share of GDP, 2014 1 8 7 - 4 - 3 11 - - 2 5 - 6 - - 10 9 - -
% change in export share of GDP, 2003-2014 1 7 10 - 6 - 2 8 - - 4 5 - 9 - - 11 3 - -
Annualized export growth, 2003-2014 4 7 3 - 10 - 2 5 - - 8 6 - 9 - - 11 1 - -
Share of jobs in foreign-owned establishments (FOEs), 2011 1 2 8 - 9 - 5 7 - - 3 4 - 6 - - 10 11 - -
Change in share of jobs in FOEs, 1991-2011 10 4 3 - 11 - 7 8 - - 1 2 - 5 - - 9 6 - -
Greenfield FDI per capita, 2009-2015 10 8 1 2 20 9 15 18 6 14 13 16 3 19 5 11 17 12 7 4
Peer Rank
CLT = Charlotte CPN = Copenhagen IND = Indianapolis MUN = Munich
ATL = Atlanta DAL = Dallas KC = Kansas City PHX = Phoenix
ATN = Austin DEN = Denver MEL = Melbourne SA = San Antonio
BIR = Birmingham (UK) FRT = Frankfurt MPLS = Minneapolis STK = Stockholm
CLE = Cleveland HAM = Hamburg MON = Montreal ZUR = Zurich

23. 3 | Innovation

24. Why innovation matters
24
Innovative capacity matters because it is the most durable economic advantage
for firms and regions in advanced economies. It is a critical input to
competitiveness, and an important driver of rising productivity which, in turn,
generates increases in living standards.
But research suggests that a few things influence the quality of innovation
ecosystems: research and development (R&D), commercialization of that R&D
into new products and services (e.g. patents), the presence of entrepreneurial
activities that are linked to technology development, and advanced industrial
production.
Innovation takes many forms, and includes improvements in products, services,
processes, and management techniques. It can be hard to measure and even
harder to predict.
Source: For a full review of the role of innovation in metropolitan growth, see George Washington Institute of Public Policy and RW Ventures, “Implementing Regionalism.”

25. $0.25
$0.28
$1.69
$1.93
$2.39
$2.63
$2.73
$3.00
$3.67
$3.68
$3.79
$4.03
$4.25
$4.93
$6.11
$6.54
$7.47
$7.86
$10.42
Kansas City
Dallas
Phoenix
San Antonio
Indianapolis
Denver
Birmingham (UK)
Frankfurt
Munich
Minneapolis
Cleveland
Hamburg
Atlanta
Melbourne
Austin
Stockholm
Montreal
Copenhagen
Charlotte
R&D expenditures significantly trail peer metros
25
A wide literature confirms that research activities help advance economic
development. Greater Charlotte ranks second to last among its global peers in
university R&D expenditures, both overall and business-funded.
All R&D Conducted at Universities per $1,000 of
GDP, 2013 or latest year available
Business-Funded R&D Conducted at Universities per
$1,000 of GDP, 2013
$0.01
$0.01
$0.06
$0.09
$0.10
$0.12
$0.13
$0.13
$0.27
$0.30
$0.70
Kansas City
Phoenix
Dallas
Cleveland
San Antonio
Minneapolis
Indianapolis
Atlanta
Denver
Austin
Charlotte
Source: NSF Higher Education Research and Development Survey data.

26. Charlotte lacks a major scientific research institution
26
Unlike its peer metros, Charlotte does not house a research institution ranked in the top
750 in the world by CWTS and Leiden University in terms of scientific impact. UNC-
Charlotte is the region’s most significant research asset.
Number of universities in CWTS/Leiden University
Top 750 List, 2010-2013
Higher Education R&D Expenditures, Top Source by
Metro, FY2013
5 Melbourne Montreal
Stockholm
4 Dallas
3
Atlanta Copenhagen
Frankfurt2
Birmingham Munich
San Antonio Zurich
1 Austin Cleveland Denver Hamburg Indianapolis
Kansas City Minneapolis Phoenix
0 Charlotte
Rank Institution Metro Area
R&D expenditures
(millions USD)
15 University of Minnesota Minneapolis $858,378
23 Georgia Institute of Technology Atlanta $730,488
31 University of Texas Austin $634,132
45
University of Texas
Southwestern Medical Center
Dallas $440,620
50
Case Western Reserve
University
Cleveland $425,788
52 University of Colorado Denver $409,443
53 Arizona State University Phoenix $405,154
70
Indiana University-Purdue
University
Indianapolis $332,760
113
University of Texas Health
Science Center
San Antonio $175,983
236 University of Missouri Kansas City $28,829
246 University of North Carolina Charlotte $24,764
Source: Brookings analysis of Centre for Science and Technology Studies (CWTS) and Leiden University data and NSF Higher Education Research and Development Survey data.

27. 2.0
2.8
3.9
4.8
4.8
5.0
5.1
5.2
5.8
6.4
7.0
10.6
10.8
11.4
13.9
14.2
17.4
19.7
22.4
24.8
San Antonio
Kansas City
Melbourne
Birmingham (UK)
Montreal
Atlanta
Phoenix
Dallas
Denver
Hamburg
Cleveland
Indianapolis
Austin
Zurich
Frankfurt
Munich
Copenhagen
Minneapolis
Stockholm
Charlotte’s patenting intensity lags peers
27
Total patenting has increased in Greater Charlotte over time, but the region still
trails global peers in commercialization. In the 2008 to 2012 period, Charlotte
produced 3.9 patents per 10,000 residents, third to last among peers.
Patents per 10,000 inhabitants, 2008-2012Total patents, Greater Charlotte,1977-2012
Charlotte
20 27
92
299
504
829
1,010
1977-1982 1983-1987 1988-1992 1993-1997 1998-2002 2003-2007 2008-2012
Source: Brookings analysis of OECD REGPAT data.

28. IT and manufacturing generate most patents
28
Charlotte’s largest technology families are information technology, advanced
manufacturing, life sciences, and energy.
Top Patenting Technology Groups, Greater Charlotte Region, 2008-2012
Rank Tech Subgroup Tech Family Patents
1 IT methods for management Information technology 121
2 Computer technology Information technology 110
3 Medical technology Life sciences 69
4 Civil engineering Energy and infrastructure 47
5 Materials, metallurgy Advanced manufacturing 44
6 Control Precision systems 44
7 Other special machines Advanced manufacturing 41
8 Chemical engineering Advanced manufacturing 40
9 Optics Precision systems 33
10 Measurement Precision systems 33
Source: Brookings analysis of OECD REGPAT data.

29. 37
35
29
28
25
15
14
13
10
5
1
Minneapolis
Cleveland
Kansas City
Indianapolis
Dallas
Phoenix
Atlanta
San Antonio
Denver
Austin
Startup activity trails most U.S. peer metros
29
Entrepreneurship enables innovation by translating new ideas into market-ready
products and services. Charlotte ranked 25th (of 40 metros) in the Kauffman
Foundation’s 2015 Startup Activity Index.
Startup Activity Rank, Kauffman Foundation, 2015
Charlotte
Components of Startup Activity Index
The Kauffman Index Startup Activity ranks forty large
metro areas in 2015 based on three metrics:
• Rate of new entrepreneurs—percent of adult
population that became entrepreneurs in a given
month calculated as a 3-year moving average;
• Opportunity share of new entrepreneurs—percent of
new entrepreneurs who were not unemployed
before starting their business calculated as a 5-year
moving average;
• Startup density—number of startup firms per
100,000 resident population defining a startup as
firms less than one-year old employing at least one
person besides the owner.
Source: The Kauffman Index: Startup Activity 2015.

30. $42
$67
$85
$86
$174
$293
$407
$474
$478
$510
$527
$583
$605
$766
$882
$919
$1,056
$1,085
$1,471
$4,084
Birmingham (UK)
Hamburg
Melbourne
Frankfurt
San Antonio
Munich
Phoenix
Kansas City
Zurich
Cleveland
Indianapolis
Montreal
Copenhagen
Dallas
Atlanta
Stockholm
Minneapolis
Denver
Austin
Very few Charlotte firms attract venture capital
30
Venture capital (VC) provides funds for innovative enterprises positioned for high
growth and the potential to create and capture new markets. VC firms stimulate
local economies; they are three to four times more patent-intensive than other
firms, and are much more likely to translate R&D into high-growth ventures.
Total venture capital investments per capita, Greater Charlotte and peer metros, 2005-2014
Charlotte
Top industries, by venture capital
investment, Greater Charlotte, 2005-2014
Rank Industry
Total VC Investment
(millions USD)
1 Software $72.37
2 Healthcare Services $59.93
3 Commercial Products $58.30
4 Other Financial Services $44.09
5 Commercial Services $42.94
6 Media $36.38
7 Chemicals $19.95
8 Services (Non-Financial) $16.27
9 Pharma and Biotech $16.07
10 Consumer Durables $11.70
Source: S. Kortum and J. Lerner, “Assessing the Contribution of Venture Capital to Innovation.” Rand Journal of Economics 31(2000), 674-92; Dirk Engel and Max Keilbach, “Firm Level Implications of Early
Stage Venture Capital Investment—An Empirical Investigation.” (Max Planck Institute of Economics, 2002). Brookings analysis of Pitchbook data.

31. Advanced industries: America’s “tech” super-sector
31
Advanced industries are technology-intensive manufacturing and services
industries, and their profile and performance provide a helpful measure of the
nation’s “tech” sector at its broadest.
Why Advanced Industries Matter
50 industries across manufacturing, services, and
energy, account for the U.S. share of:
2.7
Jobs R&D
8.9%
90.3%
Patents
81.2%
GDP
17.9%
Exports
57.5%
Defining Advanced Industries
50 industries across manufacturing, services, and
energy that meet two criteria:
$450
Minimum share of workers in industry
whose occupations require a high
degree of STEM knowledge
21 percent
Minimum industry R&D per worker, 80th
percentile of industries
Source: Mark Muro and others, “America’s Advanced Industries” (Washington: Brookings Institution, 2015).

32. Charlotte has a diversity of advanced industries
32
Charlotte’s advanced industries range from high-end services to advanced
manufacturing to energy generation and distribution. This mix provides a range of
employment opportunities at different wage and education levels.
Ten largest advanced industries by employment, Greater Charlotte, 2014
Rank Advanced Industry Jobs
Share of advanced
industry jobs
Annual compensation
per worker ($)
1 Management and Technical Consulting 15,250 15.9% 85,931
2 Computer Systems Design 10,100 10.5% 106,348
3 Architectural and Engineering 9,020 9.4% 78,724
4 Motor Vehicle Parts Manufacturing 7,590 7.9% 52,601
5 Data Processing and Hosting 6,800 7.1% 121,391
6 Electric Power Generation and Distribution 3,410 3.5% 136,079
7 General Purpose Machinery Manufacturing 3,030 3.1% 68,132
8 Engine and Turbine Manufacturing 2,480 2.6% 98,093
9 Other Miscellaneous Manufacturing 2,420 2.5% 37,595
10 Medical Equipment Manufacturing 2,390 2.5% 44,854
All advanced industries 96,210 100% 86,370
All industries 1,082,870 -- 54,763
Source: Brookings analysis of Moody’s Analytics data.

33. But trails peers in advanced industries intensity
33
Charlotte’s share of employment and output generated by advanced industries
trail most peer metros, but advanced industries employment growth has been fifth
highest since 2008.
Advanced Industries Employment and Output Profile, Charlotte and Peer Regions
Rank Metro Area
Share of total
workforce, 2014
Jobs,
2014
Annualized job growth rate,
2008-2014
Share of GDP,
2014
GDP (USD billion),
2014
1 Austin 12.8% 119,480 2.9% 25.6% 26.7
2 Dallas 10.4% 344,650 0.7% 23.9% 95.8
3 Denver 10.3% 139,690 1.8% 19.2% 30.0
4 Kansas City 9.6% 99,850 1.5% 14.4% 14.5
5 Minneapolis 9.5% 181,990 0.3% 16.4% 33.3
6 Indianapolis 9.1% 91,920 0.5% 23.5% 23.8
7 Cleveland 8.9% 93,520 -0.9% 13.7% 14.8
8 Charlotte 8.9% 96,210 1.4% 16.6% 19.1
9 Atlanta 8.8% 221,320 0.7% 14.5% 39.8
10 Phoenix 8.2% 154,900 -0.1% 14.9% 28.0
11 San Antonio 6.5% 65,440 2.9% 15.9% 16.0
Source: Brookings analysis of Moody’s Analytics data.

34. Bottom Line – Innovation
34
Fast growth in advanced industries employment since 2008 shows that Greater
Charlotte does house innovative firms in management and technical consulting,
advanced manufacturing, and computer systems design.
But very low levels of research and development, technology
commercialization, and venture capital reveal that Greater Charlotte’s innovation
ecosystem is not yet at the same level as global peers.
Unlike its peer metro economies, Greater Charlotte does not house major
research universities or medical centers, major engines of the innovation
economy. UNC-Charlotte is the region’s most significant research asset, but it is not
currently ranked among the top 750 universities with the greatest scientific impact.
Innovation CLT ATL ATN BIR CLE CPN DAL DEN FRT HAM IND KC MEL MPLS MON MUN PHX SA STK ZUR
R&D conducted at universities per $1,000 of GDP, 2013 18 6 4 12 8 1 17 13 11 7 14 19 5 9 2 10 16 15 3 -
Business-funded R&D conducted at universities per $1,000 GDP, 2013 10 3 1 - 7 - 8 2 - - 4 11 - 5 - - 9 6 - -
Percentage of university scientific publications cited in top 10 percent, 2010-2013 20 7 4 9 5 11 8 2 15 10 13 19 12 3 18 6 16 17 14 1
Percentage of university scientific publications conducted with industry, 2010-2013 20 5 6 16 7 1 10 2 8 12 3 18 19 14 17 9 15 11 4 13
Patents per 10,000 inhabitants, 2008-2012 18 14 7 16 9 3 12 11 5 10 8 19 17 2 15 4 13 20 1 6
Startup activity rank, Kauffman Foundation, 2015 7 4 1 - 10 - 6 2 - - 8 9 - 11 - - 5 3 - -
Venture capital investments per capita, 2005-2014 16 5 1 20 10 7 6 2 17 19 9 12 18 3 8 14 13 15 4 11
Share of jobs in advanced industries, 2014 8 9 1 - 7 - 2 3 - - 6 4 - 5 - - 10 11 - -
% change in advanced industries employment, 2008-2014 5 7 1 - 11 - 6 3 - - 8 4 - 9 - - 10 2 - -
Lower Higher
Peer Rank CLT = Charlotte CPN = Copenhagen IND = Indianapolis MUN = Munich
ATL = Atlanta DAL = Dallas KC = Kansas City PHX = Phoenix
ATN = Austin DEN = Denver MEL = Melbourne SA = San Antonio
BIR = Birmingham (UK) FRT = Frankfurt MPLS = Minneapolis STK = Stockholm
CLE = Cleveland HAM = Hamburg MON = Montreal ZUR = Zurich

35. 4 | Talent

36. Why Talent Matters
36
Human capital—the stock of knowledge, skills, expertise, and capacities
embedded in the labor force—is of critical importance to enhancing productivity,
raising incomes, and driving economic growth.
As labor markets have become more global, skilled immigrants have become
an increasingly important source of talent for U.S. metro economies. Foreign
students studying at U.S. universities—the well-educated workers of
tomorrow—are a new and growing input to metropolitan economic
competitiveness and cultural diversity.
Producing, attracting, and retaining educated workers; creating jobs for those
workers; and connecting those workers to employment through efficient labor
markets all matter for regional competitiveness and ensuring broad-based
economic opportunity.
Source: For a full review of the role of human capital in metropolitan growth, see George Washington Institute of Public Policy and RW Ventures, “Implementing Regionalism.”

37. Charlotte’s workforce is well-educated
37
About 35 percent of the region’s workforce has obtained a post-secondary
degree, placing Charlotte in the middle of its highly educated peer group.
Percentage of population above 15 years old with tertiary education, 2013
28.7
28.9
31.2
32.1
32.2
33.0
33.3
33.3
33.8
34.1
35.1
36.0
36.6
36.9
39.5
41.2
42.0
42.0
42.6
43.3
Hamburg
San Antonio
Montreal
Frankfurt
Birmingham (UK)
Cleveland
Indianapolis
Phoenix
Dallas
Munich
Melbourne
Atlanta
Kansas City
Copenhagen
Austin
Stockholm
Zurich
Denver
Minneapolis
Charlotte
Source: Brookings analysis of U.S. Census Bureau data.

38. 11
10
9
8 8
7 7
6
4
1 1
Indianapolis Austin Dallas Phoenix Kansas City San Antonio Atlanta Cleveland Denver Minneapolis
Yet regional employers struggle to fill job vacancies
38
Despite its educated workforce, Charlotte’s employers nevertheless face
challenges in filling job vacancies. Among U.S. peers, Charlotte’s online job
postings had the longest median duration (11 days) before being filled.
Median duration of job openings (days), Greater Charlotte and peer regions, 2013
Charlotte
Source: Brookings analysis of Burning Glass data.

39. 25.4%
23.9%
22.7% 22.5% 22.2% 21.9% 21.7% 21.5% 21.3% 20.8%
18.3%
Denver Austin Indianapolis Minneapolis Cleveland Kansas City Dallas Atlanta Phoenix San Antonio
48.3% 47.4%
44.9%
42.9% 42.7% 42.1% 41.7% 41.5%
39.3%
37.4%
35.4%
Austin Denver Atlanta Dallas Kansas City Minneapolis Cleveland Phoenix San Antonio Indianapolis
Employer demand for STEM skills is high
39
About one in five Charlotte workers work in STEM occupations. Nearly half of all
job ads are in STEM occupations, the third highest share in the nation.
Share of job ads in STEM occupations, Greater Charlotte and peer regions, 2013
Charlotte
Share of workers in STEM occupations, Greater Charlotte and peer regions, 2013
Charlotte
Source: Brookings analysis of Burning Glass data.

40. 1
2
5
7
11
12
12
13
14
15
17
Minneapolis
Denver
Cleveland
Atlanta
Indianapolis
Dallas
Phoenix
Kansas City
San Antonio
Austin
And STEM jobs are among the hardest to fill
40
The median duration for STEM job ads are higher (14 days) than job ads overall
(11 days), and middle-skill STEM jobs—those requiring more than a high school
degree but less than a Bachelor’s degree—have the longest fill times.
Median duration of STEM job openings (days), by
education requirement, Greater Charlotte, 2013
Median duration of STEM job openings (days),
Greater Charlotte and peer regions, 2013
Charlotte
18
32
10
High School or Less Some college or
Associate's degree
Bachelor's Degree
Median duration STEM
jobs overall: 14 days
STEM Jobs
Source: Brookings analysis of Burning Glass data.

41. 78.8
84.6
81.6
72.3
71.0
86.8
82.3
82.1
74.4
75.0
78.2
82.5
79.4
80.7
80.7
81.2
80.4
79.3
72.2
72.8
92.6
86.3
83.8
83.5
80.0
80.0
79.7
78.7
78.5
77.4
77.3
76.8
76.4
75.7
74.5
73.7
71.9
71.3
70.6
69.6
Stockholm
Zurich
Copenhagen
Hamburg
Frankfurt
Minneapolis
Denver
Kansas City
Munich
Melbourne
Montreal
Austin
Cleveland
Dallas
Indianapolis
Atlanta
Phoenix
Birmingham (UK)
San Antonio
Meanwhile the labor force participation rate is falling
41
Charlotte’s labor force participation rate has declined by a larger margin than all
global peer metros except Atlanta and Phoenix since 2000, exacerbating labor
supply-demand mismatches.
Labor Force Participation Rate, 2000-2014
Charlotte
20142000
Source: Brookings analysis of OECD data.

42. 5.7%
6.0%
6.4%
9.4%
9.7%
11.8%
12.1%
13.2%
13.4%
14.2%
14.4%
14.5%
14.8%
17.5%
19.6%
20.0%
21.4%
25.2%
25.9%
37.4%
Cleveland
Indianapolis
Kansas City
Minneapolis
San Antonio
Denver
Atlanta
Birmingham (UK)
Hamburg
Phoenix
Copenhagen
Austin
Dallas
Frankfurt
Stockholm
Munich
Montreal
Zurich
Melbourne
Immigration can help address skills demands
42
Immigrants further economic growth by matching their skills with the demands of
local employers. While the share of its population born abroad is relatively low,
Charlotte is an emerging immigrant gateway, passing 250,000 immigrants in 2014.
And in-migrants, whether from other states or abroad, are relatively well-educated.
Educational attainment, by migration status, Greater
Charlotte, 2014
Foreign-born share of total population, Greater
Charlotte and peer regions, 2013
Charlotte
14.8%
8.0%
13.1%
20.8%
20.4%
25.1%
20.6%
28.6%
30.4%
43.8%
43.0%
31.4%
Less than high school
High school graduate
Some college or associate's degree
Bachelor's degree or higher
Overall population
Migrated from:
Another U.S. state
Abroad
Source: Brookings analysis of U.S. Census Bureau data.

43. 1.39
1.43
1.53
1.78
1.79
1.86
2.44
2.72
3.63
3.65
3.94
San Antonio
Indianapolis
Kansas City
Cleveland
Denver
Phoenix
Minneapolis
Atlanta
Dallas
Austin
And employers are demanding international talent
43
Greater Charlotte’s employers exhibit strong demand for highly skilled foreign
workers, applying for the fourth most H-1B visa applications per 1000 workers
among U.S. peers. Nearly 81 percent of those applications are positions that
demand STEM skills, the second highest share in this analysis.
Share of H-1B applications for positions demanding STEM
skills, Greater Charlotte and peer regions, 2010-2011
H-1B guest worker visas requested per 1,000 workers,
Greater Charlotte and peer regions, 2010–2011
Charlotte
60.0%
66.2%
69.0%
73.7%
74.2%
74.5%
75.6%
75.6%
75.7%
80.7%
80.8%
Cleveland
San Antonio
Indianapolis
Dallas
Atlanta
Denver
Austin
Kansas City
Phoenix
Minneapolis
Charlotte
Source: Brookings analysis of U.S. Department of Labor, Labor Condition Application data.

44. 10.6
11.3
11.9
12.3
12.7
14.0
14.5
16.1
16.9
21.3
22.5
San Antonio
Phoenix
Kansas City
Indianapolis
Cleveland
Minneapolis
Atlanta
Austin
Denver
Dallas
Foreign students are another potential talent source
44
Foreign students enhance an economy’s global engagement by injecting spending
into the local economy, establishing connections with their home market, and staying
to local to work upon graduation. Currently, Charlotte has fewer foreign students at its
colleges and universities than many of its peer regions.
F1 student visas approved per 1,000 higher education
students, Greater Charlotte and peer regions, 2008–2012
Charlotte
India – 742
China - 641
Saudi Arabia - 464
South Korea - 239
Canada - 162
Top origin markets for F1 student visas, Greater
Charlotte, 2008–2012
Source: Brookings analysis of Immigration and Customs Enforcement data.

45. Bottom Line – Talent
45
Greater Charlotte’s workforce falls in the middle of its peer group in terms of tertiary
educational attainment.
Charlotte’s employers nevertheless face challenges in filling job vacancies, especially
middle-skill occupations that demand STEM skills. Among U.S. peers, Charlotte’s online job
postings had the longest median duration before being filled. As workers have aged, Charlotte’s
labor force participation rate has declined, potentially exacerbating these skills deficiencies as
STEM-intensive advanced industries expand. Greater Charlotte’s educational institutions will be
critical in filling this gap.
Employers are turning to in-migrants—both from abroad and the rest of the U.S.—to fill
skills needs. Charlotte is not yet a major immigration hub, but its foreign-born population is
growing quickly. In-migrants tend to be disproportionately well-educated.
Talent CLT ATL ATN BIR CLE CPN DAL DEN FRT HAM IND KC MEL MPLS MON MUN PHX SA STK ZUR
Share of 15+ population with tertiary education, 2013 10 8 5 16 15 6 12 2 17 20 14 7 9 1 18 11 13 19 4 3
Median duration of job openings, 2013 11 4 9 - 3 - 8 2 - - 10 6 - 1 - - 7 5 - -
Share of workers in STEM occupations, 2013 6 9 2 - 5 - 8 1 - - 3 7 - 4 - - 10 11 - -
Median duration of STEM job openings, 2013 9 4 11 - 3 - 6 2 - - 5 8 - 1 - - 7 10 - -
Labor force participation rate, 2014 16 17 12 19 13 3 14 7 5 4 15 8 10 6 11 9 18 20 1 2
Change in labor force participation rate, 2000-2014 18 20 15 9 11 6 14 10 3 2 16 13 5 17 8 4 20 12 1 7
Foreign-born share of total population, 2013 17 13 8 12 20 9 7 14 6 11 19 18 1 16 3 4 10 15 5 2
Share of foreign-born population with at least some college or associate's degree, 2013 8 7 4 - 6 - 10 9 - - 2 3 - 5 11 1 - -
H-1B guest worker visas per 1,000 workers, 2010-2011 4 3 1 - 8 - 2 7 - - 10 9 - 5 - - 6 11 - -
F1 student visas approved per 1,000 higher education students, 2008-2012 7 4 3 - 6 - 1 2 - - 8 9 - 5 - - 10 11 - -
Lower Higher
Peer Rank
CLT = Charlotte CPN = Copenhagen IND = Indianapolis MUN = Munich
ATL = Atlanta DAL = Dallas KC = Kansas City PHX = Phoenix
ATN = Austin DEN = Denver MEL = Melbourne SA = San Antonio
BIR = Birmingham (UK) FRT = Frankfurt MPLS = Minneapolis STK = Stockholm
CLE = Cleveland HAM = Hamburg MON = Montreal ZUR = Zurich

46. 5 | Infrastructure

47. Why infrastructure matters
47
Firms rely upon global access points like airports and ports and digital
infrastructure to move their products, services, and people to markets outside
the region in the most efficient manner possible.
The competitiveness of a metropolitan economy also hinges on its ability to
effectively connect its people and physical assets to their best use within the
region—what planners and economic developers call “spatial efficiency.”
Source: For a full review of the role of infrastructure in metropolitan growth, see George Washington Institute of Public Policy and RW Ventures, “Implementing Regionalism.”

48. CLT is a fast-growing, well-connected airport
In 2015, the Charlotte-Douglas International Airport moved 44.9 million
passengers between Charlotte and 147 destinations, the 24th highest total in the
world. Passenger growth was among the fastest in its global peer group between
2004 and 2014.
48
44.9 million
CLT’s total passengers, 2015
24th
CLT’s global rank, 2015
-20.3%
-7.2%
-3.8%
3.6%
10.2%
12.2%
16.2%
19.4%
21.7%
33.1%
42.0%
42.5%
45.3%
46.0%
48.0%
55.5%
59.9%
65.1%
65.4%
72.7%
Cleveland
Indianapolis
Kansas City
Phoenix
Dallas
Minneapolis
Atlanta
San Antonio
Frankfurt
Munich
Montreal
Denver
Birmingham (UK)
Hamburg
Austin
Zurich
Stockholm
Copenhagen
Melbourne
Origin-destination aviation passenger growth, Greater
Charlotte and peer regions, 2004-2014
Charlotte
Source: Brookings analysis of Sabre aviation data.

49. Int’l passenger connections strongest with Europe
International origin-destination flows are largest with the rest of North America
(Toronto, Mexico City, Montreal); Europe (London, Frankfurt, Munich, Paris); and
Asia (Shanghai, Tokyo, Delhi, and Seoul). Growth has been fastest with South
America, Africa, and Asia.
49

50. But a high share of passengers never leave CLT
Nearly 58 percent of passengers never step out of the airport, the highest share
of any region, limiting the economic impact of the airport.
50
0.4%
0.6%
0.7%
2.4%
2.5%
2.8%
3.0%
3.9%
6.3%
6.9%
7.3%
16.1%
17.0%
24.1%
24.9%
26.9%
29.6%
36.6%
47.4%
57.9%
Birmingham (UK)
Hamburg
Indianapolis
Melbourne
San Antonio
Stockholm
Austin
Kansas City
Montreal
Cleveland
Copenhagen
Zurich
Munich
Denver
Phoenix
Minneapolis
Frankfurt
Dallas
Atlanta
Charlotte
Share of passengers that pass through airport, Greater
Charlotte and peer regions, 2014
“Metro areas that serve as destinations for
large numbers of people are, implicitly, points
of convergence for new ideas and capital.
These places have the right mix of human
capital and other resources to incubate new
business ventures and to stimulate creativity.
The net effect is an employment boost
throughout local industries, from high-skill
services that rely heavily on air travel to more
stationary industries like manufacturing.”
- Tomer, Puentes & Neal, 2012
Source: Brookings analysis of Sabre aviation data.

51. Charlotte trades about $130 billion in goods
$130 billion in goods trade (domestic + international) starts or ends in Greater
Charlotte, nearly 12 percent of which flows globally. Greater Charlotte firms rely
on ports in other U.S. regions to send and receive international goods.
51
Largest port complexes used for Greater Charlotte’s
international goods trade, billions USD, 2010
$130 billion
Total goods trade value, 33/100 U.S.
metros
11.7%
International trade share, 67/100 U.S.
metros
Port Complex
Total Trade
(billions USD)
New York 2.2
Los Angeles 1.7
Miami 1.1
Detroit 1.1
Laredo 0.7
Houston 0.7
Savannah 0.5
Anchorage 0.5
Chicago 0.5
Buffalo 0.4
Source: Brookings analysis of Economic Development Research Group data.

52. Greater Charlotte is not yet a major port complex
The region is not a major international port, ranking behind most U.S. peers in
terms of freight flow. Of the $2.7 billion in international freight that moved through
Greater Charlotte’s ports in 2010, 99.7% travels via air, mainly higher value
commodities.
52
Top 5 commodities moved by Greater Charlotte’s port
complex, millions USD, 2010
$833.9
$535.2
$438.8
$301.8 $293.2
Pharmaceuticals Chemicals/
Plastics
Machinery Electronics Precision
Instruments
$184
$449
$569
$800
$2,669
$3,830
$4,474
$5,591
$19,404
$26,736
$33,868
San Antonio
Kansas City
Austin
Phoenix
Indianapolis
Denver
Minneapolis
Cleveland
Atlanta
Dallas
Total international freight movement, Greater Charlotte
and peer port complexes, millions USD, 2010
Charlotte
Source: Brookings analysis of Economic Development Research Group data.

53. Broadband speeds lag and access varies by income
Quality broadband access allows students, workers, and firms to benefit from the
power of the internet. Charlotte’s average download speeds trail most peers;
overall broadband access is average and varies significantly by income.
53
Internet download speed, mbps, 2015 Share of households with broadband access, 2014
Broadband access, by income, 2014
Source: Brookings analysis of data from Ookla and U.S. Census Bureau.

54. Commuting times in Charlotte are about average
Transportation networks connect firms to global access points like airports and
ports, shuttle workers to jobs, and facilitate intra-metro commerce and
collaboration. Greater Charlotte’s average commuting times fall in the middle of its
peer group, suggesting that the proximity between workers and jobs is not a
significant weakness but could still be improved.
54
Distribution of travel time to work for all commuters*, minutes, 2014
8%
10%
9%
11%
10%
11%
11%
11%
12%
11%
13%
10%
12%
11%
13%
13%
13%
13%
13%
13%
13%
14%
33%
36%
38%
39%
38%
39%
40%
41%
39%
40%
42%
25%
25%
26%
23%
25%
23%
23%
22%
24%
24%
21%
12%
10%
9%
8%
9%
8%
8%
7%
7%
7%
6%
12%
8%
7%
7%
6%
6%
5%
6%
5%
5%
4%
Atlanta
Dallas
Denver
Austin
Phoenix
Minneapolis
San Antonio
Indianapolis
Cleveland
Kansas City
0 to 19 minutes 0 to 14 minutes 15 to 29 minutes 30 to 44 minutes 45 to 59 minutes 60+ minutes
Charlotte
Source: Brookings analysis
of U.S. Census Bureau data.

55. Bottom Line – Infrastructure
55
The Charlotte-Douglas International Airport is a significant global asset. It is
one of the fastest-growing airports among Charlotte’s peer regions. However, a high
share of passengers never leave the airport, limiting its impact on the local economy.
The airport also anchors freight movement, although Greater Charlotte is not
yet a significant port complex. The region tends to rely on the nation’s largest ports
to send and receive goods internationally, underscoring the importance of the new
intermodal facility at the airport.
Digital infrastructure quality and access could be improved. Charlotte’s average
internet download speeds trail most peers, and access varies significantly by income.
Infrastructure CLT ATL ATN BIR CLE CPN DAL DEN FRT HAM IND KC MEL MPLS MON MUN PHX SA STK ZUR
Aviation passenger growth, 2004-2014 4 14 6 8 20 2 16 9 12 7 19 18 1 15 10 11 17 13 3 5
Share of passthrough aviation traffic, 2014 20 19 7 1 10 11 18 14 17 2 3 8 4 16 9 13 15 5 6 12
Total international freight movement, 2010 7 2 9 - 3 - 1 5 - - 6 10 - 4 - - 8 11 - -
Internet download speed, 2015 18 10 3 8 20 4 13 12 9 6 14 5 19 15 16 11 7 17 2 1
Share of hosueholds with broadband access, 2014 6 4 1 - 10 - 7 2 - - 9 5 - 3 - - 8 11 - -
Share of commuters traveling more than 45 minutes to work, 2014 6 11 8 - 2 - 10 9 - - 3 1 - 5 - - 7 4 - -
Lower Higher
Peer Rank
CLT = Charlotte CPN = Copenhagen IND = Indianapolis MUN = Munich
ATL = Atlanta DAL = Dallas KC = Kansas City PHX = Phoenix
ATN = Austin DEN = Denver MEL = Melbourne SA = San Antonio
BIR = Birmingham (UK) FRT = Frankfurt MPLS = Minneapolis STK = Stockholm
CLE = Cleveland HAM = Hamburg MON = Montreal ZUR = Zurich

56. Bottom Line – Charlotte’s competitive position
56
Economic performance: Overall economic growth has been robust over the past
decade, but on metrics of inclusion Greater Charlotte has lagged.
Trade and Investment: Greater Charlotte is very globally-oriented. Exports and
foreign direct investment account for a disproportionate share of the regional
economy, led by tradable anchors like machinery, transportation equipment, and
financial services.
But the region is at risk of losing ground to peer metropolitan economies unless it
shores up its competitive drivers:
• Innovation: Build up very low levels of research and development, technology
commercialization, and venture capital investment;
• Talent: Help employers overcome challenges in filling job vacancies, especially
occupations that require STEM skills; and
• Infrastructure: Address lagging broadband speeds and disparities in broadband
access by income.

57. Conclusion
57
This comparative global benchmarking analysis reveals that Greater Charlotte has
significant assets on which to build: globally engaged companies in key advanced
industries; a highly-educated workforce; and an internationally-connected airport.
But that same perspective yields other areas that warrant improvement: upgrading
the region’s system for innovation and entrepreneurship; addressing employer
difficulties in finding STEM workers; and bridging disparities in broadband access.
Going forward, whatever their course of action, Charlotte leaders should ensure they
are focusing on what Brookings’ Amy Liu calls the “markets and civics”:
“Markets: Economic development should prioritize building strong business ecosystems for core
industries, improving the productivity of firms and people, and facilitating trade—the market
foundations from which growth, prosperity, and inclusion emerge.
Civics: To get the markets right requires good civics: the work to organize and implement
strategies and initiatives that engage stakeholders and partners to achieve long-term goals. A
data-driven economic narrative and sense of urgency, networked leadership with high capacity
organizations for implementation, and engagement of diverse stakeholders and perspectives to
ensure strategies are inclusive are all essential.”
- Amy Liu, “Remaking Economic Development,” 2016

58. Benchmarking results
58
Trade and Investment CLT ATL ATN BIR CLE CPN DAL DEN FRT HAM IND KC MEL MPLS MON MUN PHX SA STK ZUR
Export share of GDP, 2014 1 8 7 - 4 - 3 11 - - 2 5 - 6 - - 10 9 - -
% change in export share of GDP, 2003-2014 1 7 10 - 6 - 2 8 - - 4 5 - 9 - - 11 3 - -
Annualized export growth, 2003-2014 4 7 3 - 10 - 2 5 - - 8 6 - 9 - - 11 1 - -
Share of jobs in foreign-owned establishments (FOEs), 2011 1 2 8 - 9 - 5 7 - - 3 4 - 6 - - 10 11 - -
Change in share of jobs in FOEs, 1991-2011 10 4 3 - 11 - 7 8 - - 1 2 - 5 - - 9 6 - -
Greenfield FDI per capita, 2009-2015 10 8 1 2 20 9 15 18 6 14 13 16 3 19 5 11 17 12 7 4
Innovation CLT ATL ATN BIR CLE CPN DAL DEN FRT HAM IND KC MEL MPLS MON MUN PHX SA STK ZUR
R&D conducted at universities per $1,000 of GDP, 2013 18 6 4 12 8 1 17 13 11 7 14 19 5 9 2 10 16 15 3 -
Business-funded R&D conducted at universities per $1,000 GDP, 2013 10 3 1 - 7 - 8 2 - - 4 11 - 5 - - 9 6 - -
Percentage of university scientific publications cited in top 10 percent, 2010-2013 20 7 4 9 5 11 8 2 15 10 13 19 12 3 18 6 16 17 14 1
Percentage of university scientific publications conducted with industry, 2010-2013 20 5 6 16 7 1 10 2 8 12 3 18 19 14 17 9 15 11 4 13
Patents per 10,000 inhabitants, 2008-2012 18 14 7 16 9 3 12 11 5 10 8 19 17 2 15 4 13 20 1 6
Startup activity rank, Kauffman Foundation, 2015 7 4 1 - 10 - 6 2 - - 8 9 - 11 - - 5 3 - -
Venture capital investments per capita, 2005-2014 16 5 1 20 10 7 6 2 17 19 9 12 18 3 8 14 13 15 4 11
Share of jobs in advanced industries, 2014 8 9 1 - 7 - 2 3 - - 6 4 - 5 - - 10 11 - -
% change in advanced industries employment, 2008-2014 5 7 1 - 11 - 6 3 - - 8 4 - 9 - - 10 2 - -
Talent CLT ATL ATN BIR CLE CPN DAL DEN FRT HAM IND KC MEL MPLS MON MUN PHX SA STK ZUR
Share of 15+ population with tertiary education, 2013 10 8 5 16 15 6 12 2 17 20 14 7 9 1 18 11 13 19 4 3
Median duration of job openings, 2013 11 4 9 - 3 - 8 2 - - 10 6 - 1 - - 7 5 - -
Share of workers in STEM occupations, 2013 6 9 2 - 5 - 8 1 - - 3 7 - 4 - - 10 11 - -
Median duration of STEM job openings, 2013 9 4 11 - 3 - 6 2 - - 5 8 - 1 - - 7 10 - -
Labor force participation rate, 2014 16 17 12 19 13 3 14 7 5 4 15 8 10 6 11 9 18 20 1 2
Change in labor force participation rate, 2000-2014 18 20 15 9 11 6 14 10 3 2 16 13 5 17 8 4 20 12 1 7
Foreign-born share of total population, 2013 17 13 8 12 20 9 7 14 6 11 19 18 1 16 3 4 10 15 5 2
Share of foreign-born population with at least some college or associate's degree, 2013 8 7 4 - 6 - 10 9 - - 2 3 - 5 11 1 - -
H-1B guest worker visias per 1,000 workers, 2010-2011 4 3 1 - 8 - 2 7 - - 10 9 - 5 - - 6 11 - -
F1 student visas approved per 1,000 higher education students 7 4 3 - 6 - 1 2 - - 8 9 - 5 - - 10 11 - -
Infrastructure CLT ATL ATN BIR CLE CPN DAL DEN FRT HAM IND KC MEL MPLS MON MUN PHX SA STK ZUR
Aviation passenger growth, 2004-2014 4 14 6 8 20 2 16 9 12 7 19 18 1 15 10 11 17 13 3 5
Share of passthrough aviation traffic, 2014 20 19 7 1 10 11 18 14 17 2 3 8 4 16 9 13 15 5 6 12
Total international freight movement, 2010 7 2 9 - 3 - 1 5 - - 6 10 - 4 - - 8 11 - -
Internet download speed, 2015 18 10 3 8 20 4 13 12 9 6 14 5 19 15 16 11 7 17 2 1
Share of hosueholds with broadband access, 2014 6 4 1 - 10 - 7 2 - - 9 5 - 3 - - 8 11 - -
Share of commuters traveling more than 45 minutes to work, 2014 6 11 8 - 2 - 10 9 - - 3 1 - 5 - - 7 4 - -
Lower Higher
CLT = Charlotte CPN = Copenhagen IND = Indianapolis MUN = Munich
ATL = Atlanta DAL = Dallas KC = Kansas City PHX = Phoenix
ATN = Austin DEN = Denver MEL = Melbourne SA = San Antonio
BIR = Birmingham (UK) FRT = Frankfurt MPLS = Minneapolis STK = Stockholm
CLE = Cleveland HAM = Hamburg MON = Montreal ZUR = Zurich
Peer Rank

59. Peer Methodology
59
Global peer cities were selected based on economic characteristics and competitiveness factors. Classifying and identifying peers
allows policymakers and stakeholders to better understand the position of their economies in a globalized context as well as to conduct
constructive benchmarking.
To select peers we utilized a combination of principal components analysis (PCA), k-means clustering, and agglomerative hierarchical
clustering. These commonly used data science techniques allowed us to group metro areas with their closest peers given a set of
economic and competitiveness indicators. For this report we selected 14 economic variables: population, nominal GDP, real GDP per
capita, productivity (defined as output per worker), total employment, share of the population in the labor force, and industry share of
total GDP (8 sectors). We included seven additional variables that measure one of the four quantitative dimensions of the
competitiveness analysis framework used in this report. The variables included are: share of the population with tertiary education
(talent), stock of greenfield foreign direct investment (FDI) (trade), number of international passengers in 2014 (infrastructure), number
of highly cited papers between 2010 and 2013 (innovation), mean citation score between 2010 and 2013 (innovation), and average
internet download speed in 2014 (infrastructure).
Our analysis proceeded in three steps. First, we applied PCA to reduce the number of dimensions of our data by filtering variables that
are highly interrelated while retaining as much variance as possible. PCA generates “components” by applying a linear transformation to
all the variables. To successfully perform our clustering algorithm we selected the number of components that explain 80 to 90 percent
of the variance of a dataset. For this report we selected the first seven components, which accounted for 84 percent of the total variation
of the data. The second stage applied a k-means algorithm to the seven components, a process which calculates the distance of every
observation in our dataset to each other, then generates a cluster centroid and assigns each data point to the closest cluster. K-means
repeats this procedure until a local solution is found. This algorithm provides a good segmentation of our data and under most
circumstances it is a sufficient method for partitioning data. However k-means sometimes generates clusters with multiple observations,
thus obscuring some of the closest economic relationships between metro areas. To improve the results of k-means we implemented a
third step, hierarchical clustering, which follows a similar approach to k-means. Hierarchical clustering calculates Euclidean distances to
all other observations, but generates a more granular clustering that permits clearer peer-to-peer comparison.

60. Data Sources
Oxford Economics: Economic indicators as well as selected indicators corresponding to talent for non-U.S.
metropolitan areas were provided by Oxford Economics (OE). Economic variable such as GDP, Gross Value Added
(GVA), employment, unemployment rates, educational attainment, and industry-level employment and output were
collected by OE from national statistics bureaus in each country or from providers such as Haver, ISI Emerging
Markets, and Eurostat. Population estimates and the share of the foreign-born population were based on official
population projections produced by national statistical agencies and or organizations such as Eurostat, adjusting
migration assumptions on a case-by case basis. The study uses gross value added (GVA) and Gross Domestic
Product (GDP) in nominal terms at purchasing power parity rates, and in real terms at 2009 prices and expressed in
U.S. dollars. All the indicators were provided at the metropolitan level.
Moody’s Analytics: Economic indicators for U.S. metro areas were provided by Moody’s Analytics. Moody’s uses
data published by the Bureau of Labor Statistics (BLS) and by the Bureau of Economic Analysis (BEA) to generate
their estimates of employment and GDP at the county level. We aggregated those estimates to metropolitan areas
using the current Census Bureau definition. For real GDP, both total and at the industry level, Moody’s provides 2009
chained dollars. For nominal analysis they report their estimates in current dollar.
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61. Data Sources
Advanced Industries: Brookings identifies 50 four-digit NAICS industries as “advanced” in the U.S. economy.
For more information: Mark Muro and others, “America’s Advanced Industries: What they are, where they are, and
why they matter” (Washington: Brookings Institution, 2015).
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Advanced Industries
NAICS
Code
Industry
NAICS
code
Industry
2111 Oil & Gas Extraction 3351 Electrical Lighting Equipment
2122 Metal Ore Mining 3352 Household Appliances
2211 Power Generation & Supply 3353 Electrical Equipment
3241 Petroleum & Coal Products 3359 Misc. Electrical Equipment
3251 Basic Chemicals 3361 Motor Vehicles
3252 Resins & Synthetic Rubbers 3362 Motor Vehicle Body & Trailers
3253 Pesticides & Fertilizers 3363 Motor Vehicle Parts
3254 Pharmaceuticals 3364 Aircraft Products & Parts
3259 Misc. Chemicals 3365 Railroad Rolling Stock
3271 Clay & Refractory Products 3366 Ships & Boats
3279 Stone & Mineral Products 3369 Misc. Transportation Equipment
3311 Iron & Steel Products 3391 Medical Equipment & Supplies
3313 Aluminum Products 3399 Jewelry, Sporting Goods
3315 Foundries 5112 Software Products
3331 Agri., Constr., Mining Machinery 5152 Cable & Other Programming
3332 Industrial Machinery 5172 Wireless Telecom Carriers
3333 Commercial & Service Machinery 5174 Satellite Telecommunications
3336 Engine & Power Equipment 5179 Other Telecommunications
3339 General Purpose Machinery 5182 Data Processing & Hosting
3341 Computer Equipment 5191 News & Media
3342 Communications Equipment 5413 Architecture & Engineering
3343 Audio & Video Equipment 5415 Computer Systems Design
3344 Semiconductors 5416 Management Consulting
3345 Precision Instruments 5417 R&D Services
3346 Magnetic & Optical Media 6215 Medical & Diagnostic Laboratories

62. Data Sources
Exports: Export data are derived from a number of sources including: Census, BEA, Moody’s analytics, BLS,
NAFSA, IRS, EIA, and Sabre. The estimates include both goods and services and are adjusted to reflect the export
value-add at the point of production using the local share of national output to allocate national exports for each
industry and county. For more information: Nick Marchio, “Brookings export database methodology” (Washington:
Brookings Institution, 2015). www.brookings.edu/~/media/research/files/interactives/2015/export-
monitor/brookingsexport-series-methodology-nm-5715.pdf
Foreign Direct Investment: Jobs in foreign-owned establishments are derived from data from Dun and Bradstreet
(D&B), the National Establishment Time Series (NETS), and the Bureau of Economic Analysis (BEA). The estimates
include all foreign investment activity into the United States between 1991 and 2011, excluding real estate and EB-5
investment. Brookings utilized Moody’s private-sector employment totals to calculate the shares of domestic jobs in
foreign-owned establishments. For more information: Nick Marchio, “Methodological Appendix for FDI in U.S. Metro
Areas: The Geography of Jobs in Foreign-Owned Establishments” (Washington: Brookings Institution, 2014).
www.brookings.edu/~/media/research/files/reports/2014/06/20-fdi-us-metro-areas/method-appendix.pdf
The source of the greenfield FDI data is the Financial Times’ fDi Markets database. This database tracks all cross-
border investment into new physical projects or expansions of an existing investment, otherwise known as
“greenfield” investment. Company announcements form the basis for the database and each submission is manually
verified before being published. In cases when the capital investment and job counts are not publicly released,
analysts impute the value invested and jobs created using an econometric model. The primary sources of the data
are newswires, internal sources, top business journals, industry organizations, investment agencies, and data
purchased from private vendors. Brookings’ analysts assigned metro areas to the city-level information available in
the database and processed the flows between different investor and recipient geographies and industry levels. The
preferred metric is the cumulative stock of FDI invested and jobs created over the reference period from 2009 to
2015. All value measures were inflation-adjusted to 2014 dollars. For more information see
http://www.fdimarkets.com/faqs/
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63. Data Sources
Patents: Patents data are derived from the OECD’s REGPAT database. The OECD manages this database as part
of the Patent Cooperation Treaty, which offers patent protection to organizations and individuals planning to do
business in multiple countries. A number of research decisions went into the construction of the patent estimates.
Patent locations correspond to the inventor’s place of residence or workplace. In cases when there are multiple
inventors, the patent was apportioned in equal shares to each co-inventor. Patents that fall under multiple
International Patent Classification (IPC) technology codes were also apportioned in equal shares to each technology
class in order to account for the cross-cutting nature of technological development. To mitigate year-to-year
fluctuations in invention activity, patents were summed in five-year intervals. The time dimensions represent the
“priority year” when the patent was first filed. This year is closest to the actual date of invention and is the most
relevant reference date when assessing an area’s technological activity at a specific point in time. Since patent filing
is a costly and administratively burdensome process the analysis excludes patents submitted in 2013 and 2014
since patents filed in these years only account for a portion of patents actually invented and may bias places and
organizations with better systems for shortening lag time between the date of invention and the application year.
For more information: Stephane Maraut and others, “The OECD REGPAT Database: A Presentation” (Paris:
OECD, 2008). www.oecd.org/sti/inno/40794372.pdf
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64. Data Sources
University Research Impact: University scientific impact data come from the Centre for Science and Technology
Studies (CWTS) at Leiden University. This publicly available database tracks bibliometric performance data for 750
universities with the largest publication output in internationally recognized journals. The database relies on the
Thomson Reuters Web of Science citations indices which researchers cleansed, geocoded, and classified into fields
of study. CWTS reports publications based on full-counting methods which gives equal weight to all publications from
a university and fractional counting methods which apportion shares to each collaborator.
For more information: L. Waltman and others, “The Leiden Ranking 2011/2012: Data collection, indicators, and
interpretation.” Journal of the American Society for Information Science and Technology 63(12), 2419–32.
www.leidenranking.com/methodology
Venture Capital: Venture capital data are derived from PitchBook, a private financial research firm that collects and
tracks global private equity activity. PitchBook analysts deploy web crawlers to perform a daily systematic scan of
media reports and public filing information on deals which they then record and validate through a manual review
process. In assembling their database they include address-level data for both investors and recipient companies,
industry, investor details along with the deal value. Brookings took the data and then assigned the investors and
recipients to metropolitan geographies. The primary statistic in the analysis is the cumulative stock of venture capital
which is the sum total of year-to-year investment flows. Secondary statistics examine the number of investors and
companies along with data between different geographies, deal categories, and industries. The advanced industries
classification is an approximate grouping based of detailed industry categories matched to Brookings’ NAICS-based
definition. All value measures were inflation-adjusted to 2014 dollars.
For more information: http://blog.pitchbook.com/wp-content/uploads/2014/06/3Q-2014-PEBreakdown-
Methodology.pdf
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65. Data Sources
Aviation: Aviation data are derived from Sabre Aviation Solutions’ global demand dataset (GDD). The dataset
includes a record for every international itinerary entering and leaving the United States or any large global metro
area with output of at least $100 billion in 2014. Each record includes the origin and destination airports, plus up to
three connecting airports with the number of passengers and total revenue generated from that specific itinerary for
that year. The GDD is based on a variety of sources including information developed from direct business relations
between Sabre and over 400 global airlines. For international itineraries not reflected in their database, Sabre
imputes missing flights and passenger levels based on additional market data. The result is a complete dataset of
travel into and out of major global aviation centers. Brookings assigned all airports to global metropolitan areas,
obtained latitude and longitude coordinates to derive distance measures, cleaned anomalous records, and
aggregated the passenger and revenue flows to better facilitate regional analysis. All value measures were inflation-
adjusted to 2014 dollars.
For more information: Adie Tomer, Robert Puentes, and Zachary Neal, “Global Gateways: International Aviation in
Metropolitan America” (Washington: Brookings Institution, 2012).
www.brookings.edu/~/media/research/files/reports/2012/10/25-global-aviation/25-globalaviation.pdf
Freight: This analysis uses a unique database measuring goods traded among U.S. metropolitan areas,
nonmetropolitan regions, and international geographies. We used the data foundation and design scheme of the
publicly available Freight Analysis Framework (FAF). The database provides a comprehensive view of freight
movement to, from, and within the United States. Originally based on calendar year 2007, Version 3.2 has been
provisionally updated to estimate 2010 total freight volumes, or flows, by annual tonnage, value, and ton-mileage.
With an interest in showing domestic and international freight flows in, out, and among all of the country’s
metropolitan areas, Brookings worked with the EDR Group to estimate freight movement across combined statistical
areas (CBSAs). For more information: Adie Tomer, Robert Puentes, and Joseph Kane, “Metro-to-Metro: Global and
Domestic Goods Trade in Metropolitan America” (Washington: Brookings Institution, 2013).
www.brookings.edu/~/media/Research/Files/Reports/2013/10/21-metro-freight/SrvyMetroToMetro.pdf?la=en
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66. Acknowledgements
This report is made possible by funding from the Central Piedmont Community College. Special thanks go to Dr. Tony Zeiss and Mary Vickers-Koch for their support
and guidance.
This presentation was prepared by Joseph Parilla, Senior Research Associate, Brookings Metropolitan Policy Program. For their research support and advice, he
would like to thank Alan Berube, Jesus Leal Trujillo, and Nick Marchio.
ABOUT THE METROPOLITAN POLICY PROGRAM AT BROOKINGS
The Metropolitan Policy Program at Brookings delivers research and solutions to help metropolitan leaders build an advanced economy that works for all. To learn
more visit www.brookings.edu/metro.
FOR MORE INFORMATION
Metropolitan Policy Program at Brookings
1775 Massachusetts Avenue, NW
Washington, D.C. 20036-2188
Telephone: 202.797.6000
Fax: 202.797.6004
Website: www.brookings.edu
Joseph Parilla
Senior Research Associate
Metropolitan Policy Program at Brookings
jparilla@brookings.edu
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