. Metropolitan Policy Program at BROOKINGS THE BROOKINGS INSTITUTION I METROPOLITAN POLICY PROGRAM 2015 Global MetroMonitor 2 0 An Uncertain Recovery 1 4 Joseph Parilla, Jesus Leal Trujillo, and Alan Berube with Tao Ran FINDINGS The economic growth trajectories of the world’s major metropolitan areas continued to diverge in 2014, reflecting a still uncertain global recovery. An analysis of employment and GDP per capita growth in the world’s 300 largest metropolitan economies—which accounted for 20 percent of the world’s population and 47 percent of its output in 2014—finds the following: ➤➤ M etropolitan economies with the fastest growth rates in 2014 were concentrated in the developing world. Three-quarters of the fastest-growing metropolitan economies were located in the Developing AsiaPacific and Eastern Europe and Central Asia regions. By contrast, 83 percent of the slowest-growing metro economies were in Western Europe, North America, and Developed Asia-Pacific. ➤➤ M etropolitan areas continue to power national economic growth; most registered faster GDP per capita or employment growth in 2014 than their respective countries. Last year, one-third of the world’s 300 largest metropolitan economies were “pockets of growth,” outpacing their national economies in both indicators. Developing Asia-Pacific led this category with 29 metro areas, followed by North America (27) and Western Europe (17). ➤➤ A majority of the world’s metropolitan areas (60 percent) have recovered to pre-recession levels of employment and GDP per capita. Of those, half are located in Developing Asia-Pacific and North America. About one-fifth of metro areas have not recovered on either indicator; nearly all of those are located in North America and Western Europe. Comparing the post-recession (2009 to 2014) to the pre-recession (2000 to 2007) period, GDP per capita growth rates dropped in developed metro areas and held steady in developing metro areas, while employment growth rates declined in both. ➤➤ M etropolitan areas specializing in commodities registered the highest rates of GDP per capita and employment growth in 2014. Utilities, trade and tourism, and manufacturing specializations were also associated with higher growth rates. By contrast, metro areas with high concentrations of business, financial, and professional services grew more slowly. The global map of metropolitan economic performance in this year’s Global MetroMonitor reveals a still-tentative and uneven recovery. With half of the world’s economic output centered in these 300 regions, their individual and collective progress will continue to shape prospects for more sustainable and broadly shared growth. Their actions bear watching. GLOBAL M ETRO MONITOR 2014 A n Uncertain Recovery 1 INTRODUCTION In 2014, an uneven global recovery persisted amid significant economic uncertainty in both advanced economies and emerging markets. Growth accelerated in the United States and United Kingdom but stalled in Japan and the Euro Area. China maintained strong growth relative to the rest of the world, even as it cooled off by its own recent torrid pace, while growth in China’s BRIC counterparts Brazil and Russia slowed significantly.1 As the year progressed, the International Monetary Fund revised its annual projections downward, citing lingering challenges from the financial crisis and more pessimistic future growth prospects.2 Global and national assessments, although important, fail to document the distinctive contributions to growth and prosperity made by the world’s economic engines: major cities and metropolitan areas. Today, more than half of the world’s population lives in cities and metro areas and, together, the world’s 300 largest metropolitan economies accounted for nearly half of all global output in 2014. In addition to their collective economic clout, these places are also highly differentiated based on their development stage, world region, and industrial specializations. Measuring the individual trajectories of the world’s large metropolitan economies offers new insights into sources of growth that national or regional assessments tend to obscure. Global comparisons of metro area performance can also inform city- and region-led economic strategies. These subnational actors increasingly have greater latitude to pursue economic reforms and investments, as political gridlock hinders efforts by national and supranational governments and multilateral institutions to improve the economy. This is the fourth edition of the Global MetroMonitor, a report that compares growth patterns in the world’s 300 largest metropolitan economies on two key economic indicators: annualized growth rate of real GDP per capita and annualized growth rate of employment.3 These are by no means the only metrics that should guide economic policymakers in cities; for instance, the distribution of economic growth across societies and the effects of growth on the environment are also important considerations, albeit outside the scope of this report. That noted, the two key metrics in the Global MetroMonitor reflect the importance that policymakers and the public attach to achieving rising incomes and standards of living (GDP per capita), as well as generating widespread labor market opportunity (employment).4 This report uses these two indicators to measure the 2014 performance of the world’s 300 largest metropolitan areas in three key dimensions: relative to one another; relative to their respective countries; and relative to their own previous performance, including the extent of their recovery since the downturn. These rankings do not attempt to measure which metro areas are most competitive, wealthy, or livable, as incredible differences in wealth and prosperity exist within the sample (Table 1). Rather, they aim to capture how metro areas are responding to continued change in the world economy, and to illuminate the underlying factors contributing to their diverse performance. 2 t h e b r ookings institution metropolitan policy program f" wt: ulh'anE! 1:53 1 - TABLE 1. INCOMES VARY SIGNIFICANTLY ACROSS THE WORLD’S 300 LARGEST METROPOLITAN ECONOMIES Highest and Lowest GDP Per Capita, 300 Largest Metropolitan Economies, 2013 Highest Lowest Rank Metro Region GDP per Capita Rank Metro Region GDP per Capita 1 Zurich Western Europe $82,410 281 Kunming Developing Asia-Pacific $6,680 2 Oslo Western Europe $82,040 282 Xuzhou Developing Asia-Pacific $6,550 3 San Jose North America $77,440 283 Shijiazhuang Developing Asia-Pacific $6,540 4 Hartford North America $76,510 284 Manila Developing Asia-Pacific $6,160 5 Geneva Western Europe $74,580 285 Medellin Latin America $5,940 6 Paris Western Europe $70,760 286 Wenzhou Developing Asia-Pacific $5,630 7 Boston North America $70,390 287 Chongqing Developing Asia-Pacific $5,590 8 Bridgeport North America $68,570 288 Casablanca Middle East and Africa $5,400 9 Washington DC North America $68,530 289 Jakarta Developing Asia-Pacific $5,020 10 Seattle North America $67,830 290 Nanning Developing Asia-Pacific $4,860 11 Macau Developed Asia-Pacific $67,780 291 Shantou Developing Asia-Pacific $4,150 12 San Francisco North America $66,790 292 Delhi Developing Asia-Pacific $3,580 13 Perth Developed Asia-Pacific $65,500 293 Ho Chi Minh City Developing Asia-Pacific $3,300 14 Calgary North America $64,540 294 Cairo Middle East and Africa $2,980 15 New York North America $64,460 295 Alexandria Middle East and Africa $2,680 16 Portland North America $64,370 296 Mumbai Developing Asia-Pacific $1,990 17 Munich Western Europe $64,180 297 Chennai Developing Asia-Pacific $1,870 18 Houston North America $63,730 298 Hyderabad Developing Asia-Pacific $1,430 19 Dublin Western Europe $63,600 299 Bangalore Developing Asia-Pacific $1,420 20 Luxembourg-Trier Western Europe $63,350 300 Kolkata Developing Asia-Pacific $1,110 Source: Brookings analysis of data from Oxford Economics, Moody’s Analytics, and U.S. Census Bureau. DATA AND METHODS This update of the Global MetroMonitor largely follows the methodology used in previous editions.5 Therefore, this section focuses primarily on changes introduced in this year’s report. (For more details on definitions, methodology, and data see Appendix B.) This study defines a metropolitan area as an economic region including one or more cities and their surrounding areas, all linked by economic and commuting ties (see Appendix B). This year’s sample is comprised of the 300 largest metropolitan economies in the world for which industry trend data were available, based on the size of their economies in 2014 at purchasing power parity (PPP) rates. Much like previous editions, the 2014 Global MetroMonitor employs a few key variables to assess the economic performance of metropolitan areas: gross domestic product (GDP), employment, and population from 2000 to 2014.6 In addition, the study uses gross value added (GVA) and employment by major industry sector.7 To analyze economic circumstances in the current year (2014), this study employs nominal GDP and GVA data in U.S. dollars at PPP rates. For trend analysis, it uses GDP and GVA data at 2009 prices and expressed in U.S. dollars. 4 t h e b r ookings institution metropolitan policy program Key Terms Used in Global MetroMonitor Gross domestic product (GDP): The sum of the market value of goods and services produced in an economy, such as a metropolitan area, country, or the world. Output (gross value added) of an industry: The difference between an industry’s gross output and its intermediary purchases, domestic or imported. Employment: The number of people who performed any work at all in the reference period, for pay or in-kind, or who were temporarily absent from a job for such reasons as illness, maternity or parental leave, holiday, training, or industrial dispute. GDP per capita: The size of an economy relative to population. It is not personal income or household income, and does not reflect the distribution of income, but proxies the average standard of living in an area. Population: The number of residents of a metropolitan area or country. The report focuses on metropolitan performance on two key economic indicators: annualized growth rate of real GDP per capita, and annualized growth rate of employment. These indicators are combined into an economic performance index by which the 300 metro areas are ranked for 2014 (see Appendix B).8 The 2014 Global MetroMonitor examines the extent of the economic downturn and subsequent recovery at the metropolitan level, comparing 2014 levels of real GDP per capita and employment to 2007 levels. Along these lines, it classifies metro economies into three performance categories: ➤➤ R ecovered: economies that have equal or higher GDP per capita and employment in comparison to 2007 levels ➤➤ P artially Recovered: economies that have recovered their 2007 levels in either GDP per capita or employment, but not both ➤➤ Not Recovered: economies with lower levels for both indicators To interpret metropolitan economic performance, this report classifies metropolitan areas by their respective countries’ income levels and world region. The 300 metropolitan areas are classified as “developed” and “developing” based on their primary country’s 2013 gross national income (GNI) per capita.9 Using the World Bank’s 2014 list of economies, “developed” status is equivalent to “high income” level, or GNI per capita in excess of $12,746.10 “Developing” metro areas are located in countries with GNI per capita below that level. Of the 300 metropolitan areas in this study’s sample, 204 are in developed countries and 96 are in developing countries.11 Based on World Bank and International Monetary Fund (IMF) definitions, this study identifies seven world regions in which the sampled metropolitan areas lie: ➤➤ W estern Europe: 68 metro areas in countries that were members of the European Union before the 2004 enlargement (EU-15), plus Norway and Switzerland ➤➤ North America: 80 U.S. and eight Canadian metro areas ➤➤ D eveloped Asia-Pacific: 33 metro areas in higher-income Asia-Pacific countries (Australia, Hong Kong, Japan, Macau, New Zealand, Singapore, South Korea, and Taiwan) GLOBAL M ETRO MONITOR 2014 A n Uncertain Recovery 5 ➤➤ D eveloping Asia-Pacific: 60 metro areas in lower-income Asian nations (China, India, Indonesia, Malaysia, Philippines, Thailand, and Vietnam) ➤➤ L atin America: 22 metro areas in Argentina, Brazil, Chile, Colombia, Mexico, Peru, Puerto Rico, and Venezuela ➤➤ E astern Europe and Central Asia: 14 metro areas in Bulgaria, Czech Republic, Hungary, Kazakhstan, Poland, Romania, Russia, and Turkey ➤➤ M iddle East and Africa: seven metro areas in Middle Eastern countries (Israel, Kuwait, the United Arab Emirates, and Saudi Arabia) and eight metro areas in African nations (Egypt, Morocco, and South Africa); this study includes only five sub-Saharan African metro areas (all in South Africa), due to the small size of their metro economies and severely limited data availability/reliability for other metropolitan areas in this region12 The 2014 edition follows the same industrial categorization as the 2012 Global MetroMonitor, comprised of seven major industrial sectors for which GVA and employment data are available at the metropolitan level (see Appendix B). FINDINGS A. Metropolitan economies with the fastest growth rates in 2014 were concentrated in the developing world. Economic activity and growth in 2014 remained disproportionately concentrated in the world’s major metropolitan areas. The 300 largest metropolitan economies housed 20 percent of both the world’s population and its employment, but accounted for 47 percent of output and 38 percent of output growth. Global GDP per capita and employment growth were both a relatively sluggish 1.4 percent in 2014. Overall, GDP per capita in the top 300 metro areas grew by 1.3 percent in 2014, compared to 1.6 percent in 2013. Employment grew at 1.5 percent in 2014, the same as in 2013. Developing metropolitan economies continued to be the sites of faster growth, further converging with their more developed peers. Employment in developing metro areas grew by 1.7 percent in 2014, slightly higher than the 1.3 percent registered in developed metro economies. GDP per capita growth differences were starker, expanding by a healthy 4.0 percent in developing metro areas, compared to 0.8 percent in developed metro economies. Broad comparisons between developed and developing metropolitan economies alone miss important trends observable between major world regions (Figure 1). Developing Asia-Pacific metro areas achieved rapid GDP per capita growth (5.9 percent); in employment growth, metro economies across Eastern Europe and Central Asia (2.9 percent) and the Middle East and Africa (2.7 percent) set the pace. Growth rates in Western European metro areas were slow, while North American metro areas exhibited strong job growth (1.7 percent) but almost no growth in GDP per capita (0.3 percent). Latin America was the only region that registered a decrease in either indicator: a 0.3 percent decline in GDP per capita. Metropolitan area distribution across this study’s performance index brings differences by development status into sharper relief (Figure 2). As in previous years, developing metro areas dominated the top quintile of performers, accounting for 48 of 60 spots (80 percent). Metro areas in this quintile experienced a 4.8 percent increase in real GDP per capita and a 2.6 percent increase in employment (Figure 2). Chinese metro areas account for over half of the top quintile. As in 2012, Macau—one of China’s special autonomous regions—was the top performing metro area in the composite index (Table 2). Trade and tourism, anchored by the region’s gaming industry, was responsible for the largest share of output growth in Macau in 2014.13 6 t h e b r ookings institution metropolitan policy program Figure 1. METROPOLITAN GDP PER CAPITA AND EMPLOYMENT GROWTH RATES BY REGION AND DEVELOPMENT STATUS, 300 LARGEST METROPOLITAN ECONOMIES, 2013-2014 FIGURE 1. DEVELOPING ASIA-PACIFIC METRO AREAS LEAD ON GDP PER CAPITA GROWTH AND EASTERN EUROPE AND CENTRAL ASIA METRO AREAS LEAD ON EMPLOYMENT GROWTH Metropolitan GDP Per Capita and Employment Growth Rates by Region and Development Status, 300 Largest Metropolitan Economies, 2013-2014 5.9% GDP per Capita Employment 4.0% 2.9% 2.7% 1.3%1.5% 1.3% 0.8% 1.7% 1.7% 0.9% 0.9% 1.2% 1.0% 0.3% All GMM 4 n=300 Developed n=204 Developing n=96 Western Europe n=68 1.6% 1.4% 1.3% 1.0% -0.3% North America n=88 Middle East & Africa n=15 Source: Brookings analysis of data from Oxfordfrom Economics, Moody’s Analytics,Moody’s and U.S. Census Bureau.and Source: Brookings analysis of data Oxford Economics, Analytics, Latin America Eastern Europe & n=22 Central Asia n=14 Developing Asia-Pacific n=60 Developed Asia-Pacific n=33 U.S. Census Bureau. Figure 2. DEVELOPING METROPOLITAN ECONOMIES ARE GROWING FASTEST Distribution of Developed and Developing Metropolitan Economies and Growth Rates by Quintile of the 2014 FIGURE 2. DEVELOPING METROPOLITAN ECONOMIES ARE GROWING FASTEST of Developed and Developing Metropolitan Economies and Growth Rates by Quintile of the 2014 Economic Performance Index, 300 Largest Metro Economic Distribution Performance Index, 300 Largest Metro Areas Areas Distribution Developing Developed 17 13 9 9 43 47 51 51 48 12 Top Quintile Second Quintile Third Quintile Fourth Quintile Lowest Quintile Growth 4.8% GDP per Capita 2.6% 2.4% 1.8% Employment 1.3% 0.7% Top Quintile Second Quintile Third Quintile 0.6% 0.8% Fourth Quintile -0.2% -0.1% Lowest Quintile Source: Brookings analysis of data from Oxford Economics, Moody’s Analytics, and U.S. Census Bureau. Source: Brookings analysis of data from Oxford Economics, Moody’s Analytics, and U.S. Census Bureau. GLOBAL M ETRO MONITOR 2014 A n Uncertain Recovery 7 TABLE 2. DEVELOPING METRO AREAS LED THE LIST OF FASTEST GROWING ECONOMIES IN 2014 Highest Performers on Economic Performance Index, 300 Largest Metropolitan Economies, 2013-2014 Highest Change, 2013-2014 Rank ’13–’14 Region GDP per Capita Metro Employment Rank ’12–’13 Ranking Change 1 Macau Developed Asia-Pacific 8.0% 4.2% 1 0 2 Izmir Eastern Europe and Central Asia 2.0% 6.6% 6 4 3 Istanbul Eastern Europe and Central Asia 2.0% 6.5% 52 49 4 Bursa Eastern Europe and Central Asia 1.8% 6.4% 4 0 18 13 5 Dubai Middle East and Africa 4.5% 4.7% 6 Kunming Developing Asia-Pacific 8.1% 2.9% 2 -4 7 Hangzhou Developing Asia-Pacific 7.0% 3.3% 15 8 8 Xiamen Developing Asia-Pacific 8.6% 2.6% 8 0 9 Ankara Eastern Europe and Central Asia 1.1% 5.7% 38 29 10 Fuzhou Developing Asia-Pacific 8.0% 2.7% 11 1 11 Wulumuqi Developing Asia-Pacific 7.4% 2.7% 5 -6 12 Budapest Eastern Europe and Central Asia 2.4% 4.7% 201 189 13 Wuhan Developing Asia-Pacific 9.3% 1.9% 33 20 14 Ningbo Developing Asia-Pacific 6.8% 2.8% 21 7 15 Changsha Developing Asia-Pacific 8.6% 1.8% 20 5 16 Chengdu Developing Asia-Pacific 8.1% 1.9% 12 -4 17 Wenzhou Developing Asia-Pacific 6.6% 2.5% 31 14 18 Delhi Developing Asia-Pacific 4.4% 3.3% 7 -11 19 Kuala Lumpur Developing Asia-Pacific 4.1% 3.4% 3 -16 20 Hefei Developing Asia-Pacific 9.5% 1.0% 44 24 21 Nanning Developing Asia-Pacific 7.2% 1.9% 16 -5 22 Nantong Developing Asia-Pacific 6.9% 1.9% 10 -12 23 Ho Chi Minh City Developing Asia-Pacific 3.9% 3.1% 55 32 24 Xuzhou Developing Asia-Pacific 6.9% 1.8% 9 -15 25 Riyadh Middle East and Africa 1.9% 3.9% 62 37 26 London Western Europe 2.5% 3.6% 58 32 27 Jinan Developing Asia-Pacific 7.1% 1.7% 50 23 28 Suzhou Developing Asia-Pacific 6.7% 1.7% 14 -14 29 Qingdao Developing Asia-Pacific 7.1% 1.6% 28 -1 30 Sofia Eastern Europe and Central Asia 2.5% 3.4% 226 196 Source: Brookings analysis of data from Oxford Economics, Moody’s Analytics, and U.S. Census Bureau. 8 t h e b r ookings institution metropolitan policy program TABLE 2. Developed Metro Areas Led the List of Slowest Growing Economies in 2014 (continued) Lowest Performers on Economic Performance Index, 300 Largest Metropolitan Economies, 2013–2014 Lowest Change, 2013-2014 Rank ’13–’14 Region GDP per Capita Metro Employment Rank ’12–’13 Ranking Change 271 Bucharest Eastern Europe and Central Asia 1.7% -0.7% 221 -50 272 Allentown North America -0.3% 0.1% 165 -107 273 Columbus North America -1.3% 0.4% 95 -178 274 Rome Western Europe -0.8% 0.1% 286 12 275 Washington North America -1.5% 0.3% 245 -30 276 Bologna Western Europe -0.4% -0.1% 287 11 277 Milan Western Europe -0.5% -0.2% 288 11 278 Venice-Padova Western Europe -0.6% -0.2% 289 11 279 Winnipeg North America -0.2% -0.4% 168 -111 280 Athens Western Europe 0.3% -0.6% 300 20 281 Virginia Beach North America -1.0% -0.1% 219 -62 282 Helsinki Western Europe -0.5% -0.3% 284 2 283 Turin Western Europe -0.7% -0.3% 290 7 284 Sao Paulo Latin America -1.5% 0.0% 181 -103 285 Montreal North America 0.7% -0.9% 69 -216 286 Buenos Aires Latin America -2.8% 0.5% 170 -116 287 Dayton North America -1.7% 0.0% 269 -18 288 Eindhoven-Den Bosch Western Europe 0.7% -1.1% 283 -5 289 Florence Western Europe -0.6% -0.6% 292 3 290 Porto Alegre Latin America -1.7% -0.2% 158 -132 291 Campinas Latin America -2.2% 0.0% 175 -116 292 RotterdamAmsterdam Western Europe 0.3% -1.2% 282 -10 293 Daqing Developing Asia-Pacific 4.0% -2.8% 278 -15 -31 294 Syracuse North America -1.2% -0.7% 263 295 Arnhem-Nijmegen Western Europe 0.0% -1.2% 281 -14 296 Caracas Latin America -3.5% 0.1% 129 -167 297 Naples Western Europe -0.7% -1.0% 293 -4 298 Albuquerque North America -2.2% -0.6% 238 -60 299 Adelaide Developed Asia-Pacific -1.2% -1.1% 275 -24 300 Bangkok Developing Asia-Pacific -0.5% -1.7% 246 -54 Source: Brookings analysis of data from Oxford Economics, Moody’s Analytics, and U.S. Census Bureau. GLOBAL M ETRO MONITOR 2014 A n Uncertain Recovery 9 map 1. 2013-2014 ECONOMIC PERFORMANCE INDEX RANKINGS, BY QUINTILE, MAP 1.METROPOLITAN 2013-2014 ECONOMIC 300 LARGEST ECONOMIES PERFORMANCE INDEX RANKINGS, BY QUINTILE, 300 LARGEST METROPOLITAN ECONOMIES Vancouver Chicago Salt Lake City San Francisco New York Los Angeles Miami Mexico City Economic Index Rank 2013 to 2014 Bogota Top quintile Second quintile Middle quintile Fourth quintile Bottom quintile Metropolitan Nominal GDP 500 2014 forecasts 100 (blns $, P PP rates) Rio de Janeiro Santiago Calgary Seattle Montreal Minneapolis Chicago Boston Denver New York Los Angeles Dallas Monterrey Atlanta Miami Guadalajara 10 t h e b r ookings institution metropolitan policy program Source: Brookings analysis of data from Oxford Economics, Moody's Analytics, and U.S. Census Bureau Stockholm Moscow Almaty Madrid Athens Wulumqi Izmir Delhi Riyadh Jeddah-Mecca Mumbai Tokyo Chengdu Shanghai Manila Bangkok Singapore Jakarta Perth Cape Town Melbourne Oslo Edinburgh Stockholm RotterdamAmsterdam Copenhagen-Malmö London Dublin Haerbin Shenyang Beijing Baotou Seoul-Incheon Warsaw Frankfurt Qingdao Paris Munich Budapest Chengdu Shanghai Wuhan Barcelona Lisbon Rome Naples Tokyo Ningbo Chongqing Madrid OsakaKobe Taipei Guangzhou Hong Kong GLOBAL M ETRO MONITOR 2014 A n Uncertain Recovery 11 Despite national security concerns, Turkish metropolitan areas had an exceptional 2014, with Izmir, Istanbul, and Bursa each placing among the world’s top five performers, led by strong expansions in business and financial services. Five North American metro areas (Austin, Houston, Raleigh, Fresno, Calgary) and two western European metro areas (London and Manchester) also managed to rank among the 60 fastest growing in the world. Business and financial services accounted for the largest shares of output growth in Austin, London, and Raleigh; commodities led in Calgary and Houston; and local/non-market services predominated in Fresno. The metropolitan areas in the last quintile registered a reduction in GDP per capita of 0.2 percent and a decline of 0.1 percent in employment. The weakest-performing metro economy in 2014 was Bangkok, where anemic manufacturing and trade and tourism sectors led to declines in employment and GDP per capita of 1.7 and 0.5 percent, respectively.14 Meanwhile, 25 metro areas in Western Europe reflected the continent’s continued economic malaise by placing in the bottom performance quintile. Poor performance was not limited to the developed world, however. Almost one-third of Latin American metro areas ranked in the lowest quintile, due in part to lagging growth in local/ non-market services in Argentina and Venezuela and manufacturing in Brazil.15 B. Metropolitan areas continue to power national economic growth; most registered faster GDP per capita or employment growth in 2014 than their respective countries. National monetary, fiscal, trade, and regulatory policies matter for metro growth, but the specific characteristics of metropolitan economies often differentiate their economic performance from that of their respective countries. In 2014, a clear majority of the 296 metropolitan areas (excluding four that are coterminous with national boundaries) in the sample outperformed their respective national economies.16 Over 60 percent of metro areas outperformed their national economies in employment creation. Developing Asia-Pacific (50) and North American (43) accounted for more than half of the metro areas in this category. Edmonton led with an employment growth rate of 4.0 percent, compared to a rate of 0.6 for Canada; local/non-market services drove 41 percent of new jobs added. Hangzhou (led by business and financial services), Fresno (local/non-market services), and Kunming (trade and tourism) also outpaced their nations. In Daqing, by contrast, employment declined 2.7 percent compared to 0.4 percent growth across China (Table 3). Almost half of the metropolitan areas (140) registered higher GDP per capita growth rates than their national economies, led by North America, where 39 of 88 metro areas exceeded national growth. Developing Asia-Pacific followed closely behind—34 of its 60 metro areas grew faster in GDP per capita than their national economies. No metropolitan area grew faster relative to its national economy than Dubai, where the business and financial services sector helped drive 4.5 percent growth in GDP per capita, versus 1.6 percent growth for the United Arab Emirates as a whole.17 Hefei (led by manufacturing), Wuhan (manufacturing), Vancouver (business and financial services), and Calgary (energy) rounded out the top five in this category. Many Chinese metro areas exhibited staggering gains in GDP per capita that far outpaced the country’s 6.7 percent growth in 2014, accounting for five of the top ten metro areas worldwide on this metric. However, Tianjin registered an increase of only 3.3 percent, revealing that subnational growth patterns differ significantly in China (see Special Feature). In 2014, one-third of the world’s 300 largest metropolitan economies were “pockets of growth,” growing faster than their national economies in both indicators (Map 2). Developing Asia-Pacific led this category with 29 metro areas, followed by North America (27) and Western Europe (17). “ Led by metro areas in China and Turkey, developing metro economies led the world in employment and income growth, while many metro areas in the United States and the United Kingdom registered significant improvements.” 12 t h e b r ookings institution metropolitan policy program TABLE 3. SOME METRO AREAS LED OR LAGGED THEIR NATIONS ON GROWTH BY LARGE MARGINS IN 2014 Largest Differences Between Metro and National Income and Employment Growth Rates, 2013-2014 GDP Per Capita Growth Rate Employment Growth Rate Faster in Metro Areas Faster in Metro Areas Metro Nation Difference Metro Area Nation Difference 1 Dubai 4.5% 1.6% 2.9% Edmonton 4.0% 0.6% 3.4% 2 Hefei 9.5% 6.7% 2.8% Hangzhou 3.3% 0.4% 3.0% 3 Wuhan 9.3% 6.7% 2.6% Fresno 4.5% 1.6% 2.9% 4 Vancouver 3.7% 1.2% 2.5% Kunming 2.9% 0.4% 2.6% 5 Calgary 3.1% 1.2% 1.9% Ningbo 2.8% 0.4% 2.4% 6 Xiamen 8.6% 6.7% 1.9% Raleigh 4.0% 1.6% 2.4% 7 Changsha 8.6% 6.7% 1.8% Fuzhou 2.7% 0.4% 2.3% 8 Perth 3.4% 1.9% 1.5% Wulumuqi 2.7% 0.4% 2.3% 9 Austin 1.9% 0.4% 1.5% Xiamen 2.6% 0.4% 2.2% 10 Chengdu 8.1% 6.7% 1.4% Wenzhou 2.5% 0.4% 2.1% Metro Nation Difference Brisbane -0.4% 1.9% -2.3% 288 Zhuhai 4.4% 6.7% 289 New Orleans -2.0% 290 St. Louis -2.1% 291 Shantou 292 Albuquerque 293 Daqing 294 Slower in Metro Areas Slower in Metro Areas Metro Nation Difference Detroit 0.3% 1.6% -1.3% -2.3% Haerbin -1.1% 0.4% -1.4% 0.4% -2.4% Allentown 0.1% 1.6% -1.5% 0.4% -2.5% Montreal -0.9% 0.6% -1.5% 4.0% 6.7% -2.7% Dayton 0.0% 1.6% -1.6% -2.2% 0.4% -2.7% Virginia Beach -0.1% 1.6% -1.7% 4.0% 6.7% -2.8% Adelaide -1.1% 1.0% -2.0% Bakersfield -2.4% 0.4% -2.8% Albuquerque -0.6% 1.6% -2.2% 295 Adelaide -1.2% 1.9% -3.1% Syracuse -0.7% 1.6% -2.3% 296 Tianjin 3.3% 6.7% -3.5% Daqing -2.8% 0.4% -3.1% 287 Source: Brookings analysis of data from Oxford Economics, Moody’s Analytics, and U.S. Census Bureau. GLOBAL M ETRO MONITOR 2014 A n Uncertain Recovery 13 map 2. Metro economy-country growth differential, 296 largest metropolitan economies, 2013-2014 MAP 2. METRO ECONOMY-COUNTRY GROWTH DIFFERENTIAL, 295 LARGEST METROPOLITAN ECONOMIES, 2013-2014 Vancouver Chicago Salt Lake City San Francisco New York Los Angeles Miami Mexico City Metro Area Performance 2013 to 2014 Bogota Metro area growing faster than country on both GDP per capita and employment Metro area growing slower than country on GDP per capita or employment or both Metropolitan Nominal GDP 500 2014 forecasts 100 (blns $, P PP rates) Rio de Janeiro Santiago Calgary Seattle Montreal Minneapolis Chicago Boston Denver New York Los Angeles Dallas Monterrey Atlanta Miami Guadalajara 14 t h e b r ookings institution metropolitan policy program Source: Brookings analysis of data from Oxford Economics, Moody's Analytics, and U.S. Census Bureau Stockholm Moscow Almaty Madrid Athens Wulumqi Izmir Delhi Riyadh Jeddah-Mecca Mumbai Tokyo Chengdu Shanghai Manila Bangkok Singapore Jakarta Perth Cape Town Melbourne Oslo Edinburgh Stockholm RotterdamAmsterdam Copenhagen-Malmö London Dublin Haerbin Shenyang Beijing Baotou Seoul-Incheon Warsaw Frankfurt Qingdao Paris Munich Budapest Chengdu Shanghai Wuhan Barcelona Lisbon Rome Naples Tokyo Ningbo Chongqing Madrid OsakaKobe Taipei Guangzhou Hong Kong GLOBAL M ETRO MONITOR 2014 A n Uncertain Recovery 15 Metro China: Economic Performance in the Nation’s Largest Metropolitan Areas Special Feature Although it is still growing rapidly by global standards, new doubts emerged in 2014 as to whether China’s exportfocused and investment-oriented economic strategy had reached its limit after decades of historically high growth. Amid changing national economic conditions, an understanding of where and how economic growth is occurring within China is critical. This special feature provides an analysis of GDP per capita and employment changes in China’s 48 largest metropolitan areas, which together account for 28 percent of China’s population but 56 percent of its national GDP.18 1. Compared to national averages, over three-quarters of China’s metropolitan areas achieved higher levels of GDP per capita or employment growth in 2014. China’s 48 large metropolitan areas accounted for 73 percent of employment growth and 60 percent of output growth in 2014. Nearly half (23) of the 48 metro areas were “pockets of growth,” meaning they exceeded national averages for both GDP per capita and employment growth. On GDP per capita growth, 25 Chinese metro areas exceeded the country’s 6.7 percent growth in 2014. Hefei led all Chinese metro areas with 9.5 percent growth, followed by Wuhan, Xiamen, and Changsha. All of these fast-growing metros, except Xiamen, are located in the central part of China. Top-ranked cities from this region also include Huhehaote (8th), Zhengzhou (9th), and Baotou (10th), marking a shift from 2013 when western China contained most of the nation’s fastest-growing metro areas. Growth in GDP per capita was slower in other parts of China. In Guangdong province in southeastern China, growth rates in Shenzhen (5.1 percent) and Guangzhou (4.9 percent) lagged national averages; each was weighed down by underperforming commodities and utilities sectors. Several other metro areas in Guangdong province— including Dongguan, Zhuhai, and Shantou—also experienced slower growth. However, GDP per capita growth was slowest in Tianjin (3.3 percent), China’s fourth-largest metro economy, where production in heavy industries such as steel and petrochemicals slowed.19 Employment growth displayed a slightly different pattern across China’s major metropolitan areas, which collectively accounted for 19 percent of national employment in 2014. In 41 of 48 Chinese metro areas, employment grew faster than the national average of 0.4 percent. Three metro areas from the eastern province of Zhejiang— Hangzhou, Ningbo, and Wenzhou—led on employment growth (ranking 1st, 3rd, and 7th, respectively) in 2014. Zhejiang boasts a strong concentration of small and medium-sized enterprises, which, according to the National Development and Reform Commission, generate more than 75 percent of employment in Chinese urban areas.20 The central Chinese metro areas that led on GDP per capita growth ranked in the middle of the overall distribution on employment growth, suggesting that living standards may be rising absent growth in jobs. A small number of Chinese metropolitan areas experienced shrinking employment in 2014, including Shenyang, Xi’an, Changchun, Dalian, Anshan, Haerbin, and Daqing. With the exception of Xi’an, all of these metro areas are in northeastern China, one of the country’s main industrial centers. Relatively inflexible and poorly managed industrial state-owned enterprises in that region have struggled in recent years amid increased global competition. 2. Among the 300 largest metropolitan economies worldwide, two-thirds of Chinese metro areas rank among the fastest-growing group. China is slowing down—annual GDP per capita growth fell from an average of 9.0 percent from 2007–2010 to 7.4 percent during 2010–2014—but Chinese metropolitan areas continue to outperform their global peers. On a performance index ranking the world’s top 300 metro areas, Kunming (6th), Hangzhou (7th), Xiamen (8th), and Fuzhou (10th) landed among the top 10 performers. Of the 48 Chinese metro areas in the sample, two-thirds (32) ranked in the top quintile (60 strongest performers) and another one-fifth (11) were in the second highest-performing quintile. China’s metro areas outperformed global peers largely due to much faster GDP per capita growth. GDP per capita growth in these Chinese metro areas reached 6.4 percent, while the world’s 300 largest metro economies experienced a 1.3 percent overall increase. Rapid productivity gains, buoyed by urbanization, continue to drive income growth in China’s cities, but employment growth in Chinese metro areas was more modest compared to the rest of the world. Employment grew by 1.4 percent in 2014, lower than the average employment growth among all metro areas in the sample. 16 t h e b r ookings institution metropolitan policy program mapMAP 3. Metro economy-country growthGROWTH differential, China’s 48 Largest Metropolitan 3. METRO ECONOMY-COUNTRY DIFFERENTIAL, Economies, CHINA's2013-2014 48 LARGEST METROPOLITAN ECONOMIES, 2013-2014 Haerbin Daqing Wulumuqi Changchun Baotou Huhehaote Shijiazhuang Beijing Tangshan Anshan Dalian Tianjin Taiyuan Zhengzhou Shenyang Yantai Jinan Xi'an Qingdao Xuzhou Nantong Nanjing Wuxi Wuhan Changzhou Chengdu Chongqing Changsha Kunming Suzhou Nanchang Shanghai Wenzhou Xiamen Hangzhou Shantou Ningbo Nanning Metro Area Performance 2013 to 2014 Metro area growing faster than country on both GDP per capita and employment Foshan Guangzhou Dongguan Metro area growing slower than country on GDP per capita or employment or both Metropolitan Nominal GDP 500 2014 forecasts 100 (blns $, P PP rates) Zhongshan Shenzhen Source: Brookings analysis of data from Oxford Economics, Moody's Analytics, and U.S. Census Bureau 3. Metropolitan growth patterns in China differ by scale of the economy, geographic location, and industrial specialization. The size (GDP) of metropolitan economies varies significantly within China’s top 48 metro areas, ranging from Shanghai ($594 billion) to Shantou ($39 billion). There are 22 metro areas that account for at least 1 percent of China’s output, and the country’s seven largest metro areas (Shanghai, Beijing, Guangzhou, Tianjin, Shenzhen, Suzhou, and Chongqing) alone account for 20 percent of the national economy. While these urban areas rival some nations in terms of economic size, China is so large that no metro area accounts for more than 4 percent of national GDP. China’s metro areas are critical economic engines, but the country’s growth does not rely on only one or two large places. Classifying China’s 48 metro areas into tiers based on economic size reveals differences in growth. First-tier cities such as Guangzhou and Shenzhen achieved below-average GDP per capita growth rates in 2014. By comparison, second-tier cities, which include provincial capitals and other economic centers, exhibited stronger performance on GDP per capita. Over the past five years, the ten fastest-growing Chinese metro areas are all from the second tier. GLOBAL M ETRO MONITOR 2014 A n Uncertain Recovery 17 Metro China: Economic Performance in the Nation’s Largest Metropolitan Areas (continued) The geography of growth in China has also shifted. From 2000 to 2007, GDP per capita growth was fastest in coastal metro areas like Dongguan, Yantai, Zhongshan, Zibo, and Qingdao. Then, as the central government ramped up investment in heavy industries in Northeastern China, growth shifted to places like Anshan, Dalian, and Changchun. From 2010 to 2014, patterns changed again. Coastal and northeastern regions gave way to higher growth in inland metro areas such as Chongqing, Hefei, Kunming, Wulumuqi, and Chengdu, which benefited from the central government’s efforts to connect these regions to the coast through significant infrastructure investment.21 The distinct economic structures of Chinese metro areas—particularly their industrial specializations—also affect their performance. Chongqing, located in Central China, offers an illustrative example. From 2000–2007, Chongqing ranked 28th among China’s 48 largest metro areas in terms of GDP per capita growth, but leaped to sixth from 2007–2010 and to first from 2010–2014. Chongqing’s rapid emergence reflects the ascent of its manufacturing sector. As labor costs rose in coastal cities, Chongqing attracted labor-intensive manufacturing seeking large supplies of workers and, in the process, its GDP per capita grew five-fold between 2000 and 2014 (Figure 3).22 Figure 3. Chongqing has outpaced China on GDP per capita growth GDP Per Capita Growth, 2000–2014 18% 16% 14% 12% 10% 8% Chongqing 6% 4% China 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Source: Brookings analysis of data from Oxford Economics, Moody’s Analytics, and U.S. Census Bureau. Advanced services are also driving growth in Chinese metropolitan areas. Hangzhou, a metro near Shanghai with a population of about 8.9 million, led all Chinese metro economies in 2014 with employment growth of 3.3 percent. The fastest-growing industry in Hangzhou was business, financial, and professional services. A rapidly growing e-commerce sector, anchored by Alibaba’s headquarters, has created a large demand for educated labor in this human-capital-intensive industry.23 18 t h e b r ookings institution metropolitan policy program C. A majority of the world’s metropolitan economies (60 percent) have recovered to pre-recession levels of employment and GDP per capita. The financial crisis and subsequent recession drastically altered regional growth patterns and therefore remain important reference points for benchmarking metropolitan performance in the global economy. The extent to which the world’s major metro economies weathered or recovered from the recession since 2007 differs significantly. More than half (180) of the 300 metro economies in the sample are “fully recovered”; these places have higher employment and GDP per capita in 2014 than in 2007. Half of these metro areas are located in Developing AsiaPacific and North America. In Developing Asia-Pacific, large metro areas like Beijing, Chengdu, and Shanghai never experienced a recession, while North American metro economies such as Boston, New York, and Seattle suffered through the downturn but have since recovered on both indicators. In Latin America, 86 percent (19 of 22) of metropolitan economies have recovered to previous peaks, thanks to a quick rebound in GDP per capita and employment growth immediately following the economic crisis (Figure 4). At the other end of the spectrum, just over one-fifth (61) of metro areas are “not recovered” in either indicator; this group is composed entirely of developed metro economies. Despite significant progress in North America and Western Europe, metro areas in these regions still account for 90 percent of these low performers. Among the 28 Western European metro areas in this group, average GDP per capita is 8 percent lower and employment is 7 percent lower than in 2007. North American metro areas like Chicago, Detroit, and Los Angeles have posted post-recession growth in both employment and GDP per capita, but have not yet made up the large losses suffered during the crisis. A subset of these metro areas also suffered declines on both indicators in 2014. This group is comprised of Italian metro areas (Naples, Turin, Venice, and Florence), U.S. metro areas (Virginia Beach, Syracuse, Albuquerque, and Dayton), and Arnhem-Nijmegen in the Netherlands. In Venice, GDP per capita in 2014 was 13 percent short of its 2007 level, while employment in Naples fell 10 percent during the same period. A third category of metropolitan areas (59) is “partially recovered.” This group has recovered on either GDP per capita or employment, but not on both indicators. North American and Latin American metro areas have mostly recovered in employment levels, while Developed Asia-Pacific and Developing Asia-Pacific metro areas have recovered in GDP per capita levels. Figure 4. Most Metropolitan Areas have recovered to 2007 Income and Employment levels Recovery Status on GDP Per Capita and Employment, 2014 Recovered on both income and employment Not Recovered on income or employment Partially Recovered on income or employment, but not both Developed Developing 93 87 61 50 180 metros 61 9 59 Source: Brookings analysis of data from Oxford Economics, Moody’s Analytics, and U.S. Census Bureau. GLOBAL M ETRO MONITOR 2014 A n Uncertain Recovery 19 map 4. Recession/Recovery Status, 300 Largest Metropolitan Areas, 2014 MAP 4. RECESSION/RECOVERY STATUS, 300 LARGEST METROPOLITAN AREAS, 2014 Vancouver Chicago Salt Lake City San Francisco New York Los Angeles Miami Mexico City Recession, recovery status Bogota Fully recovered Partially recovered Not recovered Metropolitan Nominal GDP 500 2014 forecasts 100 (blns $, P PP rates) Rio de Janeiro Santiago Calgary Seattle Montreal Minneapolis Chicago Boston Denver New York Los Angeles Dallas Monterrey Atlanta Miami Guadalajara 20 t h e b r ookings institution metropolitan policy program Source: Brookings analysis of data from Oxford Economics, Moody's Analytics, and U.S. Census Bureau Stockholm Moscow Almaty Madrid Athens Wulumqi Izmir Delhi Riyadh Jeddah-Mecca Mumbai Tokyo Chengdu Shanghai Manila Bangkok Singapore Jakarta Perth Cape Town Melbourne Oslo Edinburgh Stockholm RotterdamAmsterdam Copenhagen-Malmö London Dublin Haerbin Shenyang Beijing Baotou Seoul-Incheon Warsaw Frankfurt Qingdao Paris Munich Budapest Chengdu Shanghai Wuhan Barcelona Lisbon Rome Naples Tokyo Ningbo Chongqing Madrid OsakaKobe Taipei Guangzhou Hong Kong GLOBAL M ETRO MONITOR 2014 A n Uncertain Recovery 21 Taking a slightly longer view, the period from 2009 to 2014 revealed differences from before the recession between developed and developing metro areas in GDP per capita performance. While GDP per capita growth declined in developed metropolitan economies—from an annual average of 1.6 percent from 2000–2007 to 0.2 percent from 2009–2014—it held relatively steady in developing metro areas, at 6.1 percent growth in 2000–2007 and 5.7 percent in 2009–2014. A more concerning trend is the slowdown in job creation, even in the developing world. Employment in developed metro areas grew 1.1 percent from 2000 to 2007, and 0.5 percent from 2009 to 2014. In developing metro areas, the rate of job growth decreased from 3.4 percent to 2.6 percent in the 2009–2014 period. It is not clear whether growth in GDP per capita can persist in developing metro areas, or recover in developed ones, if employment growth continues to falter. D. Metropolitan areas specializing in commodities registered the highest rates of GDP per capita and employment growth in 2014. Examining metropolitan performance by industry provides further insights into the drivers of job creation and GDP per capita growth. To examine these trends, this analysis assigned 296 metropolitan areas (minus four that coterminous with national boundaries) one of seven industrial specializations: business, financial, and professional services; commodities; construction and local/non-market services; manufacturing; trade and tourism; transportation; and utilities. Industrial specializations were assigned using location quotients, which are based on the ratio of an industry’s share of metropolitan real GVA to its share of national real GVA. Figure 5. METRO AREAS SPECIALIZED IN COMMODITIES GREW FASTER THAN OTHER METRO AREAS IN 2013-2014 GDP per Capita and Employment Change by Metro Industrial Specialization, 296 Metro Areas, 2013–2014 GDP per capita 2.6% 1.9% 2.0% 1.9% 1.7% 1.4% 1.1% Employment 1.7% 1.6% 1.6% 1.6% 1.3% 0.8% Commodities n=18 Utilities n=12 Trade andTourism n=30 Manufacturing Construction & Local Transportation Business, Financial n=73 Non-Market Services n=28 & Professional Services n=73 n=78 Source: Brookings analysis of data from Oxford Economics, Moody’s Analytics, and U.S. Census Bureau. 22 0.6% t h e b r ookings institution metropolitan policy program Commodities-focused metropolitan areas registered the strongest performance in 2014. Across these 18 metro areas, GDP per capita grew by 2.6 percent and employment grew by 1.9 percent—both well above average—even as commodities prices fell worldwide. The recent rise in oil and gas production in North America partly explains the success of metropolitan areas like Calgary, Denver, Houston, and Tulsa, which are epicenters of the region’s shale revolution.24 Metro areas specializing in the utilities sector—including electric power, natural gas, steam supply, water supply, and sewage removal—also experienced above average per capita GDP growth (2 percent), but also saw below average employment expansion (1.1 percent). Metropolitan areas with a specialization in trade and tourism benefited from sustained growth in global flows of goods and people. Following years of sluggish expansion, international trade accelerated in 2014, helping spur growth in infrastructure hubs such as Atlanta, Jinan, and Qingdao.25 Similarly, tourist destinations such as Las Vegas, Miami, and Orlando benefited from an estimated 4.5 percent expansion in global tourism in 2014.26 Metropolitan economies specializing in manufacturing—the second largest specialization across the 296 metropolitan areas—also grew at above average rates for income (1.7 percent) and employment (1.6 percent), but significant differences exist between developed and developing manufacturing hubs. Developing metro areas with this specialization experienced a healthy expansion of 5.6 percent in manufacturing value-added in 2014, nearly three times the growth rate of developed manufacturing regions (1.8 percent). China accounts for much of this difference, particularly its manufacturing hubs in the Pearl River Delta region (Fuzhou, Zhongshan, Foshan, and Zhuhai) that continued to move up the value-added chain in 2014. Business, financial, and professional services accounted for the largest share of metropolitan industrial specializations, together generating 44 percent of the total GDP of the 296 metropolitan areas analyzed. Metro economies in this category displayed mixed performances, growing slightly above average on employment (1.6 percent) but experiencing only modest expansion in GDP per capita (0.6 percent). Despite this overall trend, developed metro economies such as London, Oslo, Paris, Tel Aviv, Vancouver, and Zurich registered above average income growth. “ Commodities-focused metropolitan areas registered the strongest performance in 2014, including North American oil and gas production centers such as Calgary, Denver, Houston, and Tulsa.” GLOBAL M ETRO MONITOR 2014 A n Uncertain Recovery 23 CONCLUSION The economic growth trajectories of the world’s major metropolitan areas continued to diverge in 2014, reflecting a still uncertain global recovery. Many large metro economies are growing faster than their respective nations, drawing on concentrations of workers, firms, and industrial clusters to spur gains in employment and living standards. Together, the 300 largest metropolitan areas accounted for 47 percent of total global GDP in 2014. Continued growth means that, six years after the global financial crisis, a majority of the world’s metropolitan economies have met or exceeded their pre-recession levels of GDP per capita and employment. However, that recovery is not evenly distributed. Fifty-seven percent of metro areas in North America and 65 percent in Western Europe have yet to achieve full recovery, suggesting that healthy national growth in places like the United States and the United Kingdom has not touched all parts of each country. Optimism in Western economies has been tempered by newfound concerns in emerging markets. Still, even as growth rates cooled in Chinese and Latin American metro areas in 2014, the locus of worldwide growth in jobs and living standards remained decidedly in the South and East. Less wealthy developing metro areas continued to converge with their more developed peers in Europe and North America. The global map of metropolitan economic performance in this year’s Global MetroMonitor reveals a still-tentative and uneven recovery. With half of global economic output centered in these 300 regions, their individual and collective progress will continue to shape prospects for more sustainable and broadly shared growth. Their actions bear watching. “ The uneven pace of economic growth in the world’s major metro areas continued to diverge in 2014, reflecting a still uncertain global recovery.” 24 t h e b r ookings institution metropolitan policy program Appendix A. 300 Largest Metropolitan Economies 2013–2014 Rank Economic Performance 2013-2014 Metro Country 1 Macau 2 3 4 Development Status GDP per Capita Change 2013-2014 Employment Change 20132014 Rank Economic Performance 2009-2014 Recession Status Macau Developed 8.0% 4.2% 10 recovered Izmir Turkey Developing 2.0% 6.6% 8 recovered Istanbul Turkey Developing 2.0% 6.5% 17 recovered Bursa Turkey Developing 1.8% 6.4% 20 recovered 5 Dubai UAE Developed 4.5% 4.7% 172 partially recovered 6 Kunming China Developing 8.1% 2.9% 9 recovered 7 Hangzhou China Developing 7.0% 3.3% 6 recovered 8 Xiamen China Developing 8.6% 2.6% 1 recovered 9 Ankara Turkey Developing 1.1% 5.7% 27 recovered 10 Fuzhou China Developing 8.0% 2.7% 13 recovered 11 Wulumuqi China Developing 7.4% 2.7% 15 recovered 12 Budapest Hungary Developing 2.4% 4.7% 160 partially recovered 13 Wuhan China Developing 9.3% 1.9% 29 recovered 14 Ningbo China Developing 6.8% 2.8% 21 recovered 15 Changsha China Developing 8.6% 1.8% 25 recovered 16 Chengdu China Developing 8.1% 1.9% 18 recovered 17 Wenzhou China Developing 6.6% 2.5% 26 recovered 18 Delhi India Developing 4.4% 3.3% 36 recovered 19 Kuala Lumpur Malaysia Developing 4.1% 3.4% 4 recovered 20 Hefei China Developing 9.5% 1.0% 14 recovered 21 Nanning China Developing 7.2% 1.9% 2 recovered 22 Nantong China Developing 6.9% 1.9% 12 recovered 23 Ho Chi Minh City Vietnam Developing 3.9% 3.1% 46 recovered 24 Xuzhou China Developing 6.9% 1.8% 5 recovered 25 Riyadh Saudi Arabia Developed 1.9% 3.9% 79 recovered 26 London United Kingdom Developed 2.5% 3.6% 85 recovered 27 Jinan China Developing 7.1% 1.7% 53 recovered 28 Suzhou China Developing 6.7% 1.7% 7 recovered 29 Qingdao China Developing 7.1% 1.6% 24 recovered 30 Sofia Bulgaria Developing 2.5% 3.4% 261 recovered 31 Huhehaote China Developing 7.8% 1.2% 33 recovered 32 Kolkata India Developing 4.7% 2.5% 68 recovered 33 Changzhou China Developing 6.8% 1.6% 16 recovered 34 Jakarta Indonesia Developing 4.3% 2.6% 42 recovered 35 Jeddah-Mecca Saudi Arabia Developed 2.4% 3.4% 153 recovered 36 Tangshan China Developing 6.9% 1.5% 37 recovered 37 Dongying China Developing 6.5% 1.7% 11 recovered GLOBAL M ETRO MONITOR 2014 A n Uncertain Recovery 25 Appendix A. 300 Largest Metropolitan Economies 2013–2014 (continued) Rank Economic Performance 2013-2014 26 Metro Country Development Status GDP per Capita Change 2013-2014 38 Austin USA Developed 1.9% 3.6% 65 recovered 39 Houston USA Developed 1.6% 3.7% 74 recovered 40 Chongqing China Developing 7.3% 1.2% 28 recovered 41 Raleigh USA Developed 0.8% 4.0% 112 partially recovered 42 Baotou China Developing 7.5% 1.1% 23 recovered 43 Yantai China Developing 6.8% 1.4% 30 recovered 44 Nanjing China Developing 6.5% 1.5% 22 recovered 45 Zhongshan China Developing 5.8% 1.8% 19 recovered 46 Medellin Colombia Developing 4.2% 2.4% 57 recovered 47 George Town Malaysia Developing 3.8% 2.6% 52 recovered 48 Lima Peru Developing 2.9% 2.9% 54 recovered 49 Fresno USA Developed -0.9% 4.5% 196 partially recovered 50 Zibo China Developing 6.6% 1.3% 35 recovered 51 Wuxi China Developing 6.4% 1.3% 3 recovered 52 Mumbai India Developing 4.6% 2.1% 67 recovered 53 Calgary Canada Developed 3.1% 2.7% 115 partially recovered 54 Zhengzhou China Developing 7.8% 0.7% 38 recovered 55 Nanchang China Developing 6.6% 1.2% 40 recovered 56 Shijiazhuang China Developing 6.5% 1.2% 45 recovered 57 Chennai India Developing 5.2% 1.7% 66 recovered 58 Foshan China Developing 5.6% 1.5% 61 recovered 59 Daejon South Korea Developed 3.0% 2.6% 90 recovered 60 Manchester United Kingdom Developed 2.6% 2.8% 236 partially recovered 61 Singapore Singapore Developed 1.8% 3.1% 48 recovered 62 Edmonton Canada Developed -0.6% 4.0% 71 recovered Employment Change 20132014 Rank Economic Performance 2009-2014 Recession Status 63 Dallas USA Developed 0.8% 3.4% 94 recovered 64 Shenzhen China Developing 5.1% 1.6% 31 recovered 65 Baton Rouge USA Developed 1.5% 3.0% 138 recovered 66 Oklahoma City USA Developed 1.8% 2.9% 103 recovered 67 Beijing China Developing 4.7% 1.6% 58 recovered 68 Las Vegas USA Developed 1.3% 3.0% 210 not recovered 69 Grand Rapids USA Developed 0.6% 3.3% 73 partially recovered 70 Dongguan China Developing 5.2% 1.4% 80 recovered 71 Edinburgh United Kingdom Developed 1.5% 2.9% 187 partially recovered 72 San Jose USA Developed 0.2% 3.4% 72 recovered 73 Orlando USA Developed 0.1% 3.5% 147 partially recovered t h e b r ookings institution metropolitan policy program Appendix A. 300 Largest Metropolitan Economies 2013–2014 (continued) Rank Economic Performance 2013-2014 Metro 74 Country Development Status GDP per Capita Change 2013-2014 Vancouver Canada Developed 3.7% 1.9% 132 recovered 75 Perth Australia Developed 3.4% 2.1% 64 recovered 76 Hyderabad India Developing 4.2% 1.7% 82 recovered 77 Guangzhou China Developing 4.9% 1.4% 34 recovered 78 Alexandria Egypt Developing 0.9% 3.0% 170 recovered 79 Bristol United Kingdom Developed 2.1% 2.5% 269 partially recovered 80 Quebec City Canada Developed 2.1% 2.4% 145 recovered 81 Liverpool United Kingdom Developed 2.4% 2.3% 217 partially recovered 82 Cairo Egypt Developing 0.7% 3.0% 41 recovered Employment Change 20132014 Rank Economic Performance 2009-2014 Recession Status 83 Jacksonville USA Developed 0.6% 3.0% 194 not recovered 84 NottinghamDerby United Kingdom Developed 2.6% 2.2% 226 not recovered 85 Taiyuan China Developing 5.6% 0.9% 55 recovered 86 Nashville USA Developed 0.7% 2.9% 76 recovered 87 Bangalore India Developing 4.3% 1.4% 98 recovered 88 Bogota Colombia Developing 3.2% 1.8% 60 recovered 89 Gwangju South Korea Developed 2.8% 2.0% 89 recovered 90 Zhuhai China Developing 4.4% 1.3% 50 recovered 91 PortsmouthSouthampton United Kingdom Developed 2.1% 2.2% 227 partially recovered 92 Shanghai China Developing 5.2% 0.9% 129 recovered 93 Daegu South Korea Developed 3.1% 1.8% 84 recovered 94 Taoyuan Taiwan Developed 3.7% 1.5% 59 recovered 95 Denver USA Developed 0.8% 2.7% 116 recovered 96 Birmingham United Kingdom Developed 2.2% 2.1% 206 not recovered 97 Kuwait Kuwait Developed 0.6% 2.7% 77 partially recovered 98 Xi'an China Developing 7.2% 0.0% 49 recovered 99 Knoxville USA Developed 1.3% 2.4% 183 recovered 100 Atlanta USA Developed 1.5% 2.3% 169 partially recovered 101 Glasgow United Kingdom Developed 2.6% 1.8% 290 not recovered 102 Changchun China Developing 7.2% -0.1% 44 recovered 103 Riverside USA Developed 0.2% 2.8% 182 not recovered 104 Portland USA Developed 0.6% 2.6% 91 recovered 105 Seoul-Incheon South Korea Developed 2.7% 1.7% 88 recovered 106 Leeds-Bradford United Kingdom Developed 2.0% 2.0% 271 not recovered 107 Casablanca Morocco Developing 1.9% 2.1% 146 recovered 108 Cracow Poland Developed 3.7% 1.3% 257 recovered GLOBAL M ETRO MONITOR 2014 A n Uncertain Recovery 27 Appendix A. 300 Largest Metropolitan Economies 2013–2014 (continued) Rank Economic Performance 2013-2014 Metro Country 109 Shenyang 110 Charlotte 111 28 Development Status GDP per Capita Change 2013-2014 Employment Change 20132014 Rank Economic Performance 2009-2014 Recession Status China Developing 6.7% 0.0% 39 recovered USA Developed 1.1% 2.3% 110 partially recovered Greenville USA Developed 0.7% 2.4% 121 partially recovered 112 Sheffield United Kingdom Developed 2.1% 1.8% 273 not recovered 113 Newcastle United Kingdom Developed 1.9% 1.9% 240 not recovered 114 Brisbane Australia Developed -0.4% 2.8% 180 recovered 115 Seattle USA Developed 0.1% 2.5% 137 recovered 116 Miami USA Developed -0.5% 2.8% 161 not recovered 117 Hsinchu Taiwan Developed 3.5% 1.1% 70 recovered 118 Salt Lake City USA Developed -0.2% 2.7% 97 recovered 119 KatowiceOstrava Poland Developed 3.5% 1.1% 163 recovered 120 Dalian China Developing 6.5% -0.2% 32 recovered 121 Busan-Ulsan South Korea Developed 2.8% 1.3% 106 recovered 122 Sacramento USA Developed 1.1% 2.0% 216 not recovered 123 Lisbon Portugal Developed 1.3% 2.0% 292 not recovered 124 CardiffNewport United Kingdom Developed 1.7% 1.7% 272 not recovered 125 San Francisco USA Developed -0.5% 2.6% 118 partially recovered 126 Anshan China Developing 6.3% -0.3% 47 recovered 127 Tainan Taiwan Developed 3.6% 0.9% 93 recovered 128 Taichung Taiwan Developed 3.1% 1.0% 87 recovered 129 Porto Portugal Developed 1.0% 1.9% 294 not recovered 130 Kaohsiung Taiwan Developed 3.5% 0.9% 101 recovered 131 San Antonio USA Developed -0.2% 2.4% 107 recovered 132 Warsaw Poland Developed 1.9% 1.5% 127 recovered 133 Phoenix USA Developed 0.7% 2.0% 159 not recovered 134 Dublin Ireland Developed 1.7% 1.5% 288 not recovered 135 Taipei Taiwan Developed 2.9% 1.0% 86 recovered 136 Milwaukee USA Developed 1.3% 1.6% 211 not recovered 137 Abu Dhabi UAE Developed 0.3% 2.1% 78 partially recovered 138 Durham USA Developed 1.2% 1.7% 231 partially recovered 139 Manila Philippines Developing 4.1% 0.5% 69 recovered 140 Indianapolis USA Developed 0.6% 1.9% 144 recovered 141 Tampa USA Developed 0.7% 1.8% 171 not recovered 142 San Diego USA Developed -0.4% 2.3% 162 partially recovered t h e b r ookings institution metropolitan policy program Appendix A. 300 Largest Metropolitan Economies 2013–2014 (continued) Rank Economic Performance 2013-2014 Metro Country 143 Shantou 144 Development Status GDP per Capita Change 2013-2014 Employment Change 20132014 Rank Economic Performance 2009-2014 China Developing 4.0% 0.4% 56 partially recovered Madison USA Developed 0.3% 2.0% 168 recovered 145 Auckland New Zealand Developed 2.4% 1.1% 105 recovered 146 Des Moines USA Developed 0.0% 2.0% 139 partially recovered 147 Mexico City Mexico Developing 1.6% 1.4% 96 recovered 148 Los Angeles USA Developed 0.1% 2.0% 164 not recovered Recession Status 149 Tucson USA Developed 1.2% 1.4% 228 not recovered 150 Guadalajara Mexico Developing 0.8% 1.5% 114 recovered 151 Baltimore USA Developed 1.0% 1.5% 157 recovered 152 Tianjin China Developing 3.3% 0.5% 43 recovered 153 Boston USA Developed 0.5% 1.6% 149 recovered 154 Stockholm Sweden Developed 0.9% 1.5% 130 recovered 155 Oslo Norway Developed 1.4% 1.2% 166 recovered 156 Almaty Kazakhstan Developing 2.6% 0.7% 51 recovered 157 East Rand South Africa Developing 0.1% 1.8% 131 recovered 158 Tulsa USA Developed 0.8% 1.4% 202 recovered 159 Springfield USA Developed 1.7% 1.0% 175 recovered 160 Santiago Chile Developed 1.2% 1.2% 62 recovered 161 Prague Czech Republic Developed 1.9% 0.9% 265 partially recovered 162 Rio de Janeiro Brazil Developing -0.2% 1.8% 133 recovered 163 Pretoria South Africa Developing -0.9% 2.0% 150 recovered 164 Tel Aviv Israel Developed 1.4% 1.0% 75 recovered 165 Gothenburg Sweden Developed 1.0% 1.1% 141 recovered 166 Minneapolis USA Developed -0.1% 1.6% 148 recovered 167 Munich Germany Developed 0.9% 1.1% 124 recovered 168 Honolulu USA Developed 1.4% 1.0% 185 recovered 169 Nürnberg-Fürth Germany Developed 1.6% 0.9% 135 recovered 170 Zurich Switzerland Developed 0.4% 1.3% 174 partially recovered 171 Berlin Germany Developed 1.1% 1.0% 143 recovered 172 Haerbin China Developing 6.1% -1.1% 95 partially recovered 173 Johannesburg South Africa Developing -1.3% 2.0% 152 recovered 174 Fortaleza Brazil Developing -0.2% 1.6% 158 recovered 175 El Paso USA Developed 0.6% 1.2% 109 recovered 176 New York USA Developed 0.1% 1.4% 176 recovered 177 LuxembourgTrier Luxembourg Developed 1.4% 0.9% 181 partially recovered GLOBAL M ETRO MONITOR 2014 A n Uncertain Recovery 29 Appendix A. 300 Largest Metropolitan Economies 2013–2014 (continued) Rank Economic Performance 2013-2014 Metro Country 178 Bakersfield 179 30 Development Status GDP per Capita Change 2013-2014 Employment Change 20132014 Rank Economic Performance 2009-2014 USA Developed -2.4% 2.4% 108 partially recovered Hannover Germany Developed 1.4% 0.8% 188 recovered 180 Linz Austria Developed 0.8% 1.1% 167 recovered 181 Curitiba Brazil Developing -0.5% 1.6% 119 recovered 182 Madrid Spain Developed 1.4% 0.8% 295 not recovered 183 ViennaBratislava Austria Developed 0.6% 1.2% 213 recovered 184 Worcester USA Developed 0.9% 1.0% 155 recovered 185 GenèveAnnemasse Switzerland Developed 0.3% 1.3% 128 partially recovered 186 Louisville USA Developed 0.2% 1.3% 142 recovered 187 Belo Horizonte Brazil Developing -0.3% 1.5% 102 recovered 188 Cape Town South Africa Developing -1.2% 1.9% 179 partially recovered 189 Leipzig-Halle Germany Developed 1.5% 0.7% 156 recovered 190 Richmond USA Developed -0.3% 1.5% 186 partially recovered 191 Hamburg Germany Developed 0.8% 1.0% 199 recovered 192 Karlsruhe Germany Developed 1.2% 0.8% 165 recovered 193 Grande Vitoria Brazil Developing -0.1% 1.3% 122 recovered 194 BraunschweigWolfsburg Germany Developed 1.4% 0.7% 92 recovered 195 San Juan Puerto Rico Developed 0.4% 1.1% 289 not recovered 196 Harrisburg USA Developed 0.2% 1.2% 246 not recovered 197 Toronto Canada Developed 1.4% 0.7% 117 recovered 198 Akron USA Developed -0.5% 1.4% 200 not recovered 199 Durban South Africa Developing -1.2% 1.7% 235 partially recovered 200 Recife Brazil Developing 0.2% 1.1% 63 recovered 201 Tokyo Japan Developed 0.7% 0.9% 204 recovered 202 Bremen Germany Developed 1.2% 0.7% 190 recovered 203 Chicago USA Developed 0.7% 0.8% 198 not recovered 204 Bilbao Spain Developed 1.7% 0.4% 297 not recovered 205 Frankfurt am Main Germany Developed 0.7% 0.8% 203 partially recovered Recession Status 206 Sydney Australia Developed 1.4% 0.5% 151 recovered 207 BielefeldDetmold Germany Developed 1.2% 0.6% 134 recovered 208 KölnDüsseldorf Germany Developed 1.0% 0.7% 215 recovered 209 Brasilia Brazil Developing -0.7% 1.4% 99 recovered 210 Stuttgart Germany Developed 1.1% 0.6% 140 recovered t h e b r ookings institution metropolitan policy program Appendix A. 300 Largest Metropolitan Economies 2013–2014 (continued) Rank Economic Performance 2013-2014 Metro Country Development Status GDP per Capita Change 2013-2014 211 Oxnard USA Developed -1.0% 1.5% 222 not recovered 212 Greensboro USA Developed 0.7% 0.7% 250 not recovered 213 Cincinnati USA Developed -1.2% 1.5% 178 partially recovered 214 Little Rock USA Developed 0.5% 0.8% 224 recovered 215 Barcelona Spain Developed 1.2% 0.4% 296 not recovered 216 Omaha USA Developed -0.1% 1.0% 191 recovered 217 Birmingham USA Developed 0.4% 0.8% 220 partially recovered 218 Moscow Russia Developed 0.0% 0.9% 120 partially recovered 219 Monterrey Mexico Developing 0.5% 0.7% 113 recovered 220 Saarbrucken Germany Developed 1.4% 0.3% 225 not recovered 221 Haifa Israel Developed 1.5% 0.3% 81 recovered 222 Hamamatsu Japan Developed 1.7% 0.2% 244 partially recovered 223 Shizuoka Japan Developed 1.7% 0.1% 245 partially recovered 224 Nagoya Japan Developed 1.0% 0.4% 252 not recovered 225 New Haven USA Developed 0.5% 0.6% 223 not recovered 226 Providence USA Developed -0.7% 1.1% 207 partially recovered 227 Melbourne Australia Developed 1.1% 0.3% 154 recovered 228 Columbia USA Developed -0.1% 0.8% 205 not recovered 229 Ottawa Canada Developed 0.1% 0.7% 238 partially recovered 230 Puebla Mexico Developing 0.0% 0.8% 83 recovered 231 Kumamoto Japan Developed 1.3% 0.2% 232 partially recovered 232 KitakyushuFukuoka Japan Developed 0.9% 0.3% 219 recovered 233 Toulouse France Developed -0.1% 0.7% 197 recovered 234 New Orleans USA Developed -2.0% 1.5% 229 partially recovered 235 Memphis USA Developed -0.2% 0.7% 270 not recovered Employment Change 20132014 Rank Economic Performance 2009-2014 Recession Status 236 Albany USA Developed 0.1% 0.6% 234 recovered 237 Detroit USA Developed 0.8% 0.3% 104 not recovered 238 Buffalo USA Developed -0.1% 0.6% 230 recovered 239 Hartford USA Developed 0.3% 0.4% 258 not recovered 240 Seville Spain Developed 0.9% 0.1% 299 not recovered 241 Sendai Japan Developed 0.8% 0.2% 268 partially recovered 242 Hong Kong Hong Kong Developed 1.2% 0.0% 100 recovered GLOBAL M ETRO MONITOR 2014 A n Uncertain Recovery 31 Appendix A. 300 Largest Metropolitan Economies 2013–2014 (continued) Rank Economic Performance 2013-2014 Metro Country 243 Kagoshima 244 32 Development Status GDP per Capita Change 2013-2014 Employment Change 20132014 Rank Economic Performance 2009-2014 Japan Developed 1.3% 0.0% 208 partially recovered Nantes France Developed -0.2% 0.6% 201 recovered 245 Okayama Japan Developed 1.1% 0.1% 266 not recovered 246 CopenhagenMalmö Denmark Developed 0.7% 0.2% 256 not recovered 247 Osaka-Kobe Japan Developed 0.6% 0.2% 267 not recovered 248 Basel-Mulhouse Switzerland Developed 0.4% 0.3% 214 recovered 249 St. Louis USA Developed -2.1% 1.3% 253 not recovered 250 Philadelphia USA Developed -0.5% 0.7% 248 not recovered 251 Bordeaux France Developed -0.2% 0.5% 212 recovered 252 Valencia Spain Developed 0.9% 0.1% 298 not recovered 253 Pittsburgh USA Developed 0.0% 0.4% 192 recovered 254 Sapporo Japan Developed 0.9% 0.0% 274 partially recovered 255 Niigata Japan Developed 1.2% -0.1% 242 partially recovered 256 Rochester USA Developed -0.1% 0.4% 237 partially recovered 257 Bridgeport USA Developed -0.2% 0.4% 241 not recovered 258 Cleveland USA Developed -0.9% 0.7% 189 partially recovered 259 Marseille France Developed 0.1% 0.3% 263 recovered 260 Paris France Developed 0.3% 0.2% 247 recovered 261 Saint Petersburg Russia Developed -0.2% 0.4% 125 recovered 262 Brussels Belgium Developed 0.4% 0.0% 262 partially recovered 263 Aachen-Liège Belgium Developed 0.7% -0.1% 243 partially recovered 264 Kansas City USA Developed -1.3% 0.7% 233 not recovered 265 Lille France Developed 0.4% 0.0% 264 partially recovered 266 Salvador Brazil Developing -0.9% 0.5% 218 partially recovered 267 Hiroshima Japan Developed 0.5% -0.1% 275 not recovered 268 Lyon France Developed -0.2% 0.2% 239 partially recovered 269 Nice France Developed 0.0% 0.1% 277 not recovered 270 Strasbourg France Developed 0.0% 0.1% 260 partially recovered 271 Bucharest Romania Developing 1.7% -0.7% 173 recovered 272 Allentown USA Developed -0.3% 0.1% 193 recovered 273 Columbus USA Developed -1.3% 0.4% 126 recovered 274 Rome Italy Developed -0.8% 0.1% 284 not recovered t h e b r ookings institution metropolitan policy program Recession Status Appendix A. 300 Largest Metropolitan Economies 2013–2014 (continued) Rank Economic Performance 2013-2014 Metro Country 275 Washington 276 Development Status GDP per Capita Change 2013-2014 Employment Change 20132014 Rank Economic Performance 2009-2014 USA Developed -1.5% 0.3% 251 partially recovered Bologna Italy Developed -0.4% -0.1% 255 partially recovered 277 Milan Italy Developed -0.5% -0.2% 283 not recovered 278 Venice-Padova Italy Developed -0.6% -0.2% 280 not recovered 279 Winnipeg Canada Developed -0.2% -0.4% 221 recovered 280 Athens Greece Developed 0.3% -0.6% 300 not recovered 281 Virginia Beach USA Developed -1.0% -0.1% 279 not recovered 282 Helsinki Finland Developed -0.5% -0.3% 278 partially recovered 283 Turin Italy Developed -0.7% -0.3% 282 not recovered 284 Sao Paulo Brazil Developing -1.5% 0.0% 136 recovered 285 Montreal Canada Developed 0.7% -0.9% 184 recovered 286 Buenos Aires Argentina Developing -2.8% 0.5% 123 recovered Recession Status 287 Dayton USA Developed -1.7% 0.0% 254 not recovered 288 Eindhoven-Den Bosch Netherlands Developed 0.7% -1.1% 281 not recovered 289 Florence Italy Developed -0.6% -0.6% 291 not recovered 290 Porto Alegre Brazil Developing -1.7% -0.2% 177 partially recovered 291 Campinas Brazil Developing -2.2% 0.0% 195 recovered 292 RotterdamAmsterdam Netherlands Developed 0.3% -1.2% 287 not recovered 293 Daqing China Developing 4.0% -2.8% 111 partially recovered 294 Syracuse USA Developed -1.2% -0.7% 276 not recovered 295 ArnhemNijmegen Netherlands Developed 0.0% -1.2% 286 not recovered 296 Caracas Venezuela Developing -3.5% 0.1% 209 recovered 297 Naples Italy Developed -0.7% -1.0% 293 not recovered 298 Albuquerque USA Developed -2.2% -0.6% 285 not recovered 299 Adelaide Australia Developed -1.2% -1.1% 249 recovered 300 Bangkok Thailand Developing -0.5% -1.7% 259 partially recovered GLOBAL M ETRO MONITOR 2014 A n Uncertain Recovery 33 APPENDIX B: Methods Selection and Definition of Metropolitan Areas The fourth edition of the Global MetroMonitor employs the size of each metropolitan economy as the main selection criterion, given the focus on metropolitan economic performance. As with previous installments of the series, the sample is composed of the 300 largest metropolitan areas for which economic and industrial data were available, based on the size of their respective economies in 2014 at purchasing power parity rates. The sample of metropolitan areas is based upon a list of international metros provided by Oxford Economics, as well as a list of the largest metropolitan economies in the United States built with data provided by Moody’s Analytics. This study uses the general definition of a metropolitan area as an economic region with one or more cities and their surrounding areas, all linked by economic and commuting ties. In the United States, metro areas are defined by the federal Office of Management and Budget (OMB) to include one or more urbanized areas of at least 50,000 inhabitants, plus outlying areas connected by commuting flows.27 For the European Union countries, Switzerland, and Norway, the European Observation Network for Territorial Development and Cohesion (ESPON) defines metro areas as having one or more functional urban areas of more than 500,000 inhabitants.28 This study uses the most accurate metropolitan area compositions of European metro areas, because the current ESPON 2013 database employs commuting data at the municipal level to define functional urban areas, the building blocks of metropolitan areas.29 This identification method is most consistent with the U.S. definition of metro areas based on commuting links, with the possibility of a metro area crossing jurisdictional borders, and having multiple cities included. For metropolitan areas outside of the United States and Europe, this study uses the official metropolitan area definition from national statistics. Not all countries, especially developing ones, have created statistical equivalents of a metropolitan area. Due to data limitations, some metropolitan areas in this report do not properly reflect regional economies, but the federal city (Moscow, St. Petersburg, Caracas), provincial-level and prefecture-level cities in China, municipality (Ho Chi Minh City), or administrative region (Casablanca). Baseline Variables and Data Sources This Global MetroMonitor employs several key variables to assess the economic performance of metropolitan areas: gross domestic product (GDP), employment, population, and GDP per capita, all from 2000 to 2014. In addition, the study uses gross value added (GVA) and employment by major industry sector. For static analysis, this study employs nominal GDP and GVA data at purchasing power parity rates. For trends analysis, it uses GDP and GVA data at 2009 prices and expressed in U.S. dollars.30 Data availability and comparability at metropolitan level precluded expanding the economic analysis to other indicators of interest, such as housing prices, employment rates, unemployment rates, and income distributions. This edition employs two main databases for analysis: Moody’s Analytics for metropolitan areas in the United States and Oxford Economics for the rest of the sample. For the United States, this study also uses the U.S. Census Bureau’s population estimates. To generate GDP by metropolitan area, this study sums county-level GDP estimates from Moody’s Analytics using county-based metropolitan area definitions.31 Oxford Economics collects data from national statistics bureaus in each country or from providers such as Haver, ISI Emerging Markets, and Eurostat. It then calculates forecasted metropolitan GDP as the sum of forecasted industry GVA at the metropolitan level.32 For population, this study uses the U.S. Census Bureau’s intercensal population estimates for the United States and data collected by Oxford Economics from relevant national statistical agencies for the rest of the sample. To forecast 2014 population for U.S. metro areas, annualized growth rates from 2008 to 2013 are applied to 2013 estimates. Oxford Economics forecasts metropolitan population based on official population projections produced by national statistical agencies and/or organizations such as Eurostat, adjusting migration assumptions on a case-bycase basis. For 44 of the 48 Chinese metropolitan areas included in the report, Brookings took an additional step to process the industry-level employment estimates. China’s National Bureau of Statistics generates industry-level employment, as well as a general category called ‘private and individual employees.’ Given the high volatility that characterizes this latter series, Brookings employed an autoregressive moving average model.33 This model applied a weighted moving average filter with one lag period, one current period, and one future period, and assigned weights of 1, 1.5, and 1, respectively. Once private employment was smoothed, Brookings allocated total private and individual employees to the industry-level employment categories in proportion to their share of the total for that 34 t h e b r ookings institution metropolitan policy program metropolitan area. This process was repeated for all of the metro areas with private and individual employees, for all years between 2000 and 2014. For industry analysis, this report collected industry-level data and estimates for metropolitan employment and GVA. This edition uses the eight major industrial sectors from the previous edition of Global MetroMonitor, for which GVA and employment data were available at the metropolitan level (see Table A1). In large part, this industrial identification was driven by data availability, with the goal of reaching a balance between industry disaggregation and consistency of categories across metros and countries. Table A1. Industry Categories in Global MetroMonitor 2014 Industry Category Commodities Agriculture, Forestry, Fishing and Hunting Approximate NAICS Code 11 Mining, Quarrying, Oil and Gas Extraction 21 31-33 Manufacturing Manufacturing Utilities Utilities 22 Construction Construction 23 Wholesale Trade 42 Trade and Tourism Retail Trade Accommodation and Food Services 44-45 72 48-49 Transportation Transportation and Warehousing Business, Financial and Professional Services Finance and Insurance 52 Real State and Rental and Leasing 53 Professional, Scientific and Technical Services 54 Management of Companies and Enterprises 55 Administrative and Support and Waste Management and Remediation Services 56 Educational Services 61 Health Care and Social Assistance 62 Arts, Entertainment and Recreation 71 Other Services (Except Public Administration) 81 Government (Public Administration) 92 Information 51 Local non-Market Services For U.S. metro areas, Moody’s Analytics provides GVA and employment by industry, using the North American Industry Classification System (NAICS) 2007. For European metro areas, Oxford Economics collects GVA and employment by industry, based on the Statistical Classification of Economic Activities in the European Community (NACE) version 2. For metro areas outside of the United States and Europe, Oxford Economics reports data available from local and national statistical agencies. Moody’s Analytics bases industry employment forecasts for U.S. metro areas on two U.S. Bureau of Labor Statistics series: the monthly Current Employment Statistics (CES) and the Quarterly Census of Employment and Wages (QCEW). In forecasting industry GVA and employment for metro areas, Oxford Economics employs different methods depending on the type of industry. For tradable sectors (primary industries and business and financial services), the GVA forecasts take into account the historical relationship between the industry’s growth in a particular metro area compared with the respective national average. Public services forecasts follow the same method, adding metro population to reflect the nature of demand for local services. GVA forecasts for trade and tourism and transportation are modeled against the performance of the previous two categories of industries (tradable sectors and public services), to reflect local multiplier effects. Industry employment forecasts are based on GVA industry forecasts and trends in labor productivity. GLOBAL M ETRO MONITOR 2014 A n Uncertain Recovery 35 Metro Economic Performance Score The report focuses on the economic performance of metropolitan areas using a standardized score composed of two indicators: the annualized growth rate of real GDP per capita and the annualized growth rate of employment. These two indicators reflect the importance that people and policymakers attach to achieving rising incomes and standards of living (GDP per capita), as well as generating widespread labor market opportunity (employment). Identifying economic data available across the entire sample of 300 metro areas limited the choice and number of additional indicators to be included in the standardized score. For example, while changes in the employment rate or the unemployment rate may better indicate labor market opportunity, there are no consistent data on the number of unemployed people or the size of the labor force across metropolitan areas worldwide. The scoring method compares each value of a variable (Xi) to the median (Xmed), then divides their difference by the distance between the value of that variable at the 90th percentile of the distribution (X90) and the 10th percentile (X10): Standardized score = X –X i med _____________ X90 – X10 Each of the two indicators (annualized growth rates of income [GDP per capita] and employment) is standardized using this method for the time period corresponding to 2013–2014, as well as for compound growth rates for both indicators for the 2009–2014 period. Once standardized, the scores for each of the two indicators are added for each metro area, thereby yielding a total score and ranking for each metro area for each time period. Inter-decile range standardization helps minimize the influence of outliers by using the 90th and the 10th percentile values instead of the minimum and maximum values, and best reflects the non-normal distribution of metro economic growth rates. This method was judged more appropriate for these data than Z-score standardization, which compares each value of a variable to the mean and divides their difference by the standard deviation, as they do not follow a normal distribution. It was also preferred to range standardization (which compares each value of a variable to the minimum and divides their residual by the distance between the minimum and the maximum) because of the sensitivity of this latter method to outliers. Comparison across Regions, Industries, and Specializations In the report we present comparisons of metropolitan areas grouped by industries, regions, development status, and industry specializations. To conduct this analysis rather than present the average of an indicator (income or employment growth) by category, we calculate the absolute level of that indicator according to the category of analysis. For example, when calculating income growth by development status, this study did not average the growth rate of all metro areas in developing countries; rather, it summed the real GDP of all metros in that category and divided it by total population of metros in the same category. This approach was selected because it reduces the weight of observations with extreme values in a specific indicator, but with a small share in the total. Metropolitan Specialization Based on their industrial mix in 2013–2014, this study classifies metropolitan areas into seven industrial specializations, reflecting the eight categories described above, with construction and local non-market services grouped into one category. Industrial specializations were assigned using location quotients, which are based on the ratio of an industry’s share of real GVA divided by the industry’s share of national real GVA. The industry specialization was determined by the highest location quotient, as long as this ratio was higher than 1.25 and that industry represented more than 5 percent of metropolitan output in 2014. The location quotient was determined based on real GVA industrial data, rather than employment, due to better data quality. Four metropolitan areas were excluded because they coincide with the country baseline (Singapore, Kuwait, Hong Kong, and Macau). While industry specialization in a particular metro area relative to the world or other metro areas in its world region might be more appropriate for the scope of this report, the available data limits such classification. There is a larger degree of consistency in the data collection and estimation methodology for the industry output of a metro and its country than across metros in different countries. 36 t h e b r ookings institution metropolitan policy program Endnotes 1. The International Monetary Fund, “World Economic Outlook: 14. Dennis Domrzalski, “Brookings: Albuquerque in double-dip recession,” Albuquerque Business First, June 25, 2014 Legacies, Clouds, Uncertainties” (Washington: International Monetary Fund, 2014). 2. 3. 15. IMF, “World Economic Outlook.” 16. The four excluded metro economies are Hong Kong, Kuwait, Ibid. Macau, and Singapore. See Appendix B for more details. Alan Berube and Philipp Rode, “Global MetroMonitor” (Washington and London: Brookings Institution and London School of Economics, 2010). 17. Mario Toneguzzi, “RBC says outlook strong for Alberta’s economy,” Calgary Herald, September 10, 2014. 4. Data are currently unavailable to compare the distribution of income gains across global metropolitan areas. Employment 18. It is important to take into consideration the nature of the avail- growth, in addition to GDP per capita growth, provides an indirect able data for population and employment for Chinese cities. The measure of whether increased labor market opportunity is current methodology measures levels of employment using pro- accompanying growth in the average standard of living. vincial-level and prefecture-level city definitions. The geographic footprint of Chinese cities also varies significantly, especially the extent to which formally defined municipalities incorporate large 5. Berube and Rode, “Global Metro Monitor.” 6. Data for 2014 are forecasts based on annual trends and data for not be considered a traditional metropolitan commuter sheds. As the first two quarters of 2014. a result these estimates do not necessarily reflect employment surrounding areas that may include additional cities that may levels of traditional metropolitan area but of a larger geographic 7. Sources for definitions: U.S. Bureau Analysis, International unit. Additionally, for 44 of the 48 Chinese metros included in this Labor Organization, United Nations Department of Economic report, statistics on employment are divided in two categories: and Social Affairs. private employment and employment in government-owned companies. The private employment is subject to high volatility 8. Economic performance in this study refers to how well an due (among other factors) to significant levels of migration from economy is doing in terms of growth of GDP per capita and rural to urban areas. Chinese authorities in different localities employment. and at different administrative levels count rural migrants as urban residents at different paces, thus creating high variation 9. Some European metro areas straddle national borders; for pur- in employment levels from one year to the other. To control for poses of this analysis, these metro areas are considered to lie in some of that volatility, Brookings employed an autoregressive the country in which most of the population resides or where the moving average model (see Appendix B). namesake city lies. 19. 10. “Tianjin economy slows after rise to top GDP per capita,” Want China Times, July 24, 2014. See World Bank list of economies as of July 1, 2014. The income classifications are in effect until July 1, 2015. 20. Juan Zhao, “Research on the Financing of Small and Medium 11. 12. While the World Bank explains that a country’s classification by Enterprises,” International Journal of Business and Management income does not necessarily reflect development status, it does (3)11 (2008): 171–174. Liu Xiangfeng, “SME Development in China: note that countries with lower- and middle-income levels are A Policy Perspective on SME Industrial Clustering,” in Hank Lim, sometimes referred to as “developing,” for the convenience of ed., SMEs in Asia and Globalization, (Economic Research Institute the term. for ASEAN and Asia, 2008). These geographical regions are not identical to the regions used 21. Nancy Huang, Joie Ma, and Kyle Sullivan, “Economic Development by the World Bank and the International Monetary Fund, given the Policies for Central and Western China,” China Business Review, insufficient number of metropolitan areas in this study’s sample November 1, 2010. from certain regions. 22. “The next China,” The Economist, July 29, 2010. 13. Fan Feifei, “Tourism aids Macao’s growth after its return to motherland,” China Daily, December 10, 2014. GLOBAL M ETRO MONITOR 2014 A n Uncertain Recovery 37 23. “City partners with Alibaba on E-commerce expo,” available at: 31. The GDP by county, estimated or forecasted, is obtained by allo- www.hangzhou.gov.cn/main/zpd/English/CityNews/T497363. cating U.S. Bureau of Economic Analysis’ state GDP to component shtml (December 2014). counties based on the counties’ share of employment in the state employment. Moody’s Analytics uses the Bureau of Labor 24. Oil prices have collapsed more than 40 percent over the past Statistics Quarterly Census of Employment and Wages (QCEW) as six months. “The new economics of oil,” The Economist, basis for the county employment estimates. For real GDP, Moody’s December 6, 2014. uses chain-weighting for every industry. 25. World Trade Organization, “World Trade Report 2014” (2014). 32. It is also important to mention that Moody’s Analytics GDP figures are lower than what other international agencies such 26. United Nations World Tourism Organization, “Annual Report 2013” (2014). as the IMF publish for the United States. This results in a more accurate depiction of the state of the U.S. economy, but results in an underestimation of economic performance when compared to 27. For this installment of the Global MetroMonitor, Brookings used other countries and metropolitan peers. the 2013 metropolitan statistical areas delineations defined by the U.S. Office of Management and Budget. U.S. Office of 33. Philip Hans Franses, Time Series Models for Business and Management and Budget, Revised Delineations of Metropolitan Economic Forecasting, (Cambridge: Cambridge University Press, Statistical Areas, Micropolitan Statistical Areas, and Combined 1998). Statistical Areas, and Guidance on Uses of the Delineations of These Areas, OMB BULLETIN NO. 13-01 (U.S. Office of Management and Budget, 2013). 28. European Observation Network for Territorial Development and Cohesion (ESPON), Study on Urban Functions, ESPON Project 1.4.3 (European Observation Network for Territorial Development and Cohesion, 2007). ESPON is a European Commission program, funded by the Commission, the European Union member countries, Iceland, Lichtenstein, Norway, and Switzerland. See ESPON, ESPON 2013 Programme, available at www.espon.eu/main/Menu_ Programme/Menu_Mission/. 29. ESPON Database 2013 and Personal Communication from Didier Peeters, researcher, the Institute for Environmental Management and Land-use Planning, Free University of Brussels, May 2012. For a discussion of metropolitan areas and functional urban areas in Europe, see Didier Peeters, “The Functional Urban Areas Database Technical Report” (European Observation Network for Territorial Development and Cohesion (ESPON), March 2011). 30. The purchasing power parity (PPP) rates come from a variety of sources such as the International Monetary Fund, the European Central Bank, and other national statistics agencies. If national and metropolitan GDP and industry GVA data were available both in current and constant prices, Oxford Economics rebased the constant price series to 2009 for consistency, and then applied the 2009 USD exchange rate (which come from various national statistics offices) to the whole series. Where constant price series were not available for a metropolitan area, Oxford Economics used the respective national industry deflators to create constant price series for that specific metropolitan area. 38 t h e b r ookings institution metropolitan policy program About The Global Cities Initiative The Global Cities Initiative aims to equip metropolitan leaders with the information, policy ideas, and global connections they need to bolster their position within the global economy. Combining Brookings’ deep expertise in factbased, metropolitan-focused research and JPMorgan Chase’s longstanding commitment to investing in cities, this initiative aims to: ➤➤ Help city and metropolitan leaders in the United States and abroad better leverage their global assets by unveiling their economic starting points on such key indicators as advanced manufacturing, exports, foreign direct investment, freight flow, and immigration. ➤➤ Provide metropolitan area leaders with proven, actionable ideas for how to expand the global reach of their economies, building on best practices and policy innovations from across the nation and around the world. ➤➤ Create a network of leaders from global cities intent upon deepening global trade relationships. The Global Cities Initiative is chaired by Richard M. Daley, former mayor of Chicago and senior advisor to JPMorgan Chase, and directed by Bruce Katz, Brookings’ vice president and co-director of the Metropolitan Policy Program, which aims to provide decisionmakers in the public, corporate, and civic sectors with policy ideas for improving the health and prosperity of cities and metropolitan areas. Launched in 2012, the Global Cities Initiative will catalyze a shift in economic development priorities and practices resulting in more globally connected metropolitan areas and more sustainable economic growth. Core activities include: INDEPENDENT RESEARCH: Through research, the Global Cities Initiative will make the case that cities and metropolitan areas are the centers of global trade and commerce. Brookings will provide each of the largest 100 U.S. metropolitan areas with baseline data on its current global economic position so that metropolitan leaders can develop and implement more targeted strategies for global engagement and economic development. CATALYTIC CONVENINGS: Each year, the Global Cities Initiative will convene business, civic and government leaders in select U.S. metropolitan areas to help them understand the position of their metropolitan economies in the changing global marketplace and identify opportunities for strengthening competitiveness and expanding trade and investment. In addition, GCI will bring together metropolitan area leaders from the U.S. and around the world in at least one international city to explore best practices and policy innovations for strengthening global engagement, and facilitate trade relationships. GLOBAL ENGAGEMENT STRATEGIES: In order to convert knowledge into concrete action, Brookings and JPMorgan Chase launched the Global Cities Exchange in 2013. Through a competitive application process, economic development practitioners in both U.S. and international cities are selected to receive hands-on guidance on the development and implementation of actionable strategies to enhance global trade and commerce and strengthen regional economies. GLOBAL M ETRO MONITOR 2014 A n Uncertain Recovery 39 Acknowledgments The authors thank colleagues at LSE Cities and Deutsche Bank Research for helping to conceive the first Global MetroMonitor in 2010 and, in particular, for developing the economic performance index methodology. We thank Dmitry Gruzinov, Anthony Light, and their colleagues at Oxford Economics for assembling data on metropolitan areas outside the United States. Alexander Jones, Chenxi Lu, Nicholas Marchio, Lorenz Noe, Elizabeth Patterson, and Jonathan Rothwell provided excellent research assistance and guidance on the analysis. For their comments or advice on drafts of this paper, the authors thank the following individuals: William Antholis, Ryan Donahue, Bruce Katz, Kenneth Lieberthal, Amy Liu, Brad McDearman, Tim Moonen, and Mark Muro. We also thank Brett Franklin and David Jackson for editorial assistance, Alec Friedhoff and Stephen Russ for visual development, and Sese-Paul Design for design and layout. This report is made possible by the David M. Rubenstein President’s Strategic Impact Fund. It is being released as part of the Global Cities Initiative: A Joint Project of Brookings and JPMorgan Chase. The program would also like to thank the John D. and Catherine T. MacArthur Foundation, the Heinz Endowments, the George Gund Foundation, and the F.B. Heron Foundation for providing general support for the program’s research and policy efforts. Finally, we would like to thank the Metropolitan Leadership Council, a network of individual, corporate, and philanthropic investors who provide us financial support and, more importantly, are true intellectual and strategic partners. The Brookings Institution is a private non-profit organization. Its mission is to conduct high quality, independent research and, based on that research, to provide innovative, practical recommendations for policymakers and the public. The conclusions and recommendations of any Brookings publication are solely those of its author(s), and do not reflect the views of the Institution, its management, or its other scholars. Brookings recognizes that the value it provides to any supporter is in its absolute commitment to quality, independence and impact. Activities supported by its donors reflect this commitment and the analysis and recommendations are not determined by any donation. About the Metropolitan Policy For More Information Program at Brookings Created in 1996, the Brookings Institution’s Metropolitan Policy Program provides decision-makers with cutting-edge research and policy ideas for improving the health and prosperity of cities and metropolitan areas including their component cities, suburbs, and rural areas. To learn more visit www.brookings.edu/metro. 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 Research Analyst Metropolitan Policy Program at Brookings jparilla@brookings.edu Alan Berube Senior Fellow and Deputy Director Metropolitan Policy Program at Brookings aberube@brookings.edu 40 t h e b r ookings institution metropolitan policy program Brookings 1775 Massachusetts Avenue, NW Washington D.C. 20036-2188 telephone 202.797.6000 fax 202.797.6004 web site www.brookings.edu telephone 202.797.6139 fax 202.797.2965 web site www.brookings.edu/metro