Metro Economics

The Storefront Index

Posted on by Joe Cortright

As Jane Jacobs so eloquently described it in The Death and Life of American Cities, much of the essence of urban living is reflected in the “sidewalk ballet” of people going about their daily errands, wandering along the margins of public spaces (streets, sidewalks, parks and squares) and in and out of quasi-private spaces (stores, salons, bars, boutiques, bars and restaurants).

Clusters of these quasi-private spaces, which are usually neighborhood businesses, activate a streetscape, both drawing life from and adding to a steady flow of people outside.

In an effort to begin to quantify this key aspect of neighborhood vitality, we’ve developed a new statistical indicator—the Storefront Index (click to see the full report)—that measures the number and concentration of customer-facing businesses in the nation’s large metropolitan areas. We’ve computed the Storefront Index by mapping the locations of hundreds of thousands of everyday businesses: grocery and hardware stores, beauty salons, bookstores, bars and restaurants, movie theatres and entertainment venues, and then identifying significant clusters of these businesses—places where each storefront business is no more than 100 meters from the next storefront.

The result is a series of maps, available for the nation’s 51 largest metropolitan areas, that show the location, size, and intensity of neighborhood business clusters down to the street level. Here’s an example for Washington, DC. On this map, each dot represents one storefront business. This maps shows storefront businesses throughout the metropolitan area. In downtown Washington, there is a high concentration of storefronts; as one moves further out towards the suburbs, the number of storefronts diminishes, and storefronts are increasingly found arrayed only along major arterials, with a few satellite city centers (like Alexandria).

SFI_DC_zoomedout

The Storefront Index helps illuminate the differences in the vibrancy of the urban core in different metropolitan areas. Here we’ve constructed identically scaled maps of the Portland and St. Louis metropolitan areas, zoomed in on their central business districts. The light colored circle represents a three-mile radius around the center of downtown. In Portland, there are about 1,700 storefront businesses in this three-mile circle—with substantial concentrations downtown, and in the close-in residential neighborhoods nearby. St. Louis has only about 400 storefront businesses in a similar area, with a smaller concentration of storefront businesses in its center, and fewer and less dense commercial districts in nearby neighborhoods.

SFI_PDX

SFI_StLouis

The Storefront Index is one indicator of the relative size and robustness of the active streetscape in and around city centers. As this table shows, there’s considerable variation among US metropolitan areas in the number of storefront businesses with three miles of the center of downtown. New York and San Francisco have the densest concentrations of storefront businesses in their urban cores.

 

Maps of the Storefront Index for the nation’s 51 largest metropolitan areas are available online here. You can drill down to specific neighborhoods to examine the pattern of commercial clustering at the street level.

We also use the Storefront Index to track change over time, looking at the growth of businesses and street level activity in a rebounding neighborhood in Portland. There’s also strong evidence to suggest that concentrations of storefront businesses provide a conducive environment for walking. We’ve overlaid the storefront index clusters on a heat map of Walk Scores for selected metropolitan areas to explore the relationship between these two measures. While Walk Score includes destinations like parks and schools, as well as businesses, it also measures walkability from the standpoint of home-based origins, while our Storefront Index shows the concentration of commercial destinations.

City Observatory has developed the Storefront Index as a freely available tool for urbanists and city planners to use in their communities. The index material is licensed under a Creative Commons Attribution license (as is all City Observatory material), and shapefiles containing storefront index information is available here.

Has the Tide Turned?

Posted on by Joe Cortright

Last month, City Observatory released a new report—Surging City Center Job Growth—chronicling a widespread rebound in city center jobs. For the first time in decades, job growth in city centers around the country has surpassed the rate of job growth in peripheral areas.

In an article called “Fool for the City,” Jacob Anbinder of The Week responded to recent media reports about the return of city centers, commenting that the issue may have been over-hyped in the media. You might think that a publication that bills itself as “All you need to know about everything that matters”  might be a little bit more reticent in accusing others of hyperbole. Just the same, let’s take a minute to address the points raised in this article, and allay Mr. Anbinder’s fears.

As we described in our report, what’s remarkable about this trend is how it runs counter to the decades-long pattern of job decentralization. In analyzing data reaching back to the 1940s, we showed the steady ebbing of the relative economic importance of city centers. The message here isn’t a new era of urban triumphalism, so much as it is the end of a long period of unabated decentralization.

As a reminder, here are the key data points from our report:

We were careful in our work to flag the importance of the industrial composition of employment change through the business cycle on the observed patterns of job losses and gains. There’s no question that cities benefited from the strength of centralized industries, like professional services and finance, relative to the weakness of more decentralized industries like manufacturing, construction, and distribution. (In addition, contrary to the implication of the article that city center results were driven by government employment, our data excluded public administration employment.) But even after controlling for these industry variations, we showed that city centers had recorded a significant gain in their competitive position vis-a-vis suburbs.

The Week points out that for the entire nine-year period under consideration, many city centers were still below their 2001 level of employment. There is no question that the earlier 2002-07 period was a continuation of the historical trend, and that nearly all cities were then losing share of total metro employment. The key point in our study is that during the last four years for which we have data, the trend is quite different. (It is worth noting that 2002-07 was the height of the housing bubble and the peak of ex-urban development and job decentralization.) It’s hardly remarkable that most city centers didn’t grow fast enough in the four years coinciding with a very weak national economy to offset the relative decline they endured in the previous five.

Our report was quite clear that this pattern of city center revival isn’t universal. In the 2002-07 period, seven of 41 metropolitan areas outperformed their peripheries; in the 2007-11 period, 21 outperformed their peripheries. (21 of 41 is not an overwhelming majority; it is, however, a much bigger group than the 7 cities that saw this pattern in the previous time period.) As in politics, all economic geography is local: some city centers continue to follow the historic pattern of having growth that lags well behind their expanding suburban peripheries. We noted that job decentralization is still the order of the day in places like sprawling Houston and Kansas City.

It’s not surprising to find that the nascent urban comeback is happening faster in some places than in others: centralized employment did well in New York and San Francisco in the earlier 2002-07 period, when nearly all other city centers were lagging well-behind their peripheries in job growth. More analysis is needed to discern what sets of factors—industry mix, local policies, population movement—are at work in each metropolitan area.

There’s undoubtedly a lot to be learned from a closer, city-by-city and industry-by-industry examination of the data. This is the reason we published our report, and also why we’ve made our data available for others to download and analyze. Moreover, the underlying source of data, the Census Bureau’s Local Employment and Housing Dynamics series, is a powerful, yet under-used source of insight into the economic processes at work in our nation’s cities. We hope others will mine this data to generate an even richer picture of the changing geography of urban employment.

As we stressed in our report, four years of data drawn from a particularly turbulent time in our economic history is hardly the final word. We’re eager to see more recent data—the 2012 to 2014 data should be released by the Census Bureau later this year. When they are, we’ll be better able to judge whether the changes we’ve recorded in the past few years are a cross-current or a true turning of the tide.

Any Port in a Storm?

Posted on by Joe Cortright

Over the past few weeks, there’s been a fair amount of media furor over the slowdown in container traffic handling on the West Coast as dockworkers and shipping companies negotiated the new terms of a labor deal.

You no doubt heard a fair amount of hyper-ventilation about the economic consequences of disruptions to this international supply line. Unsurprisingly, the longshoremen’s union took maximum advantage of its leverage over workflow to drive a hard bargain with the shippers. This is a kind of kabuki show that is repeated whenever these multi-year contracts are up for renewal. And, as almost always happens, the two parties have come to an agreement, and ports, especially the Ports of Los Angeles and Long Beach are working quickly to move the backlogged traffic.

With the prospect of a new wider Panama Canal re-arranging the competitive environment for global shipping, many seacoast cities are giving new thought to how port traffic might influence their future growth prospects.  There’s little question that big “load-center” ports are hubs of commerce, where the economies of scale in shipping seem to be creating a winner-take-all situation.

But how big a deal is container traffic to the typical metropolitan economy? What if your city isn’t the big winner in the container traffic game?  That question is a very live one in Portland. Overshadowed by the furor generated by the coast-wide slowdown was an announcement earlier this month by Korean shipper Hanjin that it was terminating container service to the Port of Portland. Hanjin accounts for three-quarters of Portland’s container traffic.

In a new column in Oregon Business magazine, I examine the economic ramifications of the Portland’s loss of dock-side container service.

For a city whose first name is “port,” the loss of container service seems like an economic body blow. We are constantly being told that Oregon has a “trade-dependent” economy. How will we survive without this iconic connection to the global marketplace?

The answer will surprise you: Just fine.

You can read the rest at OregonBusiness.Com

There’s little doubt that container service is a highly visible icon of any city’s connections to the global economy. It’s the sort of thing that television reporters can stand up in front of a camera and tell visually compelling stories.

But for most city economies, dockside container service has little to do with whether they succeed or fail in the global economy. The ability of cities to compete hinges not on whether they can cheaply move bulk goods, but on whether they can create world-class products. Particularly in high-cost countries like the United States, firms compete on product differentiation and performance, not transportation cost. This is true of the high-value products of advanced industries: everything from commercial jets to computer chips. This is even more true for services–software, motion pictures, financial services–for which physical movement of product is essentially irrelevant.

As we move toward an increasingly intangible, innovation-driven economy, the old metaphors we use to visualize the economy are becoming a less useful guide to thinking about how the world works.

Who’s Vulnerable to Retail Retrenchment?

Posted on by Joe Cortright

This week comes news that Target is laying off 1,700 workers at its Minneapolis headquarters, looking to become leaner and more efficient. It’s just the latest move in a shifting retail landscape in the United States.

Target is not just downsizing its headquarters, it’s shifting to smaller urban stores–Target Express. Other retailers like Walmart and Office Depot have have also been developing smaller stores. The days of big boxes and power centers seem to be giving way to to more urban-centered and smaller-footprint retailing, undermining the economics of larger-scale retailing. It’s estimated that there are over 1,200 dead or dying malls in the U.S. It appears that we’re way overbuilt for retail space. Finding productive uses for these disused spaces is now a major undertaking for communities around the nation.

Several factors seem to be driving the tectonic shifts in retailing. Part of the problem is that retail, like housing,was overbuilt during the bubble: commercial developers typically followed new housing development, and as the housing stock sprawled in the last decade, so too did the expansion of retail space.

Another important factor is the technological change in the form of growing e-commerce. More and more, we’re purchasing goods and services via the Internet and mobile devices. According to data compiled by Erik Brynjolfsson, e-commerce now accounts for about 30 percent of non-food, non-auto retailing, and is continuing to grow:

fred

There’s a bit of irony here: big box stores only become economically feasible thanks to earlier technological advances, including universal product codes, computerized inventory management, real-time ordering, and global data networks. These same technologies now help enable smaller stores (tailoring inventory to localized demand) and empower consumers to order online at home and via pervasive mobile devices.

The shifting retail environment will have impacts on the transportation system as well. The latest transportation data show a decline in the number and length of shopping trips (which decreases transport intensity of retailing), but this is at least partially offset by more travel by commercial delivery vehicles (like UPS and Fedx). It’s an open question as to how this will play out: will these shifts encourage (more) fleets of smaller transit trucks, or will increasing e-commerce retail sales and smaller urban stores mean larger trucks on urban roads? (Regardless, the D.O.T. believes e-commerce will significantly impact our road infrastructure by 2045, and that despite the hopes of Jeff Bezos, drones may not help solve that any time soon.)

To judge who’s most likely to be affected by these trends, we compiled some metropolitan level data on the amount of retail space per capita. The data come from Co-Star, a private firm that tracks retail space leasing throughout the nation. (They helpfully make their market reports available here). These data are for 2007 and we’ve computed retail space per capita in each market by dividing total square footage by each metropolitan area’s 2007 population.

The national average is about 46 square feet of retail space per capita, with most metropolitan areas having between 40 and 55 square feet per capita. There are a number of outliers, however.

Milwaukee/Madison has the highest amount of retail space per capita, and many southern, sprawled metros rank higher on this metric as well. These are the places most likely to struggle with a dwindling appetite for retail space, and the economic consequences that follow, be it in fewer retail jobs, large swathes of unused space, or transportation costs. At the other end of the spectrum, some metropolitan areas have far more space-efficient retailing: Portland has just 30 square feet of retail space per capita, fully one-third less than the national average.

By global standards, the U.S. has much more space devoted to retailing than anyone else: comparable estimates for other countries include: 23 square feet per capita in the United Kingdom, 13 square feet per capita in Canada, and 6.5 square feet per capita in Australia. If the experience of these countries is any indication, it’s a good bet that there’s lots there’s still lots of room for downsizing in the U.S. retail sector. However, despite these trends, Miami apparently isn’t concerned.

How much could US retail shrink? And where?

Posted on by Joe Cortright

The first quarter of 2017 has marked a parade of announced store closures. The long awaited axe has fallen on 68 more Macy’s stores around the country. J.C. Penney has announced it will close another 138 stores. Other major national retail chains, including The Limited, Gap, Walgreens, Aeropostale and Chico’s, have also announced similarly large closures.  These are just the latest moves in a shifting, mostly shrinking retail landscape in the United States.

One retailer, Target is not just downsizing its store count, it’s shifting to smaller urban stores–Target Express. Other retailers like Walmart and Office Depot have have also been developing smaller stores. The days of big boxes and power centers seem to be giving way to to more urban-centered and smaller-footprint retailing, undermining the economics of larger-scale retailing. It’s estimated that there are over 1,200 dead or dying malls in the U.S. It appears that we’re way overbuilt for retail space. Finding productive uses for these disused spaces is now a major undertaking for communities around the nation.

Several factors seem to be driving the tectonic shifts in retailing. Part of the problem is that retail, like housing,was overbuilt during the bubble: commercial developers typically followed new housing development, and as the housing stock sprawled in the last decade, so too did the expansion of retail space.

Another important factor is the technological change in the form of growing e-commerce. More and more, we’re purchasing goods and services via the Internet and mobile devices. Census Bureau data on retail sales show that e-commerce continues to increase its market share.  Excluding restaurant sales, and sales of vehicles and gasoline, e-commerce now accounts for about 12 percent of all retailing, a figure that has effectively doubled in the past six years.

There’s a bit of irony to the technological displacement at work here: big box stores only became economically feasible thanks to earlier technologies, like universal product codes, computerized inventory management, real-time ordering, and global data networks. These same technologies now help enable smaller stores (tailoring inventory to localized demand) and empower consumers to order online at home and via pervasive mobile devices.

The shifting retail environment will have impacts on the transportation system as well. The latest transportation data show a decline in the number and length of shopping trips (which decreases transport intensity of retailing), but this is at least partially offset by more travel by commercial delivery vehicles (like UPS and Fedex). It’s an open question as to how this will play out: will these shifts encourage (more) fleets of smaller transit trucks, or will increasing e-commerce retail sales and smaller urban stores mean larger trucks on urban roads? There’s some evidence that Internet delivery will mean less car travel, as the decline in shopping travel will more than offset the increased vehicle travel associated with deliveries. And delivery efficiency actually increases as volumes increase.

To judge who’s most likely to be affected by these trends, we compiled some metropolitan level data on the amount of retail space per capita. The data come from Co-Star, a private firm that tracks retail space leasing throughout the nation. (They helpfully make their market reports available here). These data are for 2007 and we’ve computed retail space per capita in each market by dividing total square footage by each metropolitan area’s 2007 population.

The national average is about 46 square feet of retail space per capita, with most metropolitan areas having between 40 and 55 square feet per capita. There are a number of outliers, however.

Milwaukee/Madison has the highest amount of retail space per capita, and many southern, sprawled metros rank higher on this metric as well. These are the places most likely to struggle with a dwindling appetite for retail space, and the economic consequences that follow, be it in fewer retail jobs, large swathes of unused space, or transportation costs. At the other end of the spectrum, some metropolitan areas have far more space-efficient retailing: Portland has just 30 square feet of retail space per capita, fully one-third less than the national average.

By global standards, the U.S. has much more space devoted to retailing than anyone else: comparable estimates for other countries include: 23 square feet per capita in the United Kingdom, 13 square feet per capita in Canada, and 6.5 square feet per capita in Australia. If the experience of these countries is any indication, it’s a good bet that there’s lots there’s still lots of room for downsizing in the U.S. retail sector. However, despite these trends, Miami apparently isn’t concerned.

Florida’s Biotech Bet

Posted on by Joe Cortright

For more than a decade, one of the hottest trends in economic development has been pursuing biotechnology. Cities and states around the nation have made considerable investments in biotech research, ranging from California’s voter-approved $3 billion research program, to smaller efforts in cities around the country, including Indianapolis, St. Louis, and Phoenix.

One of the states that made the biggest bets on biotech was Florida, which in 2003 committed state funds to luring the Scripps Research Institute to building a new campus in Palm Beach County. The Scripps deal served as a template for subsidies to other life sciences research institutions opening similar research labs in other Florida cities. The total cost of the program is estimated to reach more than $800 million.

In a new article, Reuters has questioned whether Florida has gotten its money’s worth for the investments it has made in biotechnology. The biotech investments were originally sold based on the promise that they would lead to a flourishing new industry employing more than 44,000 people. But a decade later, there’s little evidence of progress.

We’ve long followed the biotechnology industry. In 2002, my colleague Heike Mayer and I undertook an extensive study of the clustering of the US biotech industry, published by the Brookings Institution–Signs of LIfe–which showed that the industry’s economic impact was tightly concentrated in just a few leading centers around the nation. While life sciences research was becoming slightly more widespread as more cities competed for National Institutes of Health (NIH) funding, all of the measures of commercialization–new firm startups, venture capital investment, and privately funded research and development partnerships– were becoming more concentrated in a few leading cities. Our analysis showed that three biotech leaders (Boston, San Francisco, and San Diego) had decisive competitive advantages in starting and growing new biotech firms that other cities would find difficult, if not impossible, to overcome.

The succeeding decade has confirmed our original analysis. The three leading centers are even more dominant today that they were a decade ago. In 2000-01, Boston, San Francisco, and San Diego accounted for about 54 percent of venture capital invested in biotechnology. In 2010-12, the three metros accounted for 60 percent of biotech venture capital. Data on venture capital flows come from the PriceWaterhouseCoopers Moneytree survey.

There’s probably no better indicator of the growth of biotechnology commercialization than the flow of venture capital funds to new startup companies. By this measure, the state of Florida’s position is essentially no different than it was a decade ago. While venture capital funding fluctuates from quarter to quarter, Florida’s share of national biotechnology venture capital funding is still less than 1 percent–in the same range that it was before its subsidies to Scripps and other research laboratories.

As it turns out, doing biomedical research doesn’t automatically lead to new companies and job creation. The hard and costly work of turning promising research ideas into marketable products happens in only a few places. The challenge in growing a commercial biotechnology hub is in overcoming the overwhelming competitive advantages that established clusters have in being places that have the financial, human, and institutional resources to succeed in this complicated and risky business. Despite the time and expense that Florida and other states have invested in biotech research, there’s almost no evidence that anyone has made anything more than marginal changes to the landscape of the U.S. biotech industry.

Jobs Return to City Centers

Posted on by Joe Cortright
(This post coincides with the newly released report, Surging City Center Job Growth. The report and more details are found here.) 

For decades, urban economists have chronicled the steady decentralization of employment in our metropolitan areas. First people moved to the suburbs for low density housing, and then businesses followed—especially retail and service businesses that catered to decentralized population. Over time, the manufacturing and distribution business which had traditionally chosen city-centered transportation hubs also moved to more sprawling locations, enabled by the shift to truck transportation and the growth of the nation’s highway system.

A few industries continued to be disproportionately found downtown. Banks, insurance companies, government offices, and many professional service firms still preferred central office locations that facilitated easy face-to-face contact. But retail moved increasingly to suburban malls and highway strip centers, manufacturing and distribution to industrial parks, and many clerical and administrative functions moved from the center to more dispersed office parks.

At City Observatory, we’ve tracked the growing movement of talented young workers back to urban neighborhoods. The growing attractiveness of urban living is leading to measurable increases in skill level of the labor force near city centers. Employers are taking notice: a growing number of firms report that they are choosing downtown locations in order to tap into the growing talent pool of young workers.

We’ve identified dozens of examples of these downtown moves and expansions, which led us to ask whether this was actually moving the needle in city center employment levels. We tapped a novel and relatively new data source, the Census Bureau’s Local Employment and Housing Dynamics (LEHD) series. It maps, block-by-block, the location of jobs in most of the nation’s metropolitan areas. Building on a research methodology developed originally by Ed Glaeser and Matt Kahn, and further applied by Brookings researcher Elizabeth Kneebone, we focused on the number of jobs within a three-mile circle surrounding the center of the central business district of each of the nation’s largest metro areas. We used a similar technique, and different data, as part of our Young and Restless report in October.

Looking back over the past decade, we found a remarkable reversal in the pattern of job growth. During the economic expansion from 2002 to 2007, the historic trend of job decentralization was very much present. City centers saw employment growth of barely one-tenth of a percent per year, while the more outlying areas grew ten times as fast.

But since 2007—the period coinciding with the onset and early recovery from the Great Recession—the picture changed dramatically. In the aggregate, the 41 metropolitan areas for which we have comparable data showed a 0.5 percent per year growth in city center employment and a 0.1 percent decrease in employment in the periphery. While only 7 city centers outperformed their surrounding metros in the 2002-07 period, 21 outperformed the periphery in 2007-11. This is a widespread trend, however the change isn’t yet universal. The growth rate of outlying areas still widely outstrips that of the city center in a half dozen metropolitan areas including Houston, Kansas City, and Las Vegas.

Data documenting this reversal come from an extremely volatile period in our recent economic history—2007 to 2011, covering the time from the peak of the last economic cycle through the trough of the Great Recession, and the first two years of recovery. We know that cyclical factors, particularly the decline in construction and goods-producing industry, caused the economic blow to fall heavily on more decentralized businesses.

To separate out the effects of the economic cycle from underlying trends in city center competitiveness, we developed a shift share analysis that looks at the change in employment by industry sector. This analysis shows that while more centralized industries outperformed decentralized ones, this factor alone didn’t account for the city center growth. Compared to the previous period, city centers actually erased their competitive disadvantage relative to suburbs, and in some industries (arts, entertainment, dining, lodging, and finance, insurance, and real estate) clearly outperformed more peripheral locations.

We think that there are a number of reasons to believe that the relatively strong performance of city centers will be maintained in this economic expansion. As we noted in our Young and Restless report last year, talented young workers are increasingly choosing to live in and near city centers. Just as the outward migration of population propelled employment decentralization in the last century, it may well be that the movement of population back to the center will sustain employment growth in city centers.

We look forward to following this trend as more data becomes available; to read the full report, go here.

Urban Employment: How does your city compare?

Posted on by CityObservatory Guest

As chronicled in our report here and commentary here, we are seeing evidence of a shift in employment back to city centers. We believe that this is driven by a number of forces, including the increasing preference of young, talented workers for urban living; some of this shift is cyclical and coincides with the fact that more decentralized industries (construction, warehousing) bore a greater brunt of the pain of the Great Recession. Some of the success has to do with cities gaining competitive advantages over their peripheral counterparts. Regardless of the causes, we are seeing that from 2007-11, aggregate performance of city centers was better than that of their more decentralized peripheries.

Still, there are always outliers– as well as cities that exemplify the trend– so we thought we’d present the following dashboard displaying results for individual metros. It shows the annual growth of employment in the city center (a 3 mile radius from the center of the central business district), as well as in the periphery (defined as the area outside the 3-mile radius).  Data are for two time periods:  2002-07 and 2007-11. Use the dropdown menu to select a metropolitan area.

Our dashboard also allows you to compare, side-by-side, the performance of a selected metro area with the aggregate performance of the 41 metropolitan areas included in our study.  To see this comparative summary, select the right-hand tab at the top of the dashboard.

Less in Common

Posted on by Joe Cortright

The essence of cities is bringing people—from all walks of life—together in one place.  Social interaction and a robust mixing of people from different backgrounds, of different ages, with different incomes and interests is part of the secret sauce that enables progress and creates opportunity.  This ease of exchange underpins important aspects of our personal lives, civic effectiveness and economic development.

But over the past several decades, a number of trends–some social, some economic, some political, and others technological–have interacted to dramatically change the ways, the places, and the amounts of interaction between different groups in our society.  By many measures, we now spend less time in social settings, and are less likely to regularly interact with people whose experiences are different from our own.  In our schools, communities, work, shopping and personal activities, we’re increasingly separated from one another.

Our new report, Less in Common, surveys a wide range of measures of how Americans have grown apart from one another over the past several decades.  We’ve intentionally drawn promiscuously from a variety of fields to illustrate the breadth and variety of ways in which this trend seems to be unfolding.

Many of these changes are reflected in the physical landscape of our cities.  In North America, development patterns, particularly the growth of suburbs after World War II, diminished access to an easily shared urban life.  Space and experiences became more private, fueled by suburban expansion, large lots, and the predominance of single-family homes. These development patterns have resulted in Americans having “less in common.”  This phenomenon appears to play out in many different ways:

Distrust among Americans is increasing.  A key marker of social capital that is regularly used in comparing nations and tracking trends over time is the generalized feeling of trust.  The General Social Survey reports that the share of the population that says “most people can be trusted” has fallen from a majority in the 1970s, to about one-third today.

Americans spend significantly less time with their neighbors.  In the 1970s, nearly 30 percent of Americans frequently spent time with neighbors, and only 20 percent had no interactions with them.  Today, those proportions are reversed.

The biggest portion of our leisure time is spent watching television.  TV watching is up to 19 hours per week today compared to about 10 hours in the 1960s.  We spend less time socializing and communicating.

Our recreation is increasingly privatized.  Since 1980, the number of members of private health clubs have quadrupled to more than 50 million.  We used to swim together—prior to World War II, almost all pools were public.  Today, we swim alone in the 5 million or so private swimming pools compared to just a few thousand public ones.

Driving alone has become the norm, with transit reserved for the poor. Today, 85 percent of American commuters travel to work in private automobiles, up from 63 percent in 1960.  Carpooling has fallen by half since 1980, and the share who commute via transit has declined from 12 percent in 1960 to less than 5 percent today.

Economic segregation trends upward as middle-income neighborhoods decline. High-income and low-income Americans have become more geographically separated within metropolitan areas. Between 1970 and 2009 the proportion of families living either in predominantly poor or predominantly affluent neighborhoods doubled from 15 percent to 33 percent.

Many of us live in gated communities. By 1997 it was estimated that there were more than 20,000 gated community developments of 3,000 or more residents. By design, gated communities restrict access and carefully control who is allowed into a community to separate residents from outsiders.

Politically, America sorts itself into like-minded geographies.  Nearly two-thirds (63 percent) of consistent conservatives and about half (49 percent) of consistent liberals say most of their close friends share their political views.

There are some counter-trends to the general pattern of isolation and separation.  Racial segregation, though still high, has declined steadily for decades. New community spaces—like farmer’s markets—have grown rapidly.  Widespread availability of the Internet combined with social media has made it easier and more democratic to connect with others and with all forms of information.

A broadly shared sense of common interest, anchored in a society that promotes social mobility and easy interaction, is a vital underpinning of effective political institutions and the economy.  If we’re going to make progress in tackling a range of our nation’s challenges, and live up to our full potential, we need to reinvigorate the civic commons.

You can also see the findings in the form of an easy-to-share infographic:

Click to see the full infographic.
Click to see the full infographic.

Surging City Center Job Growth

Posted on by Joe Cortright

For over half a century, American cities were decentralizing, with suburban areas surpassing city centers in both population and job growth. It appears that these economic and demographic tides are now changing. Over the past few years, urban populations in America’s cities have grown faster than outlying areas, and our research shows that jobs are coming with them.

Our analysis of census data shows that downtown employment centers of the nation’s largest metropolitan areas are recording faster job growth than areas located further from the city center. When we compared the aggregate economic  performance of urban cores to the surrounding metro periphery over the four years from 2007 to 2011, we found that city centers—which we define as the area within 3 miles of the center of each region’s central business district—grew jobs at a 0.5 percent annual rate. Over the same period, employment in the surrounding peripheral portion of metropolitan areas declined 0.1 percent per year. When it comes to job growth, city centers are out-performing the surrounding areas in 21 of the 41 metropolitan areas we examined. This “center-led” growth represents the reversal of a historic trend of job de-centralization that has persisted for the past half century.

As recently as 2002-2007, peripheral areas were growing much faster (1.2 percent annually) and aggregate job growth was stagnant in urban cores (0.1 percent). While the shift of metropolitan job growth toward services is aiding job centralization, the strong central growth of 2007-11 appears to be driven by the growing competitiveness of central cities relative to peripheral locations.

Our analysis shows that city centers had unusually strong job growth relative to peripheral locations in the wake of the Great Recession. Some of the impetus for central city growth comes from the relatively stronger performance of industries that tend to be more centralized, such as finance, entertainment, restaurants, and professional services.  The story is not just that job growth in central cities is improving when compared to outlying areas – city centers have also erased their competitive disadvantage relative to peripheral locations.

We undertook a shift-share analysis that allowed is to separate out the effects of changing industry mix from relative competitiveness. The data make it clear that city centers are more competitive in 2011 than they were in 2007. While city centers had a negative competitive effect in the 2002-07 period, their relative competitiveness for industry has been equal to peripheral locations from 2007-11.

 

The strength of city centers appears to be driven by a combination of the growing attractiveness of urban living, and the relatively stronger performance of urban-centered industries (business and professional services, software) relative to decentralized industries (construction, manufacturing) in this economic cycle. While it remains to be seen whether these same patterns continue to hold as the recovery progresses, (the latest LEHD data on city center job growth are for calendar year 2011), there are structural forces that suggest the trend of center-led growth will continue.

To hear a podcast on the report and its ramifications, go here. 

Download the full report on this page to learn more about this shift and read our complete analysis.

Tracking Neighborhood Change: How we made “Lost In Place”

Posted on by Dillon Mahmoudi

In this post, we’ll go over the data and mapping steps that were used to create our Lost In Place report on the concentration of poverty and the interactive web map. This post is one of several commentary posts that accompany the report, including an examination of how poverty has deepened.

Data for our report is provided at the Census Tract geography for US Metropolitan Statistical Areas (MSAs) with a 2010 population of over 1 million people — 51 in total. Our online map and report are based off two reported data points across five Census years: population and poverty levels in 1970, 1980, 1990, 2000 and 2010. Unfortunately for data analysis, Census Tract boundaries changed each census year between 1970 and 2010 as the geography of people changed. Fortunately, John Logan of Brown University and his colleagues released the Longitudinal Tract Database (LTDB) and have estimated tract-level Census counts from historical Census data from 1970 through 2010 using Census 2010 tract boundaries.

Two additional steps were necessary: we needed to determine which Census Tracts were part of our MSAs of interest, and in order to create maps and determine which tracts are within 10 miles of each MSAs central business district (CBD), we need to merge the Census tract data with their corresponding Census tract polygons. First, each 2010 Census Tract number is composed of a 2-digit identifier for the state, a 3-digit county identifier, followed by a 6-digit tract identifier. For example, Census Tract number 41051010600 can be decomposed State 41 (Oregon), County 051 (Multnomah) and Tract 010600. Using the Census Metropolitan Statistical Area Definition Files, we see that any Census Tract that starts with 41051 (often referred to as the FIPS State-County) is within the MSA 38900 (Portland-Vancouver-Hillsboro, OR-WA). Using this information, we filtered the our tracts list to only those within our MSAs of interest.

Second, using only this filtered set of Census Tracts, we matched the Census Tract numbers to the Census Tract numbers of Census 2010 tract shapefiles. Using a list of CBDs for each of the metro areas, we calculated the distance from the CBD to the nearest point of each MSAs Census Tract polygon. Once this spatial relationship is calculated, we could calculate totals for core MSA and the MSA as a total.

Using the existing literature, we developed the typology of tracts in poverty featured in the report. We used QGIS to create GEOJSON-based shapefiles with the geographic data in them. This allows us to host the files on github, making them available for download. But first, we needed to shrink the size of the shapefiles in order to serve an entire metro areas tract files quickly. We did this by simplifying the geography using rgeos in R. Additionally, by having a shapefile for each metropolitan area, we can quickly and dynamically load shapefiles for each metro area. To create the interactive maps for each metro, we used a combination of Mapbox.js and the Stamen Design basemaps.

We hope that both the data and the analysis that we develop at City Observatory help advance the understanding of cities.  Please feel free to contact us with your questions and comments.

Our dataset can be downloaded here.

How Poverty Has Deepened (part 2)

Posted on by CityObservatory Guest

Recently, we discussed the growth in the number of urban high-poverty neighborhoods, which we illustrated by examining the distribution of poverty rates among census tracts. This analysis showed that high poverty neighborhoods are becoming more common in urban areas. Today we will use this distribution to discuss what few of us have directly experienced: extremely concentrated poverty. There is a small but growing segment of the population that lives in significantly differently conditions than the rest of the population; this group is one that sees extreme hardship and the highest rates of poverty nationally.

As you can see, while next to no one lived in urban census tracts had an 80% or higher poverty rate in 1970, over 72,000 people lived in neighborhoods with an 80% or higher poverty rate 40 years later. 20,000 lived in tracts with a 90% or higher poverty rate. It is extremely difficult for many to imagine living in a neighborhood where 1 in 2 people live in poverty (notice that this number tripled 1970 to 2010), but to live in a place where almost no one lives on more than $22,050 a year- for a family of 4- has profound implications for those residents.

While 72,000 is not a lot in the scope of the millions of residents of urban neighborhoods nationwide, it is still deeply concerning to have that many live in pockets of such highly concentrated poverty. To understand more about what 80% poverty means, I examined a census tract in Cleveland with an 83% poverty rate. It is census tract # 39035109801, and it is part of the Central neighborhood in Cleveland. In 1970, it had over a 50% poverty rate. Google Earth shows this picture of it:

cleveland google maps

It is a mix of empty land, industrial warehouses, and low-income housing units. The 2010 Census data provides the following demographic breakdown:

These are extremely atypical demographics. For example, the national median household income was $50,046 in 2010, compared to $7,654 in this neighborhood. Even with pictures, numbers, and demographic profiles, it is very difficult for most people to understand how difficult it can be to live in a place with this level of poverty.

We know that high poverty rates– even at the levels of 30% instead of 50% or higher- can have long-lasting implications for residents. Specifically,

“Concentrated poverty is associated with negative social effects (higher crime, worse mental and physical health), and lower economic prospects (both for current residents now and their children over their lifetimes). Concentrated poverty tends to be self-reinforcing: low-income communities have fewer fiscal resources (despite greater needs), producing low-quality public services. A lack of strong social networks undercuts the political efficacy of these citizens. There are a number of studies that review the extensive literature on the negative effects of concentrated poverty (Jargowsky & Swanstrom, 2009; Sard & Rice, 2014; Kneebone, Nadeau, & Berube, 2011).” –Lost in Place: Why the persistence and spread of concentrated poverty—not gentrification—is our biggest urban challenge.

Most troubling is the direct impact on children in poverty. 26% of children are living in poverty, almost double the national rate (14.5%). In the neighborhood I just highlighted, 897 children 14 and younger—or 45% of the population according to the census—grew up in a place where if they were not impoverished, almost all of their neighbors were. The effects of a poor neighborhood, including sub-standard public services, worse schools, a lack of social ties necessary to get better jobs, and the many other well-noted direct social and economic impacts of living in concentrated poverty all mean that a growing number young children are growing up with less of a chance than they would have had 40 years ago.

More unfortunately, this also means that demographically, the growing concentration of poverty and income segregation has resulted in lower opportunities for people of color. Poverty and lowered income mobility disproportionately affects children of color; 71% of black infants and toddlers are low income, as are 67% of Hispanic infants and toddlers. (The Central neighborhood above is an even more extreme example of this disproportionality.) New evidence by Reardon, Fox and Townsend (2014) examines economic integration and racial segregation, noting that:

“The racial disparities in neighborhood income distributions are particularly troubling because these are differences that are present even among households with the same incomes. If long-term exposure to neighborhood poverty negatively affects child development, educational success, mental health, and adult earnings (and a growing body of research suggests it does, as noted above), then these large racial disparities in exposure to poverty may have long-term consequences. They mean that black and Hispanic children and families are doubly disadvantaged—both economically and contextually—relative to white and Asian families.”

Given the self-reinforcing nature of poverty and its effects, this is a very concerning trend for black and Hispanic communities. The more common experience of urban poverty, and its concentration and deepening, doesn’t add up to a promising future- for any of us.

(At CityObservatory, we will continue to explore themes of poverty, economic integration, and policy solutions aimed at alleviating these issues. We also hope to illuminate growing evidence that increasing the welfare of low-income citizens has positive implications for middle and higher-income citizens. To read more about income segregation and economic opportunity, go here. For some links to articles we find particularly relevant go here and here.)

How Should Portland Pay for Streets?

Posted on by Joe Cortright

For the past several months, Portland’s City Council has been wrestling with various proposals to raise additional funds to pay for maintaining and improving city streets. After considering a range of ideas, including fees on households and businesses, a progressive income tax, and a kind of Rube Goldberg income tax pro-rated to average gasoline consumption, the council has apparently thrown up its hands on designing its own solution.

The plan now is for the street fee solution to be laid at the feet of Portland voters in the form of a civic multiple choice test: Do you want to pay for streets with a monthly household street fee, a higher gas tax, a property tax, an income tax or something else entirely?

Given voter antipathy of taxes of any kind, it’s likely that “none of the above” would win in a landslide if it’s included as an option on the ballot (not likely).

All of these options have their own merits and problems, and it’s doubtful that there is a majority consensus for any one of them. How, how much, and who pays for streets is a key issue for every city. From an urbanist and public finance perspective, and as a guide to thinking about which—if any—of these approaches Portland should adopt, here are my eight suggested rules for paying for streets:

1. Don’t tax houses to subsidize cars. Despite mythology to the contrary, cars don’t come close to paying for the cost of the transportation system. The Tax Foundation estimates that only 30% of the cost of roads is covered by user fees like the gas tax. Not only do cars get a free ride when it comes to covering the cost of public services—unlike homes, they’re exempt from the property tax—but we tax houses and businesses to pay for car-related costs. Here are three quick examples: While half of storm runoff is from streets, driveways and parking lots, cars aren’t charged anything for stormwater—but houses are. A big share of the fire department’s calls involve responding to car crashes—and cars pay nothing toward fire department costs. Similarly, the police department spends a significant amount of its energy enforcing traffic laws—this cost is borne largely by property taxes—which houses pay, but cars don’t. If we need more money for streets, it ought to be charged on cars.

Adding a further charge on houses to subsidize car travel only worsens a situation  in which those who don’t own cars subsidize those who do. One in seven Portland households doesn’t own a car, and because they generally have lower incomes than car owners, fees tied to housing redistribute income from the poor to the rich.

2. End socialism for private car storage in the public right of way. Except for downtown and a few close-in neighborhoods, we allow cars to convert public property to private use for unlimited free car storage. Not asking those who use this public resource to contribute to the cost of its construction and upkeep makes no sense and ultimately subsidizes car ownership and driving. This subsidy makes traffic worse and unfortunately—but understandably—makes it harder and more expensive to build more housing in the city’s walkable, accessible neighborhoods. If, as parking expert Don Shoup has suggested, we asked those who use the streets for overnight car storage to pay for the privilege, we’d go a long way in reducing the city’s transportation budget shortfall—plus, we’d make the city more livable.  We should learn from the city’s success in reforming handicapped parking that getting the prices right makes the whole system work better.

3. Reward behavior that makes the transportation system work better for everyone. Paying for the transportation system isn’t just about raising revenue—it should be about providing strong incentives for people to live, work and travel in ways that make the transportation system work better and make the city more livable. Those who bike, walk, use transit, and who don’t own cars (or own fewer cars) actually make the street system work better for the people who do own and use cars. We ought to structure our user fee system to encourage these car-free modes of transportation, and provide a financial reward to those who drive less. The problem with a flat-household fee or an income tax is it provides no incentive for people to change their behavior in a way that creates benefits for everyone.

4. Prioritize maintenance. There’s a very strong argument that we shouldn’t let streets deteriorate to the point where they require costly replacement. Filling potholes and periodically re-surfacing existing streets to protect the huge investment we’ve already made should always be the top priority. Sadly, this kind of routine maintenance takes a back seat to politically sexier proposals to expand capacity. We need an ironclad “fix it first” philosophy. Also, we need to guard against “scope creep” in maintenance. There’s a tendency, once a “repair” project gets moving, to opt for the most expensive solution (see bridges: Sellwood, Columbia River Crossing). That’s great if your project gets funded, but a few gold-plated replacements drain money that could produce much more benefit if spread widely.  We need to insist on lean, cost-effective maintenance.

5. Don’t play “bait and switch” by bonding revenue to pay for shiny, big projects. There’s an unfortunate and growing tendency for those in the transportation world to play bait-and-switch with maintenance needs. They’ll tell us about the big maintenance backlog to justify tax and fee increases. Then they bond two or three decades worth of future revenue to pay for a shiny new project; the Sellwood Bridge and the local share of the Portland-Milwaukie light rail have been funded largely by tying up the increase in state gas tax revenue,vehicle registration fees, and flexible federal funds for the next two decades. The state, which routinely financed construction on a pay-as-you-go basis, has also maxed out its credit card: in 2002 ODOT spent less than 2% of its state revenue on debt service; today, it spends 35%. Now it is pleading poverty on highway maintenance. Politically, this makes a huge amount of sense.  You get to build the projects today, and pass the costs into the future. Unfortunately, in practice it leads to a few gold-plated projects now, while jeopardizing the financial viability of the transportation system in the long run.

6. Promote fairness through the “user pays” principle. We all want the system to be “fair.” In the case of general taxes, we often put a priority on progressivity—that taxes ought to be geared toward ability to pay. But for something like transportation (as with water rates, sewer rates, or parking meter charges), fairness is best achieved by tying the cost to the amount of use, or what economists call the “benefit principle.” Charges tied to use are fair for two important reasons: higher income people tend to use (in this case, drive) more than others, and therefore will end up paying more. Also, charges tied to use enable people to lower the amount they pay by changing their behavior.

7. Don’t buy the phony safety card. We’ll hear all about the need to spend money to make our streets safer. The safety argument is an all-purpose smokescreen to justify almost any expenditure, no matter how distantly related to safety. (Ostensibly, the $3.5 billion Columbia River Crossing project was justified as a “safety” project, even though the I-5 bridge had a lower crash rate than the Fremont Bridge). Here’s the key fact of street safety: Smaller, slower streets are safer. Metro’s region-wide analysis of crash data showed that fast-moving, multi-lane arterials are by far the most dangerous streets in the region for cars, cyclists, and pedestrians . The more we get people out of cars, the more crashes and injuries decline. The most effective thing we can do to improve safety turns out to be the cheapest: implement features that slow and calm traffic, and make walking, cycling, and transit more attractive.

Correction:  Commissioner Steve Novick points out correctly  that his proposal contains a specific list of laudable safety projects that he proposes undertaking with street fee proceeds if his proposal is adopted.  These projects don’t fall into the “phony safety” category outlined above.  My apologies if this commentary implied otherwise.  Still, voters should consider two other things.  First, while the proposed list is a good one, it is “preliminary and subject to change” and isn’t binding on future city commissions, and the “safety” category is an elastic one.  Safety projects are defined as those that “reduce the likelihood of a person being killed or injured and address the perception of risk.”  Second, transportation money is very fungible.  Its always possible to re-arrange the budget to tell someone that this “new” money is only being used for good purposes.   The larger question is the overall priorities for the entire transportation budget.  If safety spending out of current revenues is reduced, the net gain could be less than advertised.(Revised, 10.20 PM January 8).

8. Don’t write off the gas tax yet. There’s a widely repeated shibboleth that more fuel-efficient vehicles have made the gas tax obsolete. Despite its shortcomings as a revenue source—chiefly that it bears no relationship to the time of day or roadway that drivers use—there’s nothing wrong with the gas tax as a way to finance street maintenance that a higher tax rate wouldn’t solve. While other methods like a vehicle-miles-traveled fee make a lot of sense, the reason they’re popular with the transportation crowd is because they would be set high enough to raise more money. And there’s the rub: people are opposed to the gas tax not because of what is taxed, but because of how much they have to pay. As an incremental solution to our maintenance funding shortfall, there’s a lot to like about a higher gas tax: it requires no new administrative structure, it’s crudely proportionate to use, and it provides some incentives for better use of streets. So when very serious people gravely intone that the gas tax is “obsolete” or “politically impossible”—you should know what they’re really saying is that people simply don’t want to pay more for streets.

Transportation and urban livability are closely intertwined. Over the past few decades it has become apparent that building our cities to cater to the needs of car traffic have produced lower levels of livability. There are good reasons to believe that throwing more money at the existing system of building and operating streets will do little to make city life better. How we choose to pay for our street system can play an important role in shaping the future of our city. As Portlanders weigh the different proposals for a street fee in the coming months, they should keep that thought at the top of their minds.

City Report: Lost in Place

Posted on by Joe Cortright

Here’s a summary of our latest CityReport: Lost in Place: Why the persistence and spread of concentrated poverty–not gentrification–is our biggest urban challenge.

Lost in Place traces the history of high poverty neighborhoods in large US cities, and constructs a new view of the process of neighborhood change.  This article summarizes some of our key findings.  A complete guide to our report, including a PDF of the report narrative, sortable tables of metro area data and links to our neighborhood level maps are available here.

We were drawn to examine this question because of the concerns that are frequently raised suggesting that efforts to promote urban revitalization have the unintended negative consequence of making life worse for the urban poor. The argument is made that improving a neighborhood simply results in one population (wealthier, whiter) moving in and the existing residents (poorer persons of color) moving out, with the result that the poor are worse off than they were had no revitalization occurred. There are some well-known examples of places that are now very high income–like Chelsea in Manhattan–which were once poor neighborhoods.

But the question is seldom asked: How representative are these instances? And how prominently do they figure shaping the overall pattern and prevalence of urban poverty?

The term gentrification itself is fraught with discord. It is widely used and seldom precisely defined. In this study, we’ve set out to shed some light on the question by focusing on a single index of neighborhood well-being: the poverty rate. Despite its flaws, the poverty rate is a good marker of a neighborhood’s relative economic status over time. Moreover, critiques of gentrification flag its harm to the poor, so logically, we should find the most dramatic effects of gentrification in high poverty neighborhoods.

There are very good reasons we ought to be concerned about the plight of those living in high poverty neighborhoods. A growing body of social science research confirms that concentrated poverty magnifies all of the pathologies associated with poverty. Most troubling, new research shows that these effects make a major contribution to the intergenerational transmission of poverty: children growing up in neighborhoods of high poverty have permanently impaired life chances compared to otherwise identical children growing up in neighborhoods with low poverty.

Our data show that while striking when it happens, instances of gentrification of previously high-poverty neighborhoods are quite rare. Only about 5 percent of the poor living in urban high-poverty neighborhoods in 1970 would have found that their neighborhood saw its poverty rate decline to less than the national average four decades later.

Three-quarters of high-poverty neighborhoods were still places of high poverty four decades later. But they were far from stable; on average these chronically-poor neighborhoods lost 40 percent of their population over four decades. High-poverty neighborhoods are not stable or sustainable; they are in a steady process of decay. It’s an illusion to suggest that in the absence of gentrification, a poor neighborhood will remain the same.

Infographic

If we’re concerned about the poor and about concentrated poverty, our attention should be riveted to a much larger and more ominous trend: the growth of new neighborhoods of high poverty. Between 1970 and 2010, the number of urban neighborhoods with poverty rates exceeding 30 percent nearly tripled, to 3,100, and the number of poor persons living in these neighborhoods doubled from 2 million to 4 million.

A majority of these newly-poor neighborhoods were places that in 1970 had poverty rates below the national average–places we call “falling stars.” They were arguably middle class 40 years ago, and today are neighborhoods of high poverty.

The sheer scale of the spread of concentrated poverty emphasizes how modest the effect of gentrification has been on the location of the poor. The number of poor living in high-poverty neighborhoods that rebounded since 1970 declined by about 67,000. This is a good maximum estimate of the “displacement” associated with gentrification. Over the same time, the number of poor persons living in newly poor neighborhoods increased by 1,250,000. This suggests that at most, the relocation of the poor attributable to gentrification accounts for perhaps five percent of the increase of population living in concentrated poverty.

We’re coming to understand that place plays a big role in shaping economic opportunity. How we build our cities–and whether we allow concentrated poverty to persist and spread–will have a profound impact on whether future generations will continue to share the American dream.


For more information regarding economic opportunity, economic segregation, and concentrated poverty, go here, and to see the full report including metro-level dashboards and maps, go here.

City Report: America’s Most Diverse, Mixed Income Neighborhoods

Posted on by Joe Cortright

Today we’re releasing our latest CityReport: America’s Most Diverse, Mixed Income Neighborhoods.

In this report, we use Census data to identify those neighborhoods that have the highest levels of both racial/ethnic and income diversity among all urban neighborhoods in the US.

We were motivated to take on this analysis, in part, because so much attention is focused on the cleavages and segregation of American cities. There’s little question that we’ve become increasingly divided by income, and that racial and ethnic segregation still underpin the persistence of poverty and the lack of opportunity for too many Americans.  And while our country is divided in many ways, we thought it would be helpful to look at those places where our growing diversity was reflected in a neighborhood that was occupied by households of every economic strata.

That’s what this report does:  we look at the places that have the highest levels of racial/ethnic diversity, measured by the likelihood that any two randomly selected neighborhood residents would be from two different racial/ethnic groups (white, black, Latino, Asian or other).  We constructed a parallel measure of income diversity based on the representation of five different household income groups in a neighborhood.  In both cases, we identified the neighborhoods that are in the top twenty percent of all urban US neighborhoods based on each of our measures of diversity.

Our core finding is that there are more than 1,300 such neighborhoods in the US that are home to nearly 7 million Americans.  While about half of these neighborhoods are in just three large metro areas (New York, San Francisco and Los Angeles), nearly every large US metropolitan area has at least one neighborhood that is among the nation’s most diverse, mixed income neighborhoods.

One challenge we face in reporting our results is that the word diversity has become a colloquial euphemism for “people of color.” This report uses the word diversity in a more precise, mathematical context:  diverse means people of different racial and ethnic groups, not simply people of color.  A neighborhood that is 100% Asian or 100% Latino or 100% white or 100% black is not diverse.

Our interest in identifying diverse, mixed income neighborhoods is heightened by the growing body of social science research that shows the widespread negative effects of segregation for cities, for neighborhoods, for families and especially for children. The American Dream, that any child can grow up to achieve success, has been effectively denied to many of those who grow up in neighborhoods that are segregated, where children are cut off from resources and networks that lead to opportunity.

In a sense, these diverse mixed income neighborhoods may provide examples and insights about how we can fashion our cities to be more inclusive.

At least some of the neighborhoods we’ve identified as the most diverse, mixed income are those that are also frequently described as gentrifying. Gentrification is a hot topic in all three of the metro areas we count has having the most diverse, mixed income neighborhoods (New York, Los Angeles and San Francisco). Places like Bedford-Stuyvestant, San Francisco’s Mission District, and downtown Los Angeles all show up as being among the most racially and ethnically diverse, and mixed income of any metropolitan neighborhoods.

The big question, going forward, is whether rapidly changing gentrifying neighborhoods can maintain thise income and ethnic diversity, or whether they will inexorably transition to being all upper income and predominantly white. The available evidence suggests that there’s little likelihood of that happening. Of the neighborhoods that transitioned to multi-ethnic status between 1970 and 1990, fully 90 percent were still multi-ethnic in 2010.  In addition, what happens in these gentrifying neighborhoods is subject to public policy. Cities that use the increase in property values and attendant tax revenues from revitalization to help support affordable housing construction can help assure that gentrifying neighborhoods remain accessible to a wide range of income groups. In addition, how we invest in public space can create opportunities to build bridging social capital between new arrivals and long time residents.


For the full report, including metro level data and maps, visit our CityReport page here.