CONNECTED CITY INNOVATIVE CITY TALENTED CITY YOUR DISTINCTIVE CITY

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1 CITY VITALS 3.0 CONNECTED CITY INNOVATIVE CITY TALENTED CITY YOUR DISTINCTIVE CITY Cleveland State University Maxine Goodman Levin College of Urban Affairs Center for Economic Development

2 TABLE OF CONTENTS 4 INTRODUCTION BY LEE FISHER: ABOUT CEOS FOR CITIES 8 CITY VITALS INDICATORS 10 C.I.T.Y. 12 METROPOLITAN AREAS 15 THE CONNECTED CITY 16 VOTING 18 COMMUNITY INVOLVEMENT 20 ECONOMIC INTEGRATION 22 TRANSIT USE 24 WALKABILITY 26 INTERNATIONAL STUDENTS 28 FOREIGN TRAVEL 30 DATA TRANSFER SPEED 32 BROADBAND ADOPTION RATE 58 WEIRDNESS INDEX 60 CULTURE/INTERNET RATIO 62 RESTAURANT VARIETY 64 INTERNET SEARCH VARIETY 67 CORE VITALITY 68 PER CAPITA INCOME 70 COLLEGE ATTAINMENT 72 POVERTY 75 METROPOLITAN PERFORMANCE 76 POPULATION 78 PER CAPITA INCOME 80 POVERTY 82 VEHICLE MILES TRAVELED 84 GREENHOUSE GASES Prepared by SENIOR RESEARCH ADVISORS FOR CEOS FOR CITIES: ZIONA AUSTRIAN, PH.D. DIRECTOR MERISSA C. PIAZZA, RESEARCH ASSOCIATE NIKKI GLAZER, RESEARCH ASSISTANT MARCUS NOTARO, RESEARCH ASSISTANT CLEVELAND STATE UNIVERSITY MAXINE GOODMAN LEVIN COLLEGE OF URBAN AFFAIRS CENTER FOR ECONOMIC DEVELOPMENT 1717 EUCLID AVE. CLEVELAND, OHIO, Designed by Studio Graphique 35 THE INNOVATIVE CITY 36 PATENTS 38 VENTURE CAPITAL 40 ENTREPRENEURSHIP 42 SMALL BUSINESS 45 THE TALENTED CITY 46 COLLEGE ATTAINMENT 48 CREATIVE PROFESSIONALS 50 YOUNG & RESTLESS 52 TRADED SECTOR TALENT 54 INTERNATIONAL TALENT 57 YOUR DISTINCTIVE CITY 86 APPENDIX 87 CHANGES FROM CITY VITALS VARIABLE NAMES AND SOURCES 89 RANKINGS 113 REFERENCES 115 SELECTED CEOS FOR CITIES RE- SEARCH

3 ABOUT CEOS FOR CITIES At a time when cities and metro regions have become the economic engines of We believe that given the complex, interconnected problems that cities and regions they nurture, retain, and attract talent, and because each invests in its own distinctive CITY DIVIDENDS the nation and when the most valuable currency of the new economy is knowledge face, it is critical to first research, frame, and organize work that puts a focusing lens characteristics and strengths. Economic growth and development is about linking A City Dividend is the return on investment for achieving a targeted, and ideas, cities must be constantly learning, sharing, and reinventing. No city lacks on cities and regions, and helps to see and understand the critical levers for their and leveraging a city s distinctive assets of people, place, and opportunity. measurable, actionable goal toward your city s economic success. City Dividends talent and ideas, but almost every city lacks a vehicle for regularly connecting with talent and ideas outside their own city and a cross-sector vehicle and framework for mobilizing, accelerating, and sustaining action on important goals in their city. The world is moving increasingly fast, resources are increasingly scarce, and challenges are increasingly complex. As a result, the collective impact of leaders from multiple sectors working together to advance city success never has been more essential. None of us is as smart as all of us, and no one sector, discipline, or generation can create sustainable change alone. Sustainable success. We believe that framing is critically important, because, as Wayne Dyer has noted, If you change the way you look at things, the things you look at change (Dyer, W.W., 2009) We believe that the cities that will succeed in the new networked economy are those that: make their boundaries porous to new ideas and talent; demonstrate the humility to understand that there is always something more to learn from other cities; OUR FOUR CORE ELEMENTS Although this report focuses only on City Vitals, our work is best understood as having four core elements: We curate smart ideas and benchmark city success through our City Vitals. We connect cross-sector leaders through our network of City Clusters. We catalyze collaborative change through our City Dividends. We accelerate progress through our Dividend Prize Challenges. are premised on our research and experience that measurable progress, or moving the needle, on targeted work can reap huge economic growth dividends for cities, and accelerate and sustain movement on important goals. This theory of action is based on what Harvard Professor Teresa Amabile calls the progress principle - the single most important motivator and catalyst of positive action is making progress and showing forward momentum in meaningful work. Small but regular wins have a cumulative increase, and can trigger much bigger reactions. (Amabile & Kramer, 2011). change happens when leaders from different sectors come together to share approach their challenges and opportunities with a clear framework; CITY CLUSTERS We have developed four City Dividends the Talent, Green, Opportunity, and a vision for change that includes a common understanding and framework for set measurable, actionable, achievable goals; and A CEOs for Cities City Cluster is a group of cross-sector, cross-generation Health/Diabetes Dividends, and are developing more. Each dividend reflects one addressing the challenges and opportunities facing their city. Too often, each harness collective cross-sector energy to chart a well-informed, leaders who join the CEOs for Cities network together as a team. It is a vehicle small change that leads to a big economic dividend. sector and profession is its own audience, working inside an echo chamber and collaborative, accelerated path to success. for regularly connecting cross-sector leaders and ideas between cities, and The Talent Dividend: A one percentage-point increase in the four-year operating within a narrow frame. CEOs for Cities is a cross-sector city success learning and action network. We connect cross-sector leaders with each other and with the smartest ideas and practices for moving the needle on the four key dimensions of city success Connections, Innovation, Talent, and Your distinctive assets. We are civic CEOs - rather than be self-limited by our name, our inclusive definition of CEO honors urban leadership where it happens, regardless of rank, title, or sector. We re not just Chief Executive Officers. Think Chief Entrepreneurial Officers, Chief Experience Officers, Chief Education Officers, Chief Economic Officers, etc. There is no shortage of theories about the secret sauce for city success. Some experts argue that geography matters more than ever and success depends on physical capital and authentic placemaking. Others submit that in a knowledge economy, cities must build human capital and creative talent. Some insist that social capital and economic opportunity ultimately define the soul of a city. Still others predict that the future city is about smart digital capital and harnessing the power of technology. Each of these theories alone is wrong. A successful city must have all of these elements. Cities succeed because they are well-connected, both internally and to the wider world, because they are fertile places for innovation and entrepreneurship, because focusing and accelerating cross-sector work on issues of high importance to your city. The Cluster model helps cities maximize the impact of ongoing local and regional initiatives and enables faster adoption of innovation and the intentional cross-fertilization of ideas within and between cities. We provide the national platform for City Clusters to connect with each other to share successes, challenges, and lessons learned and the latest cutting-edge ideas and practices for city success through our webinars, newsletter, and website. Participating in our workshops and national meetings as a group significantly enhances the chances that you ll do something with what you learned and explore ways to take some new ideas and customize them to your city. college attainment rate for the population aged 25 and older in the 51 largest U.S. metropolitan areas means, on average, a $974 increase in annual per capita income for the metropolitan area, totaling an increase of $111 billion for the 51 largest metro areas. The Green Dividend: If we can reduce the number of vehicle miles traveled per person per day in the 51 largest U.S. metro areas by one mile, these regions would save $35 billion in fuel and the expense of purchasing and maintaining vehicles. The Opportunity Dividend: A one percentage-point reduction in poverty in the nation s 51 largest metro areas means government savings of $31 4 5

4 billion per year as each additional person in poverty is associated with, on average, over $18,000 in antipoverty expenditures in a metropolitan area. The Health/ Diabetes Dividend: A one percentage point decrease in the diabetic population in the nation s 51 largest metro areas means a savings in medical and other costs, on average, of $1,070 for each person in the metropolitan area, totaling an economic savings of $1.2 billion per year in the largest 51 metro areas. DIVIDEND PRIZE CHALLENGES CEOs for Cities highly successful $1 million Talent Dividend Prize, funded by the Kresge and Lumina Foundations in partnership with Living Cities, helped to catalyze, motivate, and accelerate work on the goal of college completion in 57 American cities competing to achieve the greatest increase in college degree completion over a three-year period. That s why we launched the City Dividend Prize Challenge. We have found that a city dividend, powered by a prize challenge, can be a strong catalyst for convening stakeholders from different sectors around a common agenda and set of metrics for addressing an important challenge. The Prize Challenge provides a powerful incentive to achieve a targeted city dividend and accelerates progress by shining a bright light on the opportunity. CITY VITALS 3.0 City Vitals and City Dividends were first developed by economist Joe Cortright of Impresa, Inc. and my predecessor, Carol Coletta, now VP/Community and National Initiatives for the Knight Foundation. With the expert assistance of our Senior Research Advisors, Dr. Ziona Austrian and Merissa C. Piazza and their team at the Center for Economic Development at Cleveland State University s Maxine Goodman Levin College of Urban Affairs, we have expanded on their groundbreaking work. The four letters that make up the word city spell out the genetic code of urban success: Connections, Innovation, Talent, and Your distinctiveness. Using 30 different indicators, we analyze these four key dimensions to economic success in the 130 largest metropolitan areas of the United States. These are what we call City Vitals. EVERY CITY MUST ASK THESE FOUR CRITICAL QUESTIONS: 1. Connected City: How do we connect our physical, human, social, and digital capital? 2. Innovative City: How do we foster a culture and ecosystem of innovation and entrepreneurship? 3. Talented City: How do we educate, develop, retain, attract, train, employ, and deploy our talent? 4. Your Distinctive City: How do we find our authentic voice? Our DNA? How do we link and leverage our distinctive assets of people, place, and opportunity? We know that there is no one recipe for success, no single path for cities to follow. As CEOs for Cities argued in our research report City Success: Theories of Urban Prosperity, city leaders ought to think about elements of success as an artist would view a color palette. Each city is different and needs a different blend. It s not enough simply to check boxes off a checklist. We understand that data are only a piece of the city success story. There are, as is often the case, limitations to the data. It has become fashionable to rate and rank cities as most livable or best for business or best for some activity or demographic group. High rankings are a source for celebration and marketing. Low rankings tend to be disputed or ignored. It is important to note that we have not made any attempt to add these various measures together to generate some overall ranking. Such combinations, in our opinion, are arbitrary and frequently obscure useful information rather than reveal insights. City Vitals 3.0 is not a collection of best and worst of lists. It is not a set of value judgments. It is certainly not intended to be viewed in a vacuum. Each metropolitan region is different, and can reasonably expect to have different opportunities and challenges than other metropolitan areas. The intent of our research is to provide a set of tools for exploring the performance of your city and metro region. We have compiled data in each of these four key areas of city success to illuminate and better define the discussion of what it takes to build a successful city and metropolitan economy. The future belongs to those cities and regions who can frame their opportunities and challenges, act in ways that demonstrate measurable progress, and connect and collaborate with the smartest people and the smartest ideas in the most places and in the most ways. City Vitals is an important component of our mission to, in the words of Steve Jobs, tear down walls, build bridges, and light fires (Jobs, 2011). Lee Fisher President and CEO CEOs for Cities Lfisher@ceosforcities.org 6 7

5 THE CITY VITALS INDICATORS The Connected City The Innovative City The Talented City Your Distinctive City Core Vitality Metropolitan Performance As Edward Glaeser notes in Triumph of the City Innovation and generation of new ideas play As Ed Glaeser notes in Trumph of the City, all The unique characteristics of place may be the only The success of a regional economy heavily depends CEOs for Cities works with cross-sector urban leaders our ability to connect with each other is the defining an important role in regional economic growth and great cities have something in common (they) attract truly defensible source of regional competitive advantage. on the vitality of its urban core or central city. Vibrant and policy makers to benchmark and accelerate their city s characteristic of our species. We know that cities thrive prosperity. Many factors, including but not limited to the smart people and help them to work collaboratively. While globalization has allowed regions to connect more metropolitan areas have strong centers that are hubs of and region s economic performance. In order to measure as places where people can live, work, play, and connect. Jane Jacobs, in The Death and Life of Great American Cities, likened the art form of a city to an intricate ballet in which the individual dancers and ensembles all have distinctive parts which miraculously reinforce each other and compose an orderly whole. It is through these connections that regions prosper. Internal connections among residents and firms, and external connections with the global economy are essential for a city s prosperity and vitality. There are numerous ways cities connect, from physical connections (roads, airports, railroad), to virtual connections, to interpersonal connections. We measure the Connected City by examining voter participation, community involvement, economic integration, transit use, walkability, foreign students, foreign travel, and internet connectivity. aggregation of talent, clusters of innovative firms, key research institutions, and a business and social culture amenable to change and risk-taking, have been found to be correlated with a city/region s potential for generating new ideas. Regional competitiveness is based on the fact that generating new ideas is not evenly distributed across space. Invisible and weightless, ideas cannot be measured directly, but the footprints they leave in the economic landscape can be traced by measuring the number of patents, the amount of venture capital, the number of the self-employed, and the number of small businesses. The indispensable asset in a knowledge-based economy is human capital especially a region s ability to grow, retain, and attract a well-educated, skilled workforce. The Great Recession has underscored the importance of talent to economic success. Bettereducated metropolitan areas saw smaller increases in unemployment in the depths of the recession, and most of the job growth in the recovery has been among bettereducated workers. The relationship between higher education and income also holds for cities. Many cities with a more-educated workforce have higher personal income while a lower personal income is often correlated with a less-educated workforce. We measure the Talented City by analyzing college attainment, abundance of creative professionals, percentage of the population that is young and well-educated (young and the restless), size of the private sector workforce, and international talent. frequently and efficiently with faraway places, regions understand that it is important to be unique, distinctive, and authentic while maintaining a global presence. Regions that create their own distinctively authentic cities and identities create a sense of place and a brand that can transcend their own advocacy efforts. As Dolly Parton notes, Find out who you are and do it on purpose (Parton, n.d.). There are many dimensions to distinctiveness and each city has its own set of unique characteristics, so it may be difficult to compare adequately metropolitan areas and cities on distinctiveness. We measure the Distinctive City using four indicators: the weirdness index, culture, internet search variety, and ethnic restaurant options. economic, social, cultural, and recreational activities. Strong cities attract talent, foster creativity and innovation, and appeal to business startups. Conversely, metropolitan areas with weak central cities have lower economic performance. An assessment of the vitality of the urban core is conducted by analyzing a series of measurements illustrating the performance of the core. Here, we define the urban core as the central city as defined by the U.S. Census Bureau Principal City. We use three performance indicators to measure Core Vitality: income, college attainment, and poverty. metropolitan performance, we present five measures that reflect the four dimensions of success outlined in City Vitals; these dimensions are connections, innovations, talent, and your distinctiveness. The five performance measures included in Metropolitan Performance are population, per capita income, poverty rates, vehicle miles traveled, and greenhouse gas emissions. 8 9

6 C.I.T.Y. CEOs for Cities has identified four essential characteristics that underlie economic prosperity. In a sense, the four letters that make up the word city spell out the genetic code of city and regional economic success: Connections, Innovation, Talent, and Your Distinctiveness. City Vitals 3.0 contains 30 variables for the 130 largest metropolitan areas in the United States that define the four areas of a city s performance connections, innovation, talent, and your distinctiveness. Our analysis recognizes that there are limitations to the data and that there is no one recipe for success, so we purposely avoid any overall ranking from best to worst. As Albert Einstein said Not everything that can be counted counts, and not everything that counts can be counted (as quoted in Kaufmann, 2003: 5). However, these data do provide a means for cities and regions to assess certain relative strengths and weaknesses against their peers nationally. City Vitals 3.0 is a benchmarking tool for practitioners, policy makers, city leadership, and engaged citizens to monitor the economic performance of their city and region and engage in intelligent benchmarking - comparing oneself to others to provide support for investment and policy decisions (Malecki, 2007). More and more metropolitan areas are becoming the change makers for economic and social change in the United States. With more people living in cities and metro regions than ever before, municipal governments have unique leverage to change positively their regions and citizens lives. In their book, Metropolitan Revolution, Bruce Katz and Jennifer Bradley note that with the U.S. government entrenched in disagreement and dysfunction, regions are at the forefront of innovation and connectivity with each other and the globe. They go on to emphasize that metropolitan areas can be economic players, innovate locally, network globally, and advocate nationally. City Vitals 3.0 honors and highlights the performance and importance of our nation s metropolitan regions and their cities through their connections, innovations, talent, and distinctiveness. By ascertaining what is important to your community and evaluating it through metrics, regions can move the needle and create a better, more prosperous region however defined. Variables are computed at the city or metropolitan level, where available. These 130 metropolitan areas are regions that have a population greater than 400,000. For more information on the methodology and how City Vitals 3.0 differs from City Vitals 2.0, see the Appendix

7 Akron, OH Harrisburg-Carlisle, PA Portland-South Portland-Biddeford, ME Albany-Schenectady-Troy, NY Hartford-West Hartford-East Hartford, CT Portland-Vancouver-Hillsboro, OR-WA Albuquerque, NM Honolulu, HI Poughkeepsie-Newburgh-Middletown, NY Allentown-Bethlehem-Easton, PA-NJ Houston-Sugar Land-Baytown, TX Providence-New Bedford-Fall River, RI-MA Asheville, NC Huntsville, AL Provo-Orem, UT Atlanta-Sandy Springs-Marietta, GA Indianapolis-Carmel, IN Raleigh-Cary, NC Augusta-Richmond County, GA-SC Jackson, MS Reading, PA Austin-Round Rock-San Marcos, TX Jacksonville, FL Reno-Sparks, NV Bakersfield-Delano, CA Kansas City, MO-KS Richmond, VA Baltimore-Towson, MD Killeen-Temple-Fort Hood, TX Riverside-San Bernardino-Ontario, CA Baton Rouge, LA Knoxville, TN Rochester, NY Birmingham-Hoover, AL Lakeland-Winter Haven, FL Sacramento-Arden-Arcade-Roseville, CA Boise City-Nampa, ID Lancaster, PA Salinas, CA Boston-Cambridge-Quincy, MA-NH Lansing-East Lansing, MI Salt Lake City, UT Bridgeport-Stamford-Norwalk, CT Las Vegas-Paradise, NV San Antonio-New Braunfels, TX Brownsville-Harlingen, TX Lexington-Fayette, KY San Diego-Carlsbad-San Marcos, CA Buffalo-Niagara Falls, NY Little Rock-North Little Rock-Conway, AR San Francisco-Oakland-Fremont, CA Canton-Massillon, OH Los Angeles-Long Beach-Santa Ana, CA San Jose-Sunnyvale-Santa Clara, CA Cape Coral-Fort Myers, FL Louisville/Jefferson County, KY-IN Santa Barbara-Santa Maria-Goleta, CA Charleston-North Charleston-Summerville, SC Madison, WI Santa Rosa-Petaluma, CA Charlotte-Gastonia-Rock Hill, NC-SC Manchester-Nashua, NH Scranton-Wilkes-Barre, PA Chattanooga, TN-GA McAllen-Edinburg-Mission, TX Seattle-Tacoma-Bellevue, WA Chicago-Joliet-Naperville, IL-IN-WI Memphis, TN-MS-AR Shreveport-Bossier City, LA Cincinnati-Middletown, OH-KY-IN Miami-Fort Lauderdale-Pompano Beach, FL Spokane, WA Cleveland-Elyria-Mentor, OH Milwaukee-Waukesha-West Allis, WI Springfield, MA Colorado Springs, CO Minneapolis-St. Paul-Bloomington, MN-WI Springfield, MO Columbia, SC Mobile, AL St. Louis, MO-IL Columbus, OH Modesto, CA Stockton, CA Corpus Christi, TX Nashville-Davidson-Murfreesboro-Franklin, TN Syracuse, NY Dallas-Fort Worth-Arlington, TX New Haven-Milford, CT Tampa-St. Petersburg-Clearwater, FL Dayton, OH New Orleans-Metairie-Kenner, LA Toledo, OH Deltona-Daytona Beach-Ormond Beach, FL New York-N. New Jersey-Long Island, NY-NJ-PA Tucson, AZ 500, ,000 Denver-Aurora-Broomfield, CO North Port-Bradenton-Sarasota, FL Tulsa, OK Des Moines-West Des Moines, IA Ogden-Clearfield, UT Vallejo-Fairfield, CA 675, ,000 Detroit-Warren-Livonia, MI Oklahoma City, OK Virginia Beach-Norfolk-Newport News, VA-NC Durham-Chapel Hill, NC Omaha-Council Bluffs, NE-IA Visalia-Porterville, CA 2,100,000 El Paso, TX Orlando-Kissimmee-Sanford, FL Washington-Arlington-Alexandria, DC-VA-MD-WV Fayetteville-Springdale-Rogers, AR-MO Oxnard-Thousand Oaks-Ventura, CA Wichita, KS Flint, MI Palm Bay-Melbourne-Titusville, FL Winston-Salem, NC Fort Wayne, IN Pensacola-Ferry Pass-Brent, FL Worcester, MA Fresno, CA Philadelphia-Camden-Wilmington, PA-NJ-DE-MD York-Hanover, PA Grand Rapids-Wyoming, MI Phoenix-Mesa-Glendale, AZ Youngstown-Warren-Boardman, OH-PA Greensboro-High Point, NC Pittsburgh, PA Greenville-Mauldin-Easley, SC Port St. Lucie, FL LARGEST 130 METROPOLITAN AREAS POPULATION 400, , , ,

8 The Connected City Increasingly cities are becoming more important in the globalized world and individuals are clustering in cities to increase connectivity (via air travel and technology) (Glaeser, 2011). Earlier studies also support this assertion. Jane Jacobs famously argued decades ago that city economies work best when they do a good job of connecting people to one another (Jacobs, 1969). Nobel Laureate economist Robert Lucas echoed this observation: What can people be paying Manhattan or downtown Chicago rents for, if not being near other people? (Lucas, 1988). The fundamental purpose of cities is to connect people. Now, perhaps more than ever, city connectivity is important to its success. In cities, these connections are both internal and external; cities have to connect their residents to one another and also connect the city as a whole to the rest of the world. There are numerous ways cities connect, from physical connections (roads, airports, railroad), to virtual connections, to interpersonal connections. As economist Harold Bathelt and his colleagues observed in a slightly different context, local success in the global economy is a function of local buzz and global pipelines. That is to say, urban areas have to have their own strong localized interactions and knowledge to function well locally, but they must also have easy and extensive connections to other places with buzz around the world (Bathelt, Malmberg, & Maskell, 2002). We define these connections broadly, from the far-reaching global to the intensely local. Accordingly, we measure key international connections, especially among people, by examining the number of persons traveling outside the U.S. in each metropolitan area, as well as the number of foreign students each metropolitan area hosts. We also look at internet connectivity by way of data transfer speed and broadband adoption. At the other end of the spectrum, we consider more local connections like voting and volunteering, both indicators of how connected people are in their role as citizens. Local connectivity is also measured by the way in which people navigate cities through transit use and walkability. We also examine economic integration the extent to which people in different income strata live near one another in the metropolitan area

9 VOTING Number of votes cast in the November 2012 presidential election divided by the voting age population of the metropolitan area, 2012 We measure voting as the number of ballots cast in the November 2012 There is a large range in voter participation within the cohort of 130 metro areas. presidential election, divided by the total voting age population of the metro Winston-Salem, NC has the highest percentage of voter participation with 81.9% of area (Leip, 2012). It should be noted that census data counts all persons living its adult population voting in the 2012 presidential election. Grand Rapids, MI is close in the U.S., regardless of citizenship status; therefore, the population number behind with 81.7%. The average voter participation rate for the 130 metro regions is includes many people over the age of 18 who are not eligible to vote. As a result, 54.0% and the median for the cohort is 56.2%. Both measures show that the number we are not measuring voter turnout, but the percent of the adult population which of votes cast was more than half the voting age population. Lower levels of voting participates in governance. participation indicate high numbers of non-citizens living in these regions. 1 Winston-Salem, NC 81.9% 2 Grand Rapids-Wyoming, MI 81.7% 3 Madison, WI 79.9% 4 Charlotte-Gastonia-Rock Hill, NC-SC 76.3% 5 Minneapolis-St. Paul-Bloomington, MN-WI 75.4% 6 Milwaukee-Waukesha-West Allis, WI 73.3% 7 Portland-South Portland-Biddeford, ME 70.9% 8 Des Moines-West Des Moines, IA 70.5% 9 Deltona-Daytona Beach-Ormond Beach, FL 70.3% 10 Spokane, WA 68.8% 11 Durham-Chapel Hill, NC 68.0% 12 Raleigh-Cary, NC 67.0% 13 Greenville-Mauldin-Easley, SC 66.9% 14 Worcester, MA 66.7% 15 Manchester-Nashua, NH 65.8% 16 Columbus, OH 65.8% 17 Cleveland-Elyria-Mentor, OH 65.4% 18 Denver-Aurora-Broomfield, CO 65.4% 19 Palm Bay-Melbourne-Titusville, FL 64.5% 20 Flint, MI 64.0% 21 Richmond, VA 63.9% 22 Jacksonville, FL 63.8% 23 Detroit-Warren-Livonia, MI 63.5% 24 Jackson, MS 63.2% 25 Cincinnati-Middletown, OH-KY-IN 63.2% 26 Greensboro-High Point, NC 63.0% 27 Asheville, NC 62.9% 28 Shreveport-Bossier City, LA 62.8% 29 St. Louis, MO-IL 62.7% 30 Akron, OH 62.4% 31 Pensacola-Ferry Pass-Brent, FL 62.3% 32 Youngstown-Warren-Boardman, OH-PA 62.2% 33 Canton-Massillon, OH 62.1% 34 Boston-Cambridge-Quincy, MA-NH 61.6% 35 Philadelphia-Camden-Wilmington, PA-NJ-DE-MD 61.6% 36 Dayton, OH 61.4% 37 Washington-Arlington-Alexandria, DC-VA-MD-WV 61.0% 38 North Port-Bradenton-Sarasota, FL 60.8% 39 Colorado Springs, CO 60.7% 40 Lansing-East Lansing, MI 60.6% 41 Baltimore-Towson, MD 60.5% 42 Kansas City, MO-KS 60.4% 43 Indianapolis-Carmel, IN 60.0% 44 Portland-Vancouver-Hillsboro, OR-WA 59.9% 45 Virginia Beach-Norfolk-Newport News, VA-NC 59.8% 46 Pittsburgh, PA 59.8% 47 Baton Rouge, LA 59.5% 48 Seattle-Tacoma-Bellevue, WA 59.4% 49 Birmingham-Hoover, AL 58.9% 50 Omaha-Council Bluffs, NE-IA 58.8% 51 Toledo, OH 58.8% 52 Knoxville, TN 58.5% 53 Harrisburg-Carlisle, PA 58.5% 54 Port St. Lucie, FL 58.3% 55 Springfield, MO 58.3% 56 Ogden-Clearfield, UT 57.8% 57 Huntsville, AL 57.8% 58 Tampa-St. Petersburg-Clearwater, FL 57.5% 59 Hartford-West Hartford-East Hartford, CT 57.3% 60 New Orleans-Metairie-Kenner, LA 57.1% 61 Reno-Sparks, NV 56.9% 62 Rochester, NY 56.7% 63 Augusta-Richmond County, GA-SC 56.6% 64 Boise City-Nampa, ID 56.3% 65 Fort Wayne, IN 56.2% MEDIAN = 56.2% 66 Buffalo-Niagara Falls, NY 56.1% 67 Mobile, AL 56.1% 68 Louisville/Jefferson County, KY-IN 56.0% 69 York-Hanover, PA 56.0% 70 Santa Rosa-Petaluma, CA 56.0% 71 Bridgeport-Stamford-Norwalk, CT 55.9% 72 Albany-Schenectady-Troy, NY 55.8% 73 Lancaster, PA 55.8% 74 Atlanta-Sandy Springs-Marietta, GA 55.5% 75 Orlando-Kissimmee-Sanford, FL 54.4% 76 Columbia, SC 54.3% 77 Providence-New Bedford-Fall River, RI-MA 54.3% 78 Nashville-Davidson-Murfreesboro-Franklin, TN 54.2% 79 Memphis, TN-MS-AR 54.2% 80 Allentown-Bethlehem-Easton, PA-NJ 54.0% AVERAGE = 54.0% 81 Syracuse, NY 53.9% 82 Lexington-Fayette, KY 53.8% 83 Reading, PA 53.7% 84 New Haven-Milford, CT 53.4% 85 Charleston-North Charleston-Summerville, SC 53.3% 86 Chicago-Joliet-Naperville, IL-IN-WI 52.5% 87 Lakeland-Winter Haven, FL 52.4% 88 Albuquerque, NM 52.4% 89 Little Rock-North Little Rock-Conway, AR 52.1% 90 Oxnard-Thousand Oaks-Ventura, CA 52.1% 91 Scranton-Wilkes-Barre, PA 51.9% 92 Poughkeepsie-Newburgh-Middletown, NY 51.8% 93 San Francisco-Oakland-Fremont, CA 51.5% 94 Springfield, MA 51.2% 95 Sacramento-Arden-Arcade-Roseville, CA 51.1% 96 Wichita, KS 51.1% 97 Cape Coral-Fort Myers, FL 51.0% 98 Provo-Orem, UT 50.6% 99 Tulsa, OK 50.1% 100 Tucson, AZ 49.8% 101 Chattanooga, TN-GA 49.5% 102 Miami-Fort Lauderdale-Pompano Beach, FL 49.1% 103 Santa Barbara-Santa Maria-Goleta, CA 49.0% 104 Salt Lake City, UT 48.7% 105 San Diego-Carlsbad-San Marcos, CA 48.6% 106 New York-N. New Jersey-Long Island, NY-NJ-PA 47.6% 107 Vallejo-Fairfield, CA 47.4% 108 Oklahoma City, OK 47.3% 109 Austin-Round Rock-San Marcos, TX 46.8% 110 Fayetteville-Springdale-Rogers, AR-MO 46.5% 111 Phoenix-Mesa-Glendale, AZ 46.3% 112 San Jose-Sunnyvale-Santa Clara, CA 45.8% 113 Las Vegas-Paradise, NV 45.8% 114 Dallas-Fort Worth-Arlington, TX 44.8% 115 Los Angeles-Long Beach-Santa Ana, CA 43.2% 116 San Antonio-New Braunfels, TX 41.7% 117 Houston-Sugar Land-Baytown, TX 41.4% 118 Modesto, CA 41.3% 119 Stockton, CA 40.9% 120 Riverside-San Bernardino-Ontario, CA 39.6% 121 Salinas, CA 39.5% 122 Honolulu, HI 38.7% 123 Fresno, CA 38.6% 124 Corpus Christi, TX 38.4% 125 Bakersfield-Delano, CA 36.9% 126 Killeen-Temple-Fort Hood, TX 36.0% 127 Visalia-Porterville, CA 33.0% 128 El Paso, TX 29.6% 129 Brownsville-Harlingen, TX 27.3% 130 McAllen-Edinburg-Mission, TX 26.2% 16 17

10 COMMUNITY INVOLVEMENT Percentage of the metropolitan area population that reported volunteering for a community activity in the past year, 2012 Personal connections are essential to a successful metropolitan region because The highest amount of volunteerism can be found in Utah, with areas such the more individuals care about one another and their community, the less crime as Ogden, Provo, and Salt Lake City having a volunteer rate of 42%. Overall, only and vandalism occur. Volunteerism and personal engagement in non-profit and slightly more than one quarter of the population in the cohort of 105 metro areas is community-oriented endeavors has traditionally been a point of pride for Americans. involved in volunteerism. The average volunteer rate for the cohort of 105 is 27% and The degree to which people freely give their time and energy to advance community the median percentage is 27%. interests is a good indicator of community involvement and social capital. Community involvement has economic and social benefits. Communities that promote easy interaction among community members facilitate economic interaction. Survey data from Scarborough Research asks adult residents if they conducted volunteer work in the past 12 months (Scarborough Research, 2012). This data is available for only 105 of the 130 metro regions of our cohort. The data is assembled by Designated Market Area (DMA), which is commonly used for marketing or advertising research and has a larger geographic footprint than a metro area. When multiple metropolitan areas are included in the same DMA, we assigned the value of community involvement of the DMA to each of these metro areas. 1 Ogden-Clearfield, UT 42% 1 Provo-Orem, UT 42% 1 Salt Lake City, UT 42% 4 Des Moines-West Des Moines, IA 34% 4 Minneapolis-St. Paul-Bloomington, MN-WI 34% 4 Portland-South Portland-Biddeford, ME 34% 4 Portland-Vancouver-Hillsboro, OR-WA 34% 8 Grand Rapids-Wyoming, MI 33% 8 San Francisco-Oakland-Fremont, CA 33% 8 San Jose-Sunnyvale-Santa Clara, CA 33% 8 Santa Rosa-Petaluma, CA 33% 8 Seattle-Tacoma-Bellevue, WA 33% 8 Vallejo-Fairfield, CA 33% 14 Austin-Round Rock-San Marcos, TX 31% 14 Cincinnati-Middletown, OH-KY-IN 31% 14 Kansas City, MO-KS 31% 14 Spokane, WA 31% 18 Atlanta-Sandy Springs-Marietta, GA 30% 18 Columbus, OH 30% 18 Deltona-Daytona Beach-Ormond Beach, FL 30% 18 Durham-Chapel Hill, NC 30% 18 Lakeland-Winter Haven, FL 30% 18 Milwaukee-Waukesha-West Allis, WI 30% 18 Orlando-Kissimmee-Sanford, FL 30% 18 Palm Bay-Melbourne-Titusville, FL 30% 18 Raleigh-Cary, NC 30% 18 Washington-Arlington-Alexandria, DC-VA-MD-WV 30% 28 Baltimore-Towson, MD 29% 28 Charlotte-Gastonia-Rock Hill, NC-SC 29% 28 Honolulu, HI 29% 28 Indianapolis-Carmel, IN 29% 28 Richmond, VA 29% 28 St. Louis, MO-IL 29% 28 Tucson, AZ 29% 35 Allentown-Bethlehem-Easton, PA-NJ 28% 35 Asheville, NC 28% 35 Buffalo-Niagara Falls, NY 28% 35 Chattanooga, TN-GA 28% 35 Colorado Springs, CO 28% 35 Denver-Aurora-Broomfield, CO 28% 35 Flint, MI 28% 35 Greenville-Mauldin-Easley, SC 28% 35 Harrisburg-Carlisle, PA 28% 35 Lancaster, PA 28% 35 Lexington-Fayette, KY 28% 35 Philadelphia-Camden-Wilmington, PA-NJ-DE-MD 28% 35 Pittsburgh, PA 28% 35 Reading, PA 28% 35 Rochester, NY 28% 35 San Antonio-New Braunfels, TX 28% 35 Syracuse, NY 28% 35 York-Hanover, PA 28% 53 Akron, OH 27% 53 Boston-Cambridge-Quincy, MA-NH 27% 53 Canton-Massillon, OH 27% 53 Cleveland-Elyria-Mentor, OH 27% 53 Dallas-Fort Worth-Arlington, TX 27% 53 Detroit-Warren-Livonia, MI 27% 53 Manchester-Nashua, NH 27% 53 Toledo, OH 27% 53 Tulsa, OK 27% 53 Virginia Beach-Norfolk-Newport News, VA-NC 27% 53 Worcester, MA 27% MEDIAN & AVERAGE = 27% 64 Birmingham-Hoover, AL 26% 64 Bridgeport-Stamford-Norwalk, CT 26% 64 Greensboro-High Point, NC 26% 64 Hartford-West Hartford-East Hartford, CT 26% 64 Memphis, TN-MS-AR 26% 64 Modesto, CA 26% 64 New Haven-Milford, CT 26% 64 Oklahoma City, OK 26% 64 Sacramento-Arden-Arcade-Roseville, CA 26% 64 Stockton, CA 26% 64 Winston-Salem, NC 26% 75 Knoxville, TN 25% 75 Little Rock-North Little Rock-Conway, AR 25% 75 Louisville/Jefferson County, KY-IN 25% 75 Nashville-Davidson-Murfreesboro-Franklin, TN 25% 75 San Diego-Carlsbad-San Marcos, CA 25% 80 Albuquerque, NM 24% 80 Chicago-Joliet-Naperville, IL-IN-WI 24% 80 Jacksonville, FL 24% 80 Mobile, AL 24% 80 North Port-Bradenton-Sarasota, FL 24% 80 Pensacola-Ferry Pass-Brent, FL 24% 80 Tampa-St. Petersburg-Clearwater, FL 24% 87 Fresno, CA 23% 87 Houston-Sugar Land-Baytown, TX 23% 87 Los Angeles-Long Beach-Santa Ana, CA 23% 87 New York-N. New Jersey-Long Island, NY-NJ-PA 23% 87 Oxnard-Thousand Oaks-Ventura, CA 23% 87 Phoenix-Mesa-Glendale, AZ 23% 87 Poughkeepsie-Newburgh-Middletown, NY 23% 87 Riverside-San Bernardino-Ontario, CA 23% 87 Visalia-Porterville, CA 23% 96 Cape Coral-Fort Myers, FL 22% 96 Las Vegas-Paradise, NV 22% 96 New Orleans-Metairie-Kenner, LA 22% 99 Bakersfield-Delano, CA 21% 99 El Paso, TX 21% 101 Brownsville-Harlingen, TX 20% 101 McAllen-Edinburg-Mission, TX 20% 101 Miami-Fort Lauderdale-Pompano Beach, FL 20% 101 Port St. Lucie, FL 20% 101 Providence-New Bedford-Fall River, RI-MA 20% - Albany-Schenectady-Troy, NY N/A - Augusta-Richmond County, GA-SC N/A - Baton Rouge, LA N/A - Boise City-Nampa, ID N/A - Charleston-North Charleston-Summerville, SC N/A - Columbia, SC N/A - Corpus Christi, TX N/A - Dayton, OH N/A - Fayetteville-Springdale-Rogers, AR-MO N/A - Fort Wayne, IN N/A - Huntsville, AL N/A - Jackson, MS N/A - Killeen-Temple-Fort Hood, TX N/A - Lansing-East Lansing, MI N/A - Madison, WI N/A - Omaha-Council Bluffs, NE-IA N/A - Reno-Sparks, NV N/A - Salinas, CA N/A - Santa Barbara-Santa Maria-Goleta, CA N/A - Scranton-Wilkes-Barre, PA N/A - Shreveport-Bossier City, LA N/A - Springfield, MA N/A - Springfield, MO N/A - Wichita, KS N/A - Youngstown-Warren-Boardman, OH-PA N/A 18 19

11 ECONOMIC INTEGRATION Percentage of the population living in middle income neighborhoods (median family income was between 67% and 150% of the metropolitan median family income), Since the 1970s, metro areas in the U.S. have seen increased residential segregation by income (Watson, 2009). This may be explained by a widening income distribution, which makes it less likely for families with different incomes to live near each other. In addition, black and Hispanic households, on average, live in neighborhoods with more than one-and-a-half times the poverty rate of white households (Logan, 2011). A key aspect of the connected city is the extent to which our neighbors and acquaintances represent the diversity of our population. However, the physical layout of many American cities effectively separates different income groups into entirely different neighborhoods. As a number of studies have shown, economic isolation exacerbates the problems associated with poverty. Neighborhoods with concentrated poverty make it harder to find positive role models and connect to To measure economic integration, we use an index that calculates the fraction of a region s population living in middle-income neighborhoods where the family income is between 67% and 150% of the median family income for the entire metro area (Reardon & Bischoff, 2011). Lancaster, PA has the highest percent of population (91.0%) living in neighborhoods where the median family income was between 67% and 150% of the metropolitan area median income. Portland, ME and York, PA also have at least 90% economic integration within their metro areas neighborhoods. Nine metro areas have less than 60% of the population living in middle income neighborhoods, with Fresno, CA ranked last, at 49.4% integration. The median economic integration for the 130 metropolitan areas was 72.2%. Due to the construction of this data, we are unable to calculate an average economic integration rate. social networks that enable employment, and they intensify problems of crime and drug abuse (Jargowsky, 2003). Like racial segregation, segregation by income has harmful effects on low-income individuals, including worse economic outcomes for adults, higher school dropout and teenage pregnancy rates, and worse academic achievement for schoolchildren. Research shows that impoverished individuals who live in mixed-income areas do better than their counterparts living in areas of concentrated poverty (Jargowsky & Swanstrom, 2009). Well-connected metropolitan areas have less division among economic groups. 1 Lancaster, PA 91.0% 2 Portland-South Portland-Biddeford, ME 90.7% 3 York-Hanover, PA 90.0% 4 Madison, WI 89.1% 5 Asheville, NC 88.4% 6 Deltona-Daytona Beach-Ormond Beach, FL 88.4% 7 Scranton-Wilkes-Barre, PA 85.8% 8 Santa Rosa-Petaluma, CA 85.4% 9 Palm Bay-Melbourne-Titusville, FL 85.2% 10 Fayetteville-Springdale-Rogers, AR-MO 84.1% 11 Ogden-Clearfield, UT 84.0% 12 Albany-Schenectady-Troy, NY 83.2% 13 Honolulu, HI 82.4% 14 Harrisburg-Carlisle, PA 82.3% 15 Pensacola-Ferry Pass-Brent, FL 82.1% 16 Springfield, MO 81.9% 17 Killeen-Temple-Fort Hood, TX 81.5% 18 Chattanooga, TN-GA 81.1% 19 Poughkeepsie-Newburgh-Middletown, NY 81.1% 20 Grand Rapids-Wyoming, MI 80.8% 21 Minneapolis-St. Paul-Bloomington, MN-WI 80.6% 22 Allentown-Bethlehem-Easton, PA-NJ 80.1% 23 Lakeland-Winter Haven, FL 80.0% 24 Youngstown-Warren-Boardman, OH-PA 80.0% 25 Provo-Orem, UT 79.5% 26 Worcester, MA 79.1% 27 Portland-Vancouver-Hillsboro, OR-WA 78.6% 28 Port St. Lucie, FL 78.6% 29 Lansing-East Lansing, MI 78.4% 30 Reading, PA 77.8% 31 Spokane, WA 76.9% 32 Greenville-Mauldin-Easley, SC 76.7% 33 Fort Wayne, IN 76.7% 34 Pittsburgh, PA 76.6% 35 Baton Rouge, LA 76.4% 36 Rochester, NY 76.4% 37 Canton-Massillon, OH 76.3% 38 Salt Lake City, UT 76.0% 39 Virginia Beach-Norfolk-Newport News, VA-NC 75.9% 40 Boise City-Nampa, ID 75.8% 41 Cape Coral-Fort Myers, FL 75.8% 42 Syracuse, NY 75.7% 43 Omaha-Council Bluffs, NE-IA 75.6% 44 North Port-Bradenton-Sarasota, FL 75.4% 45 Des Moines-West Des Moines, IA 75.3% 46 Vallejo-Fairfield, CA 75.1% 47 Brownsville-Harlingen, TX 74.8% 48 Winston-Salem, NC 74.8% 49 Modesto, CA 74.7% 50 Manchester-Nashua, NH 74.6% 51 Orlando-Kissimmee-Sanford, FL 74.1% 52 Las Vegas-Paradise, NV 74.0% 53 McAllen-Edinburg-Mission, TX 74.0% 54 Cincinnati-Middletown, OH-KY-IN 73.8% 55 Buffalo-Niagara Falls, NY 73.5% 56 Hartford-West Hartford-East Hartford, CT 73.4% 57 Little Rock-North Little Rock-Conway, AR 73.4% 58 Huntsville, AL 73.4% 59 Dayton, OH 73.3% 60 Jacksonville, FL 73.2% 61 Seattle-Tacoma-Bellevue, WA 73.2% 62 Oxnard-Thousand Oaks-Ventura, CA 72.9% 63 Tampa-St. Petersburg-Clearwater, FL 72.5% 64 Louisville/Jefferson County, KY-IN 72.4% 65 St. Louis, MO-IL 72.4% MEDIAN = 72.2% 66 Columbia, SC 72.1% 67 Mobile, AL 71.8% 68 Knoxville, TN 71.5% 69 Tulsa, OK 71.5% 70 Flint, MI 71.4% 71 Toledo, OH 71.1% 72 Augusta-Richmond County, GA-SC 71.0% 73 Charleston-North Charleston-Summerville, SC 70.7% 74 Richmond, VA 70.5% 75 Providence-New Bedford-Fall River, RI-MA 70.3% 76 Boston-Cambridge-Quincy, MA-NH 70.3% 77 Kansas City, MO-KS 70.2% 78 Akron, OH 70.1% 79 Greensboro-High Point, NC 69.9% 80 Wichita, KS 69.8% 81 Springfield, MA 69.4% 82 Salinas, CA 69.3% 83 Albuquerque, NM 69.3% 84 Raleigh-Cary, NC 68.7% 85 Oklahoma City, OK 68.4% 86 Indianapolis-Carmel, IN 68.0% 87 Shreveport-Bossier City, LA 67.7% 88 Nashville-Davidson-Murfreesboro-Franklin, TN 67.6% 89 Visalia-Porterville, CA 67.3% 90 Colorado Springs, CO 67.3% 91 Baltimore-Towson, MD 67.1% 92 Milwaukee-Waukesha-West Allis, WI 67.0% 93 Birmingham-Hoover, AL 66.8% 94 Stockton, CA 66.7% 95 Jackson, MS 66.4% 96 El Paso, TX 66.3% 97 San Jose-Sunnyvale-Santa Clara, CA 66.3% 98 Atlanta-Sandy Springs-Marietta, GA 66.2% 99 Lexington-Fayette, KY 66.2% 100 Washington-Arlington-Alexandria, DC-VA-MD-WV 66.0% 101 Sacramento-Arden-Arcade-Roseville, CA 65.7% 102 Columbus, OH 65.2% 103 New Haven-Milford, CT 65.1% 104 Chicago-Joliet-Naperville, IL-IN-WI 65.0% 105 San Diego-Carlsbad-San Marcos, CA 64.9% 106 Cleveland-Elyria-Mentor, OH 64.9% 107 Santa Barbara-Santa Maria-Goleta, CA 64.6% 108 Corpus Christi, TX 64.5% 109 Philadelphia-Camden-Wilmington, PA-NJ-DE-MD 64.4% 110 Phoenix-Mesa-Glendale, AZ 64.4% 111 Charlotte-Gastonia-Rock Hill, NC-SC 64.1% 112 Riverside-San Bernardino-Ontario, CA 63.9% 113 Denver-Aurora-Broomfield, CO 63.1% 114 Reno-Sparks, NV 62.8% 115 Detroit-Warren-Livonia, MI 62.7% 116 New Orleans-Metairie-Kenner, LA 62.5% 117 San Francisco-Oakland-Fremont, CA 62.1% 118 Austin-Round Rock-San Marcos, TX 60.8% 119 Tucson, AZ 60.6% 120 Durham-Chapel Hill, NC 60.1% 121 San Antonio-New Braunfels, TX 60.0% 122 Miami-Fort Lauderdale-Pompano Beach, FL 58.5% 123 Bakersfield-Delano, CA 58.3% 124 Dallas-Fort Worth-Arlington, TX 58.2% 125 Bridgeport-Stamford-Norwalk, CT 57.7% 126 Houston-Sugar Land-Baytown, TX 53.5% 127 Memphis, TN-MS-AR 53.2% 128 New York-N. New Jersey-Long Island, NY-NJ-PA 52.9% 129 Los Angeles-Long Beach-Santa Ana, CA 52.6% 130 Fresno, CA 49.4% 20 21

12 TRANSIT USE Percentage of non-poor workers that commute via public transportation, Public transportation gives people options of travel, aids in mobility of the Not surprisingly, New York, NY has the highest public transit use among nonpoor, at 31.5%. The major metropolitan areas of San Francisco, CA, Washington, poor and elderly, and encourages personal interaction with strangers. Unlike private automobile transportation, which isolates citizens from one another, public transit DC, Boston, MA, and Chicago, IL also have at least 10.0% of their non-poor workers requires us to sit and stand side-by-side with strangers. In order to gauge the degree using public transit. One third of the metropolitan areas in our cohort of 130 (43 to which transit use is a choice, rather than a necessity, we were especially interested metros) have 1.0% or less of their non-poor workers using public transit as a in use of public transportation by a city s non-poor population. mode of transit. The average transit use for the cohort was 6.6% and the median Workers 16 and over that reported usage of public transportation for their percentage of transit use was 1.3%. The fact that the average is vastly higher than journey to work are taken as a percentage of non-poor workers; people working from the median indicates that as expected larger cities tend to have more integrated home were excluded. Data is from the U.S. Census American Community Survey transit usage than smaller cities. (ACS) 3-year estimates for New York-N. New Jersey-Long Island, NY-NJ-PA 31.5% 2 San Francisco-Oakland-Fremont, CA 15.6% 3 Washington-Arlington-Alexandria, DC-VA-MD-WV 14.7% 4 Boston-Cambridge-Quincy, MA-NH 11.9% 5 Chicago-Joliet-Naperville, IL-IN-WI 11.4% 6 Philadelphia-Camden-Wilmington, PA-NJ-DE-MD 9.2% 7 Bridgeport-Stamford-Norwalk, CT 8.8% 8 Seattle-Tacoma-Bellevue, WA 8.5% 9 Honolulu, HI 8.3% AVERAGE = 6.6% 10 Portland-Vancouver-Hillsboro, OR-WA 6.2% 11 Baltimore-Towson, MD 6.0% 12 Los Angeles-Long Beach-Santa Ana, CA 5.6% 13 Pittsburgh, PA 5.3% 14 Poughkeepsie-Newburgh-Middletown, NY 4.8% 15 Minneapolis-St. Paul-Bloomington, MN-WI 4.4% 16 Denver-Aurora-Broomfield, CO 4.1% 17 New Haven-Milford, CT 3.9% 18 Madison, WI 3.7% 19 Durham-Chapel Hill, NC 3.5% 20 Las Vegas-Paradise, NV 3.5% 21 Miami-Fort Lauderdale-Pompano Beach, FL 3.5% 22 Santa Barbara-Santa Maria-Goleta, CA 3.4% 23 Salt Lake City, UT 3.3% 24 San Jose-Sunnyvale-Santa Clara, CA 3.2% 25 Milwaukee-Waukesha-West Allis, WI 3.1% 26 Hartford-West Hartford-East Hartford, CT 3.0% 27 Atlanta-Sandy Springs-Marietta, GA 2.9% 28 Cleveland-Elyria-Mentor, OH 2.9% 29 San Diego-Carlsbad-San Marcos, CA 2.8% 30 Buffalo-Niagara Falls, NY 2.8% 31 Providence-New Bedford-Fall River, RI-MA 2.6% 32 Albany-Schenectady-Troy, NY 2.6% 33 Sacramento-Arden-Arcade-Roseville, CA 2.5% 34 Spokane, WA 2.4% 35 Vallejo-Fairfield, CA 2.4% 36 Houston-Sugar Land-Baytown, TX 2.2% 37 New Orleans-Metairie-Kenner, LA 2.2% 38 Austin-Round Rock-San Marcos, TX 2.1% 39 St. Louis, MO-IL 2.1% 40 Ogden-Clearfield, UT 2.1% 41 Reno-Sparks, NV 2.0% 42 Tucson, AZ 1.9% 43 Charlotte-Gastonia-Rock Hill, NC-SC 1.9% 44 Phoenix-Mesa-Glendale, AZ 1.9% 45 San Antonio-New Braunfels, TX 1.8% 46 Springfield, MA 1.8% 47 Cincinnati-Middletown, OH-KY-IN 1.7% 48 Albuquerque, NM 1.7% 49 Orlando-Kissimmee-Sanford, FL 1.7% 50 Reading, PA 1.6% 51 Worcester, MA 1.6% 52 Louisville/Jefferson County, KY-IN 1.6% 53 Santa Rosa-Petaluma, CA 1.6% 54 Virginia Beach-Norfolk-Newport News, VA-NC 1.5% 55 Syracuse, NY 1.5% 56 Corpus Christi, TX 1.5% 57 Columbus, OH 1.5% 58 Riverside-San Bernardino-Ontario, CA 1.5% 59 Lansing-East Lansing, MI 1.5% 60 Provo-Orem, UT 1.5% 61 Rochester, NY 1.5% 62 Oxnard-Thousand Oaks-Ventura, CA 1.4% 63 Richmond, VA 1.4% 64 Cape Coral-Fort Myers, FL 1.4% MEDIAN = 1.3% 65 Dallas-Fort Worth-Arlington, TX 1.3% 66 Detroit-Warren-Livonia, MI 1.3% 67 Salinas, CA 1.3% 68 Allentown-Bethlehem-Easton, PA-NJ 1.3% 69 Fresno, CA 1.3% 70 Stockton, CA 1.3% 71 El Paso, TX 1.2% 72 Dayton, OH 1.2% 73 Tampa-St. Petersburg-Clearwater, FL 1.2% 74 Harrisburg-Carlisle, PA 1.1% 75 Charleston-North Charleston-Summerville, SC 1.1% 76 Manchester-Nashua, NH 1.1% 77 Scranton-Wilkes-Barre, PA 1.1% 78 Memphis, TN-MS-AR 1.1% 79 Nashville-Davidson-Murfreesboro-Franklin, TN 1.1% 80 Grand Rapids-Wyoming, MI 1.1% 81 Akron, OH 1.1% 82 Lancaster, PA 1.0% 83 Shreveport-Bossier City, LA 1.0% 84 Jacksonville, FL 1.0% 85 Des Moines-West Des Moines, IA 1.0% 86 Indianapolis-Carmel, IN 1.0% 87 Kansas City, MO-KS 1.0% 88 Portland-South Portland-Biddeford, ME 0.9% 89 Modesto, CA 0.9% 90 Greensboro-High Point, NC 0.8% 91 Raleigh-Cary, NC 0.8% 92 Bakersfield-Delano, CA 0.8% 93 Toledo, OH 0.8% 94 Baton Rouge, LA 0.8% 95 Deltona-Daytona Beach-Ormond Beach, FL 0.8% 96 Lexington-Fayette, KY 0.8% 97 Winston-Salem, NC 0.8% 98 Canton-Massillon, OH 0.7% 99 Omaha-Council Bluffs, NE-IA 0.7% 100 North Port-Bradenton-Sarasota, FL 0.7% 101 Flint, MI 0.7% 102 York-Hanover, PA 0.7% 103 Augusta-Richmond County, GA-SC 0.6% 104 Visalia-Porterville, CA 0.6% 105 Chattanooga, TN-GA 0.6% 106 Little Rock-North Little Rock-Conway, AR 0.6% 107 Colorado Springs, CO 0.6% 108 Lakeland-Winter Haven, FL 0.5% 109 Palm Bay-Melbourne-Titusville, FL 0.5% 110 Youngstown-Warren-Boardman, OH-PA 0.5% 111 Birmingham-Hoover, AL 0.5% 112 Fayetteville-Springdale-Rogers, AR-MO 0.5% 113 Port St. Lucie, FL 0.5% 114 Boise City-Nampa, ID 0.5% 115 Tulsa, OK 0.5% 116 Columbia, SC 0.4% 117 Knoxville, TN 0.4% 118 Brownsville-Harlingen, TX 0.4% 119 Asheville, NC 0.4% 120 Mobile, AL 0.4% 121 Pensacola-Ferry Pass-Brent, FL 0.4% 122 Oklahoma City, OK 0.4% 123 Wichita, KS 0.4% 124 Fort Wayne, IN 0.3% 125 Springfield, MO 0.3% 126 Huntsville, AL 0.3% 127 McAllen-Edinburg-Mission, TX 0.2% 128 Jackson, MS 0.2% 129 Greenville-Mauldin-Easley, SC 0.2% 130 Killeen-Temple-Fort Hood, TX 0.1% 22 23