Amy Liu’s recent paper, “Remaking Economic Development,” is disruptive in that it rightfully undercuts the shaky foundation of what draws many practitioners to the field: the idea that success is simply structuring transactions to attract new jobs and investment. These two metrics alone can’t diagnose the economic health or trajectory of a community. Instead, as the paper outlines, setting the right goals—measured by growth, prosperity, and inclusion—provides a much richer framework for a community’s trajectory, vibrancy, and opportunity.

Goal-setting clarifies how a community defines success and when it has been achieved, and promotes collaboration and increases buy-in from diverse stakeholders. If, as Liu argues, goals were designed to lead to growth, prosperity, and inclusion, metro areas would make dramatically different choices around policies, investments, and priorities, and people and communities would likely be in an overall stronger economic position.

However, these goals represent a longer-term proposition than conventional measures, and, perhaps naively, “Remaking Economic Development” fails to acknowledge the barriers that prevent most communities from setting the right goals:

1. Goals should focus on long-term interests, but election cycles prioritize clear near-term political wins. Meaty investments in infrastructure, workforce development, and fiscal policy reform needed to shift the competitive position of a community rarely yield easily defined and clearly increased short-term political capital.
2. Economies function as regions, but many municipal strategies are not aligned with regional goals. A metropolitan area is the logical unit to measure success, but civic leaders are elected from individual municipalities, or from a state that has a larger focus. Although it’s easier to market a region of 5 million people than a city of 650,000, in Detroit, intramural competition between cities and suburbs, suburbs and suburbs, and even neighborhoods within the city all undermine the cooperative effort to set goals regionally. The failure of mayors within a region to recognize their economic connectedness is a huge problem and fuels wasteful incentive battles over retail and other projects that are not economic drivers.
3. Goal-setting takes time, money, and requires data, but capacity is in short supply. Most economic developers and political leaders lack the framework, experience, and manpower to effectively lead a goal-setting process. And if the choice is between collectively setting goals or managing a flurry of “bird-in-hand” transactions, the transaction under consideration will always receive resources first. Leaders are primarily evaluated on near term jobs and investment figures; not having the time to lead a goal-setting process and, in many cases, lacking the approach and datasets to appropriately undertake this activity make goal-setting easy to eliminate.

Despite these obstacles, setting the right goals is critical to building healthy communities. To combat political challenges, strong collaboration between business and public sector leadership is crucial, as is the recognition of diverse sub-economies with different value propositions and opportunities. Leaders must ultimately acknowledge that near term wins mean little if they are leading down a path that will not fundamentally address the long-term investment climate and the region’s productive capacities, grow wages or address employment levels, and offer broad opportunities for diverse economic participation. The following steps can help:

1. Harness diverse, cross-sectoral perspectives. Fundamentally, businesses understand their industries better than anyone else; hence the public sector should identify ways to encourage growth, increased productivity, greater inclusion, and more competitiveness in targeted sectors by listening to businesses and jointly setting goals that marry private sector profit and public economic and social interests effectively. This approach may offset some of the other realities of short election cycles and limited capacity to participate in goal-setting or planning processes.
2. Identify unique roles for communities within a larger regional framework. Although competition between local cities may inhibit the most meaningful dialogue and alignment of interests, deeper analysis often produces greater clarity on the niche opportunities for different communities. For example, although Detroit has a strong manufacturing base, a major project requiring more than 40 acres will likely have better site options in the suburbs. In the same vein, companies seeking a vibrant urban campus with easy access to food, living, and other amenities are likely better suited to Detroit than one of the surrounding communities. That said, both companies are likely to draw employees from communities all over the region. Effective goal-setting includes analysis that should allow municipalities to uncover their niche opportunities within a larger regional framework.
3. Balance short-term and long-term priorities and successes. The truth is that near term investments are vital in creating momentum, providing stability, and creating jobs while long-term investments, policy decisions, and industry-focused asset development fundamentally position an economy to win over time. For example, incentives play an important role in offsetting competitive disadvantages in the short-term and should be used as a way to fill the gap while a community fixes the bigger economic challenges, ranging from exorbitant development costs to workforce development issues. The disconnect is that many communities are not focusing incentives on strategic, long-term priorities.

"Remaking Economic Development” elegantly exposes the shortsightedness toward aggressive deal-making that often prevents communities from thoughtfully building their long-term economic strength with an eye on growth, prosperity, and inclusion. Sadly, the economic development profession has historically focused on growth without much attention to prosperity and inclusion, which are arguably most important in building a sustainable economy. Goal-setting—painful as it may be—is the first step towards remaking the practice and establishing an honest foundation to build a better economy in the future.

      

 

 

The death and massive displacement that Hurricane Katrina and subsequent levee failures caused in New Orleans 10 years ago caused many Americans at the time to ask: How could this happen? How could so many vulnerable residents—especially low-income African Americans in poor health—be left behind in the devastation?

At the time, my colleague Bruce Katz and I suggested one contributing factor: “a long-standing policy of neglect toward the city’s most vulnerable residents, exemplified by their continued segregation into neighborhoods of high poverty.”

Our analysis in 2005 found that among the 50 largest cities in the United States, New Orleans before the storm had the second-highest share (behind only Fresno) of its poor residents living in neighborhoods of extreme poverty, where more than 40 percent of individuals had incomes below the poverty line. We suggested that, in addition to suffering long-term effects on their well-being from living in such neighborhoods, residents at the time of the storm may have been cut off from information about the scale of the impending disaster, from private transportation that could help them evacuate, and from social networks outside the city that could provide them shelter and assistance.

As the world turns its attention again to New Orleans 10 years after the storm and assesses its recovery, the city’s—and region’s—geography of poverty has shifted markedly.

As the Data Center observes in its recent post-Katrina look at the region, the poverty rate in the city of New Orleans in 2013 (27 percent) was statistically unchanged from 2000. The city had about 33,000 fewer poor individuals in 2013 than in 2000, but the drop in the city’s overall population left the poverty rate roughly the same.

Our analysis indicates, however, that the share of the city’s poor residents living in neighborhoods of extreme poverty dropped from 39 percent in 2000 to 30 percent in 2009-13 (the latest small-area data available). This drop occurred at the same time that concentrated poverty rose dramatically in many major American cities, spurred by the Great Recession and slow recovery. As a result, whereas New Orleans ranked second among big U.S. cities in concentrated poverty prior to the storm, it ranked just 40th by 2009-13 (see Appendix table).

To be sure, there still remain a great many very poor neighborhoods in New Orleans. In 2009-13, 38 of the city’s 173 census tracts had poverty rates exceeding 40 percent, down only slightly from 41 tracts in 2000 (see maps). Yet the population of those neighborhoods dropped dramatically, from more than 90,000 in 2000 to just over 50,000 in 2009-13. For many reasons, neighborhoods that were poorer before the storm have been much slower to rebuild and recover their previous population levels.

Poverty in New Orleans has not disappeared—far from it—but it has definitely scattered. As the city demolished its major public housing projects after the storm and replaced them with less-dense mixed-income housing, the number of households with housing choice vouchers tripled, as documented in a recent Data Center report. While voucher holders within the city of New Orleans tend to cluster in higher-poverty areas, many of those neighborhoods are not as poor as the public housing communities where many of the city’s low-income families used to live.

Meanwhile, poverty has also spread well outside the city’s borders. While the city’s poor population declined between 2000 and 2013, it rose by a nearly equivalent amount in the rest of the metropolitan area. And although the poverty rate in the rest of metro New Orleans has increased (from 13 percent to 16 percent), relatively few poor residents of those areas live in communities of extreme poverty, notwithstanding notable differences by race and ethnicity.

These data only begin to hint at the complicated movements of households and economic fluctuations that have influenced the extent and location of poverty in New Orleans, before and after Katrina. Yet as more cities and regions strive to increase their economic, social, and environmental resilience to future large-scale disasters, trends in concentrated poverty in New Orleans and other places bear continued scrutiny from policymakers and the public. 

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• Download data on concentrated poverty in major cities of the 100 largest U.S. metropolitan areas

      

 

 

EITC Interactive data from Tax Years 1997 to 2010 are available upon request by emailing NHolmes@brookings.edu.

To find past information on key characteristics of EITC-eligible taxpayers in your state or metropolitan area download archived profiles and read the profile user guide (PDF)

      

 

 

Our latest report on income inequality in cities finds that the gap between the rich and poor across the 50 largest cities continued to grow, albeit slightly, from 2012 to 2013. In general, both high- and low-income households made gains, but income growth at the top end outpaced that at the bottom end.

However, the cities in which either group made progress were, for the most part, different.

This was a little surprising. We thought that the cities in which wealthy households posted big gains might also see incomes improve the most for poorer households. Top-earning households would use their additional discretionary income to purchase more local goods and services that, in turn, employed lower-income workers—restaurants, landscapers, house cleaners, child care providers, etc.

That's one logical implication from Enrico Moretti's book, The New Geography of Jobs, which my colleague Mark Muro wrote about here a couple years back. Moretti finds that the most innovative, tech-focused regional economies actually generate more jobs and higher incomes for less-skilled workers than other regions. So at least in terms of employment and earnings opportunities, it's better to be a poorer household in Silicon Valley than in, say, Milwaukee.

This year's data, though, throw a little cold water on that theory. Of the 50 cities we examined, 12 saw incomes rise by a significant margin at the top, and 11 saw incomes rise by a significant margin at the bottom. But only two cities made both lists (Jacksonville and Houston). In New York, Dallas, Seattle, and San Jose, Calif., big gains among high-income households were accompanied by almost no change among low-income households. At the same time, poorer residents of Kansas City, Mo., Nashville, Tenn., Oklahoma City, and—yes—Milwaukee posted gains absent much movement near the top.

A slightly longer view, from before the Great Recession up to 2013, tells a similar story.  On average, low-income households lost ground across the board, regardless of how high-income households fared. Their losses were slightly less steep in cities where high-income households weathered the recession best, and steeper in cities where the wealthy got hit hardest. For the most part, however, incomes at the top and bottom of the distribution in these cities moved somewhat independently.

These small data points don’t refute the underlying theory. Our data are just for cities, not the wider metro areas across which these economic dynamics truly operate. And there are examples such as San Francisco, where very dramatic (albeit not quite statistically significant) income gains for top earners in 2013 coincided with real gains at the bottom, too. Of course, we don't actually know whether the gains at the bottom reflected actual improvement for San Francisco's poorer households, or if instead poorer households were simply displaced from the city due to rising housing costs (it's probably some of both).

Regardless, the fact that where the rich are getting richer, the poor are often not, presents a challenge for local policymakers aiming to boost social mobility for their lower-income workers and families. In the short run, at least, rising prosperity at the top in a city won’t reliably trickle down to the bottom.

      

 

 

Proximity to employment can influence a range of economic and social outcomes, from local fiscal health to the employment prospects of residents, particularly low-income and minority workers. An analysis of private-sector employment and demographic data at the census tract level reveals that:

Between 2000 and 2012, the number of jobs within the typical commute distance for residents in a major metro area fell by 7 percent. Of the nation’s 96 largest metro areas, in only 29—many in the South and West, including McAllen, Texas, Bakersfield, Calif., Raleigh, N.C., and Baton Rouge, La.—did the number of jobs within a typical commute distance for the average resident increase. Each of these 29 metro areas also experienced net job gains between 2000 and 2012.

As employment suburbanized, the number of jobs near both the typical city and suburban resident fell. Suburban residents saw the number of jobs within a typical commute distance drop by 7 percent, more than twice the decline experienced by the typical city resident (3 percent). In all, 32.7 million city residents lived in neighborhoods with declining proximity to jobs compared to 59.4 million suburban residents.

As poor and minority residents shifted toward suburbs in the 2000s, their proximity to jobs fell more than for non-poor and white residents. The number of jobs near the typical Hispanic (-17 percent) and black (-14 percent) resident in major metro areas declined much more steeply than for white (-6 percent) residents, a pattern repeated for the typical poor (-17 percent) versus non-poor (-6 percent) resident.

Residents of high-poverty and majority-minority neighborhoods experienced particularly pronounced declines in job proximity. Overall, 61 percent of high-poverty tracts (with poverty rates above 20 percent) and 55 percent of majority-minority neighborhoods experienced declines in job proximity between 2000 and 2012. A growing number of these tracts are in suburbs, where nearby jobs for the residents of these neighborhoods dropped at a much faster pace than for the typical suburban resident (17 and 16 percent, respectively, versus 7 percent).

For local and regional leaders working to grow their economies in ways that promote opportunity and upward mobility for all residents, these findings underscore the importance of understanding how regional economic and demographic trends intersect at the local level to shape access to employment opportunities, particularly for disadvantaged populations and neighborhoods. And they point to the need for more integrated and collaborative regional strategies around economic development, housing, transportation, and workforce decisions that take job proximity into account.

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In September we reported that suburbs in our nation’s largest metro areas had seen their poor population grow by 66 percent since 2000, making them home to the largest and fastest growing poor population in the country.

However, the past year also offered important lessons about effective approaches to the new geography of poverty. Through a series of briefs, practitioners from across the country shared their firsthand perspectives on the innovative models they helped to launch to confront the rise of suburban poverty in their regions. In some ways, each of the four models described in these briefs is unique. They come from different parts of the country and tackle different facets of the complex issues suburbs face in the context of growing poverty:

• BRicK Partners’ Robin Snyderman and Beth Dever describe how, in the wake of the foreclosure crisis, hard-hit jurisdictions in Chicago’s west and south suburbs launched collaboratives to work together on mitigating the worst effects of the housing market collapse. As recovery has taken hold, these municipalities have continued collaborating to spur investment and development in their parts of the region.

• Mary Jean Ryan of the Community Center for Education Results writes about the Road Map Project—a collective impact model to improve education and employment outcomes for poor and minority students across seven school districts in South King County, WA.

• In Montgomery County, MD, Uma Ahluwalia, director of the county’s Health and Human Services Department, describes the Neighborhood Opportunity Network, a partnership between the county, area nonprofits, grassroots organizations and the faith-based community to strengthen community networks in rapidly changing neighborhoods and to connect residents in high-need areas to critical safety net supports.

• Finally, Joe Neri and Trinita Logue of IFF detail the evolution of their community development financial institution into a large-scale organization with an integrated continuum of services that has allowed it to successfully build human services and community development capacity in struggling suburbs.

Yet, from these varied perspectives, a striking number of common lessons learned emerge about the importance of:

• Data. These practitioners consistently use data to target limited resources and to measure their progress over time. The development of shared mapping and analytical tools has helped Chicago’s suburban collaboratives make transparent decisions about how to invest public and private dollars strategically, targeting high-priority projects rather than spreading dollars thinly across all jurisdictions. For the Road Map Project, setting agreed upon goals and interim benchmarks to improve student outcomes helped mobilize partners from the beginning and keeps them engaged and on track.

• Communication. Understanding data internally is not sufficient. Each practitioner points to the importance of clearly and regularly communicating—with partners, with community members and leaders, with funders—both to build consensus and to share early progress. Beyond tracking its impact through data, the Road Map Project routinely holds public events and briefings to share the results of its assessments with community partners and to spread best practices. Montgomery County treats community engagement and outreach as an iterative process, continually working to build trust and share information on important resources with community members.

• Assembling the right team. Each one of these models hinges on partnership and collaboration. Even a scaled and integrated organization like IFF regularly collaborates to build capacity in struggling suburbs and emphasizes the importance of identifying the right partners. As it helped build early childhood care and education capacity in the suburbs, IFF connected with local providers where possible and helped them to scale up their services to meet the growing need. In other cases, however, it helped local leaders partner with higher-capacity providers from outside the community.

• Building capacity. Successfully launching and sustaining these models first requires a solid organizational foundation. In the case of the Cook County collaboratives and the Road Map Project, building capacity meant establishing the coordinator or backbone organization. For the Neighborhood Opportunity Network it meant hiring community connectors. For IFF to increase its geographic reach and portfolio of services, the organization first had to invest in growing its own internal infrastructure and back office functions.

• Seed funding. In every instance, community foundation dollars helped catalyze these innovations, providing initial dollars that helped build the capacity necessary to launch or expand these models. Eventually, government, other philanthropic and private dollars followed.

      

 

 

The Great Recession created some of the toughest employment conditions that American workers experienced in the postwar period. The economy overall shed 8.7 million jobs in 2008 and 2009, and the unemployment rate reached a 25-year high of 10 percent in 2009. That year, more than 14 million Americans were looking for work but unable to find it, more than double the number before the recession started.

As Brookings’ Metro Monitor has demonstrated, however, the impacts of the recession have varied widely across the nation’s major metropolitan economies. This owes to several factors, including differing industrial specializations and house-price trends across metro areas, as my colleague Jonathan Rothwell has shown. In assessing the economic health of major metro areas, the Metro Monitor incorporates, among other indicators, BLS data on unemployment rates, which reflect that the vast majority of areas still have a higher unemployment rate than pre-recession.

However, the unemployment rate is an incomplete picture of the state of the labor market. That is because it only captures the share of individuals who are looking for work, but unable to find it. It thus leaves out a large number of Americans who, frustrated by the state of the job market, have decided not to look for work, or have given up doing so. Moreover, it focuses on all individuals age 16 and over in the labor market, which may include many younger and older people who are not in their prime working years.

That is why Federal Reserve Chair Janet Yellen, among many others, also looks at the prime-age labor force participation rate when assessing the health of the economy. That indicator measures the share of individuals aged 25 to 64 who are either employed or looking for work. The unemployment and labor force participation rates together offer a fuller picture of the national labor market situation.

Typically, data on labor force participation are available only for the United States as a whole, or sometimes for states. However, analysts can also use the Census Bureau’s American Community Survey to assess these dynamics in metropolitan areas on an annual basis. This analysis examines trends for the 100 largest metropolitan areas in their prime-age civilian employment-to-population ratio (here abbreviated as employment ratio) from 2007 to 2013. This ratio is calculated as the number of 25 to 64 year-olds who are working, divided by the total number of people in that age group. In this way, the employment ratio (ER) captures both the unemployment rate (UR) and the labor force participation rate (LFPR) for the population most likely to work, as ER = (1-UR)*LFPR. The 100 metro areas examined here are the largest by population in 2013. Of these 100, the Office of Management and Budget revised the boundaries of 29 between 2007 and 2013 so that the data measure slightly different geographies in each year, but these differences are not large enough to affect the results of this analysis (those metro areas are denoted in the linked appendix table). The analysis finds the following:

The overall employment ratio in major metro areas was lower in 2013 than in 2007.

In 2007, about 79 million of 106 million adults aged 25 to 64 in the nation’s 100 largest metro areas were working, equating to an employment ratio of 74.8 percent (Figure 1). This ratio dipped in 2010 to 72 percent, as 1 million fewer adults were working that year, even though their overall numbers had increased by nearly 3 million. By 2013, the employment level among 25 to 64 year-olds had rebounded to 82 million, but that still represented only 73.3 percent of the total population in that age range. As such, these metro areas in the aggregate fell short of their pre-recession employment ratio by 1.5 percentage points, or the equivalent of 1.6 million workers in 2013.

Figure 1. Prime-Age Employment Ratio (%), 100 Largest Metro Areas, 2007-2013

Employment-to-population ratio, civilian population aged 25 to 64. Source: Brookings analysis of American Community Survey data

Two-thirds of major metro areas had a lower prime-age employment ratio in 2013 than in 2007.

As Figure 1 illustrates, the 2007 to 2013 period captures periods of both steep downturn and slow recovery of the U.S. labor market. In the vast majority of metro areas (86 of 100), the employment ratio declined from 2007 to 2010. In half, the ratio then increased from 2010 to 2013 (50 of 100). Yet in most cases, that later increase failed to fully offset a steep initial drop.

Six years on, 65 metropolitan labor markets still posted lower employment ratios in 2013 for prime-age workers than before the Great Recession began (Figure 2). The steepest employment ratio declines, of 5 percent or more, occurred in mid-Florida metro areas and Sacramento, CA, all of which continued to suffer from the late-2000s housing crash. Las Vegas and Riverside exhibited similarly large declines. The other 35 metro areas managed to recover their pre-recession ratios. Metro areas in Texas, the upper Midwest, and the San Francisco Bay Area, among others, were part of this group.

Two Michigan metro areas posted the strongest employment ratio rebounds from 2010 to 2013.

After suffering above-average declines in employment due to the collapse of the auto industry, and manufacturing more generally, during the recession, Detroit and Grand Rapids posted the two largest increases in their prime-age employment ratios among the 100 major metro areas from 2010 to 2013 (Figure 2). They ended the period roughly where they started in 2007, thanks in part to the comeback of manufacturing in Michigan. Dayton and Louisville, two other metro areas with a significant manufacturing presence, also figured among those with the strongest employment ratio gains during that period. So did technology centers including Portland, OR, San Jose, San Francisco, and Austin, fueled by overall growth in that sector.

Figure 2. Change in Prime-Age Employment Ratio, 100 Largest Metro Areas, 2007 to 2013

Source: Brookings Institution analysis of American Community Survey data

Other metro areas made no real progress from 2010 to 2013, remaining largely stuck where they were in 2010. This was the case even in some places that suffered steep employment drops from 2007 to 2010, such as Deltona, FL, Greensboro, Las Vegas, and Scranton. Two metro areas that posted milder employment declines in the earlier period, Knoxville and Spokane, continued to backslide from 2010 to 2013.

Prime-age employment ratios varied widely across metro areas in 2013, from a low of 62 percent to a high of 81 percent.

Unemployment and labor force participation rates, which are typically calculated for the population age 16 and over, tend to vary across metro areas based in part on their age structure. Metro areas with many younger people who are still in school, or many older people who have exited the labor market, may exhibit higher unemployment or lower labor force participation. Yet even when one examines employment ratios for the same prime working-age population across metro areas, significant differences emerge.

In 2013, 19 percentage points separated employment ratios in the lowest-ranking metro area (Bakersfield, CA at 62.3 percent) and highest-ranking metro area (Madison, WI at 81.3 percent). Metro areas with relatively high ratios tended to have highly educated populations, like Madison, Washington, D.C., Raleigh, and Boston; and/or to have predominantly white populations, like Des Moines, Omaha, Salt Lake City, and Kansas City. Those with the lowest employment ratios included many agricultural regions in California and Florida, several of which experienced high unemployment fueled by the housing market crash (see below).

Most metro areas that had either very high or very low employment ratios in 2013 were in similar positions in 2007, suggesting that structural as well as cyclical factors influence metro employment outcomes. Nine of the 10 metro areas with the highest employment ratios in 2013 also ranked in the top 10 in 2007 (Boston moved from number 12 to number 7). Likewise, six of the bottom 10 metro areas in 2013 ranked as low in 2007.

Metro areas with steeper house price declines also experienced steeper employment ratio declines from 2007 to 2013.

The after-effects of the house price crash on metropolitan areas are apparent in their employment ratio trends. By the fourth quarter of 2013, according to data from the Federal Housing Finance Administration, house price indices in the 100 largest metro areas ranged from 4 percent above (Austin) to 48 percent below (Las Vegas) their levels from six years earlier. Not coincidentally, Austin had recovered its pre-recession employment ratio by 2013, while Las Vegas’ remained 4.3 percentage points short of its 2007 level.

Figure 3. Change in Employment Ratio by Change in House Price Index,

100 Largest Metro Areas, 2007-2013

Source: Brookings analysis of American Community Survey and Federal Housing Finance Administration data

There is a strong relationship between house price and employment ratio trends across the 100 largest metro areas (Figure 3). The 25 metro areas that experienced the smallest drops or actual increases in their house price indices from 2007 to 2013 registered an average employment ratio decline of only 0.7 percentage points during that period. By contrast, in the 25 metro areas where house price indices fell the most (by at least 26 percent) the employment ratio declined by an average of 3.4 percent. Thus, the pace of house price recovery in metro areas and the trajectory of their employment opportunity seemed to go hand in hand.

*             *             *

This snapshot of data from 2013 confirms that many places are still falling short of the employment opportunity they provided America’s workers before the Great Recession. And even among those places that have recovered, several engage well below-average shares of their adults in work today. These trends serve as reminders that five years into the recovery, much work remains to be done in metro America to achieve higher levels of employment and ensure the benefits of economic growth for all.

The author thanks Charlie Rafkin and Natalie Holmes for research assistance.

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• Employment Rate Top 100 101

      

 

 

Newly released Census Bureau data confirm that, four years into an official economic recovery, the nation’s largest metro areas continued to struggle with stubbornly high poverty levels even amid improving employment numbers. An analysis of the 2013 American Community Survey data on residents living below the federal poverty line (e.g., $23,834 for a family of four in 2013) reveals that:

Within these regions, the suburban poor population grew more than twice as fast as the urban poor population between 2000 and 2013 (66 percent versus 30 percent). By 2013, the suburbs accounted for 56 percent of the poor population in the nation’s largest metro areas, with the number of poor in suburbs outstripping the urban poor by 3.5 million.

Metro areas that experienced the fastest increases in their suburban poor populations during this time period exemplified the economic challenges facing the country during and before the Great Recession. They included Sun Belt regions hit hard by the collapse of the housing market, such as Austin, Atlanta, Cape Coral, Fla., and Las Vegas-Henderson. Suburban poverty also rose rapidly in Midwestern metro areas that had yet to fully recover from the 2001 downturn before the later, deeper recession set in, such as Grand Rapids, Mich., Indianapolis, and Milwaukee. (For detailed metro area data, see the Appendix.)

Percentage Change in the Suburban Poor Population

Source: Brookings Institution analysis of Census and American Community Survey data

Even as the recovery proceeded, most major metro areas did not see poverty fall significantly. Between 2012 and 2013, Colorado Springs was the only metro area that managed a statistically significant decline in its poor population. At the same time, six regions—Albany, Allentown, Pa., Seattle-Tacoma-Bellevue, Spokane, Wash., Winston-Salem, N.C., and Worcester, Mass.—registered a significant uptick in the number of residents living below the poverty line.

Of the 68 regions, six metro areas experienced significant declines in their city poverty rates in 2013. In three (Charleston, San Antonio, and San Francisco-Oakland-Hayward), the number of poor residents actually dropped. In Allentown, Pa. and Chattanooga, Tenn., however, the poor population and the city poverty rate rose.

Among individual metro areas, only two experienced significant declines in their suburban poverty rates (Deltona, Fla. and Riverside-San Bernardino-Ontario, Calif.), and in only one (Riverside-San Bernardino-Ontario) did the total number of suburban residents living in poverty fall from 2012 to 2013. At the same time, poverty rates rose in the suburbs of Albany and Charleston, and poor populations grew in those two suburban areas and three others—Seattle-Tacoma-Bellevue, Winston-Salem, N.C., and Worcester, Mass.

Four years into the recovery, America’s metro areas—like the nation overall—had achieved only modest progress toward reducing poverty to its pre-recession levels. Where gains did occur, they tended to happen in big cities, further accelerating a long-term trend in the suburbanization of U.S. poverty and the challenges that accompany it.

A Note on Methods

With the release of the 2013 data, the Census Bureau adopted the 2013 metropolitan area statistical definitions as opposed to the 2009 delineations used in previous iterations of the ACS. These new definitions incorporate more recent data on population and commuting patterns that, in some cases, change the counties that make up a metro area.

To compare 2013 data with estimates from Census 2000, we compile county-level data from 2000 to match the 2013 delineations for the 100 largest metro areas. However, a similar approach is not always feasible for more recent estimates from the ACS (e.g., 2007). For metro areas that changed delineations in 2013, many contain counties with populations below 65,000, which means we cannot create comparable metropolitan level estimates using single-year estimates. Therefore, when analyzing trends between 2013 and earlier years of ACS data, we restrict the analysis to metro areas for which we can make “apples to apples” comparisons.

To identify primary cities we select the first named city in the official metropolitan statistical area title and any other city in the title with a population of 100,000 or more. The remainder of the metro area is treated as suburban. For three of the top 100 metro areas—Greenville, S.C.; Harrisburg, Pa.; and Northport, Fla.—the first-named city has a population of less than 65,000. Because estimates for these places are not available in the single-year ACS release, we exclude them for the city/suburban analysis. Thus, of the 100 largest metro areas, we can create comparable metro definitions and city/suburban estimates for 68 regions.

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• Appendix Tables

      

 

 

Downloads

• Appendix Tables

     

 

 

The new poverty plan unveiled last week by Rep. Paul Ryan has definitely sparked a conversation, generating a flurry of responses from positive to critical to somewhere in between (call it skeptical). By not engaging in a budget cutting exercise as in the past, Ryan has framed his proposals as an effort to start a conversation in Washington about real policy reforms to more effectively fight poverty and promote economic opportunity.

But for all of Rep. Ryan’s talk about the traveling he did over the past year to learn from people fighting poverty on the “front lines,” his new plan says very little about the importance of place in that fight. Whether it’s increasing access to opportunity or streamlining access to services, place matters.

For instance, one proposal that has garnered a great deal of interest is Ryan’s Opportunity Grant. Describing the program in a USA Today op-ed, he noted that, “The problem with all these federal [anti-poverty] programs is that they're fragmented and formulaic. They don't see how people's needs interact.” To overcome this problem, Ryan’s Opportunity Grant would begin as a pilot that would consolidate 11 federal programs into a single block grant. To participate, states would submit plans laying out how they would use those funds on people in need, “hold them accountable” through work requirements, offer choices of providers and track results.

Ryan’s Opportunity Grant tackles a very real problem.

In our work on suburban poverty, time and again we have seen communities trying to craft more scaled, integrated and outcome-driven solutions to confront growing suburban poverty, only to be stymied by a fragmented and inflexible federal anti-poverty policy framework. Not only has the system failed to respond to today’s shifting geography of poverty, it has often impeded more efficient and effective strategies to address poverty in struggling communities.

In some ways, Ryan’s Opportunity Grant pilot is similar to the Metropolitan Opportunity Challenge Alan Berube and I proposed in Confronting Suburban Poverty in America to address these challenges. Both proposals aim to provide greater flexibility and integration to federal funding streams and to use evaluation to figure out and build on what works. However, our Metropolitan Opportunity Challenge would require states to partner with metropolitan and local leaders to target funds strategically within and across regions in ways that measurably increase access to opportunity.

Because Ryan’s plan stops with states it misses the chance to ensure that reforms to the federal system translate into better implementation. It ignores the reality that access to opportunity varies depending on where you live. Different regional labor markets offer different types of jobs, and not all pay wages that offer a path out of poverty. Those jobs that do aren’t spread evenly across places, and may not be accessible to low-income workers who can’t afford to live nearby or maintain a reliable car to make a long commute. Even his proposal of an integrated caseworker and a one-stop-shop for services overlooks the fact that many communities, particularly in the suburbs and in rural areas, lack access to safety net services to begin with.

Many commentators have voiced concerns about the structure of the Opportunity Grant (including the pitfalls of block granting and the challenges of getting outcome measurement right) and about Ryan’s plan more broadly. Hopefully these are the opening salvos of a real debate in Washington about how to fight poverty more effectively in this country. But to make real strides in improving opportunity in America, that debate should be grounded in the understanding that place matters.

     

 

 

Today marks one year since the release of our book Confronting Suburban Poverty in America. Over the course of the last year, we’ve traveled to dozens of communities across the country to talk about the rapid rise of suburban poverty, a trend experienced by almost every major metro area in recent years, and what it means for residents, communities, policymakers, and practitioners grappling with the shifting geography of poverty. Here are our top five reflections from those travels:

1. Numbers are powerful, but only if they are known.

Local leaders and residents often don’t know the extent to which poverty has grown in their communities, or fully understand the complex challenges facing new arrivals and long-time suburban residents who make up the growing poor population. Fortunately, we have seen communities make significant strides by bringing together diverse stakeholders for conversations grounded in data and evidence. In November, Elizabeth participated in a Homeless Education Network summit that highlighted the increase in student homelessness in Pittsburgh’s suburbs. Media coverage of the event led a local YMCA to reach out to the suburban Penn Hills school district to explore ways they could work together to target services to the poor and homeless families in that community. Efforts like Navigating the New Normal in Minnesota are similarly helping to bridge the divide between research, perceptions, and on-the-ground realities.

2. Forget the cookie cutter.

The vocabulary we use to tell a national story—for instance, the word, “suburb”—often falls short of capturing the nuance of local identity and experience. In Houston or Phoenix, the landscape looks suburban well before you pass the city limits, and nearby communities may feel more like rural areas than suburbs. In contrast, a region like Boston may need a more nuanced framework to understand and guide policy decisions across older, densely populated small cities and towns that make up the metro area. This diversity within and across places carries a wider lesson for national practitioners, who succeed most when they partner with local and regional actors who understand the histories, identities, and varying levels of capacity that exist on the ground.

3. Small amounts of capital help build critical capacity.

In their new brief, Robin Snyderman and Beth Dever point to the importance of early investments from local philanthropy that allowed Chicago’s suburban collaboratives to boost their capacity by hiring dedicated coordinators. That staff capacity was critical to attracting and implementing federal funds. Whether it’s multi-jurisdictional collaboration, collective impact models around education (like the Road Map Project in Seattle) or community development (like Great Neighborhoods in Greater Boston), or expanding high-performing nonprofits into suburbs (like Mary’s Center in the National Capital region), local philanthropy is consistently critical for building capacity to confront the challenges of poverty in suburbs. As Robin and Beth point out, however, traditional government funding streams will be needed to sustain these models in the long run.

4. Growing jobs and fighting poverty are not separate initiatives.

While there is still a lot of work to be done to update perceptions, conversations shouldn’t just focus on the problem. Framing the discussion in terms of economic opportunity and regional competitiveness can help engage more partners—particularly the private sector—in efforts to improve outcomes for low-income people and places. In our recent visit to South King County, Washington, we learned about several promising initiatives underway to help communities struggling with rising poverty. Those conversations also revealed an appetite to leverage the sub-region’s assets to grow better jobs, and more strategically coordinate efforts to help prepare local populations for those opportunities.

5. Recovery did not hit the reset button.

The severity of the Great Recession caused policymakers and practitioners in many parts of the country to think differently about how to address shared challenges with limited resources. A few years into the recovery, the crisis has abated, but need remains high and resources haven’t rebounded. Some places are still experiencing rapid increases in their low-income population—like suburban Williamson County, Texas where more than 200 civic and nonprofit leaders recently gathered for a summit on the swift demographic and economic changes underway there. But for many other communities across the country, they are trying to adjust to a “new normal” and the reality that poverty in suburbia is here to stay. Without the urgency of a crisis, however, it can be harder to spur partners across sectors and jurisdictions to do things differently. To help communities catalyze and sustain action that improves outcomes for low-income residents over the long term, it is important as ever to align public and private funding to support more regional, cross-cutting anti-poverty strategies.

     

 

 

Seattle Mayor Ed Murray recently announced a plan to raise the minimum wage in his city to $15/hour over the next few years. The plan emerged from a special business/labor advisory committee, approved by 21 out of 24 its members, after four months of hearings, academic studies, and debate . The measure awaits approval by the City Council, but the move to $15/hour in Seattle seems well underway.

Seattle may be the first, but it won’t be the last, city to take this bold step. Granted, there were some peculiarities in Seattle’s case, including a $15/hour minimum wage ballot initiative that succeeded in the nearby city of SeaTac in November, and the election of a new Socialist Party Seattle City Council member who campaigned on the issue. But with inequality taking center stage as a political issue in big cities around the country, mayors, businesses, and labor advocates are watching Seattle closely.

However, the focus on big cities shouldn’t obscure the fact that wages are a function of regional economics. Seattle is indeed a big city, with 635,000 residents and (by our count) nearly 500,000 jobs. But it’s only part of King County, Washington, which has roughly 2 million residents and more than 1 million jobs. And King County is just one of three counties that make up the wider Seattle metropolitan area, with a population of 3.5 million and 1.8 million jobs.

While low-wage jobs are prevalent in Seattle, they’re even more prevalent in its nearby suburbs. Using data from the American Community Survey, my colleague Sid Kulkarni and I calculated that between 2009 and 2011, there were on average 149,000 jobs (full-time and part-time) in the city of Seattle that paid less than $15/hour. Over the same period, the remainder of King County had an average of 216,000 jobs that paid hourly wages below that threshold. These low-wage jobs represented 30 percent of all jobs in Seattle, and 34 percent of all jobs in the rest of King County.

It stands to reason that low-wage jobs are more suburban than high-wage jobs. Typically, the highest-value jobs in a region are located in central cities. High-paying sectors like finance, advanced health care, information technology (Redmond notwithstanding), and higher education tend to be more urban than suburban. Yes, cities also have lots of low-paying jobs in hospitality and retail, but so do suburbs. Those jobs tend to follow people, and most people in major metro areas live in suburbs. As my colleague Elizabeth Kneebone has found, as population sprawls, so does low-wage work.

To be sure, many people who live in the King County suburbs of Seattle will benefit from a $15/hour Seattle minimum wage, because they work in the city. According to a University of Washington study conducted for Mayor Murray’s Income Inequality Advisory Committee, fully four in 10 people who earn less than $15/hour working in Seattle jobs—and who would thus presumably benefit from the minimum wage increase—live outside of the city. That’s particularly important in a region like Greater Seattle, where suburbs are home to most of the poor. At the same time, the UW study finds that nearly as many Seattle residents in sub-$15/hour jobs work outside the city limits.

None of this amounts to an argument against Seattle taking the first step toward increasing its minimum wage. Residential and commercial demand is so strong in the city these days that Seattle may have more latitude than its suburbs to boost its minimum wage significantly without encountering negative employment effects. And maybe the city needs to move first in order to convince its neighbors (and itself) that a $15/hour minimum wage won’t make the sky fall.

But these statistics offer an important reminder that the problems of low wages, inequality, and social mobility do not stop at city borders. Ultimately, more cities might try acting in coordination with their surrounding jurisdictions, as the District of Columbia did with two Maryland counties, to boost their minimum wages and ameliorate any “border effects.” And as Seattle contemplates other key policy initiatives, like universal preschool and backfilling state cuts to transit funding (a King County ballot initiative failed last month), it should keep open the lines of communication with its neighbors, and act as one county—or region—where it can.

     

 

 

This year, 2014, is rife with 50-year retrospectives of the War on Poverty. More than just a round-number anniversary, the topic is attracting a lot of attention thanks to growing rates of poverty and inequality in America, as well as a nostalgia for a time when the federal government did “big things,” like establishing Medicare and the Food Stamp program. In today’s gridlocked Washington (and notwithstanding the Affordable Care Act), that seems like ancient history.

As we’ve noted previously, many of the retrospectives are simply an occasion for arguing about whether we “won” or “lost” the war. For all the economic struggles that millions of American families continue to face today, evidence clearly demonstrates that many of the anti-poverty policies and programs we’ve adopted over the past five decades have significantly materially improved the lives of lower-income people.

Yet the evidence seems more mixed when it comes to poor places. More than one in five big-city residents is poor. And of those poor residents, nearly one in four lives in a neighborhood of “extreme poverty,” where the poverty rate exceeds 40 percent. When community poverty rises to that level, it multiplies the negative consequences of individual poverty, and can mute the effectiveness of programs intended to help the poor.

This was the stark backdrop against which a collection of researchers (including me) and practitioners came together at the University of Southern California last month, to discuss “Innovating to End Urban Poverty.”

Yet as we know by now, poor people are not confined to urban areas. Neither are high levels of community poverty exclusively urban. The latest Census Bureau data indicate that fully one-quarter of poor individuals who live in extremely poor neighborhoods in the nation’s 100 largest metro areas are in suburbs. And suburbs account for four in ten poor individuals in those regions who live in areas of high poverty—a neighborhood poverty rate exceeding 20 percent. (We’ll be releasing a more detailed analysis of the latest data in the coming weeks.)

True to the name of the conference, however, the presenting researchers and practitioners advanced ideas and spoke about innovations that, for the most part, were rooted in poor city neighborhoods. To be sure, they advanced many cutting-edge practices, including helping parents navigate school choice options, re-engaging the previously incarcerated, expanding community-based health care, and using community organizing to give voice to politically under-represented groups. Yet these solutions are largely built on the infrastructure, expertise, and lessons borne of decades of work in low-income urban neighborhoods. School choice, for instance, isn’t really an option in most struggling suburbs. Political organizing is nascent at best.

Only one panel at the conference focused on “place” as a context for addressing poverty. A short paper I wrote for that panel argues that contemporary anti-poverty strategies must recognize the different needs of poor families in both cities and suburbs. The suburbs, for example, often lack the density to deliver services in a distinct area. Poor families often spread over greater distances in the suburbs, and they face different barriers (transportation, for example) than city dwellers do.

Moreover, as poverty spreads to the suburbs, it becomes less a neighborhood problem and more of a regional or sub-regional problem—affecting the south sides and suburbs of Atlanta, Chicago, and Seattle, or the east sides and suburbs of Cleveland, Pittsburgh, and Washington, D.C.

Investing our existing resources in organizations and strategies that are less tied to one particular place, and more collaborative in their execution, represents one important way forward. In Confronting Suburban Poverty in America, Elizabeth and I propose a Metropolitan Opportunity Challenge. The Challenge would reward regional and sub-regional strategies via competitive funding, create new forms of partnerships, and, above all, create more comprehensive networks to achieve scale and spread the most highly effective programs.

Angela Blanchard, CEO of Neighborhood Centers, Inc., represented this approach on the panel I participated in. That organization’s work throughout the Greater Houston area also captures well what Marge Turner, another panelist, termed in her paper “place-conscious” anti-poverty strategies—those that grapple with the important context that place creates in addressing the needs of low-income families, but are not circumscribed by the boundaries of those locales.

     

 

 

For low-income working families, the Earned Income Tax Credit (EITC) is one of the nation’s most effective tools for reducing inequality and alleviating poverty. However, as President Obama pointed out in his State of the Union address, “It doesn’t do enough for…workers who don’t have kids.” In fact, given the modest provision for childless workers (which begins to phase out at just 55 percent of full-time, minimum wage earnings), a childless worker making poverty-level wages would actually be taxed into poverty under current tax law.[1]

With the release of the president’s budget for fiscal year 2015, the administration provided details for how it would go about expanding the EITC to bolster the credit for workers without qualifying children.[2] The administration’s proposal joins others from officials in both the House of Representatives and the Senate aimed at strengthening the EITC for childless workers and, in turn, its work incentive and poverty alleviation effects. These proposals include Representative Richard Neal’s Earned Income Tax Credit Improvement and Simplification Act of 2013 and the Working Families Tax Relief Act of 2013 introduced by Senators Sherrod Brown and Richard Durbin.[3]

To better understand each of these proposals’ impact on low-wage workers at the state level and across the nation’s 100 largest metro areas, we used our MetroTax model to assess the effects of each expansion scenario, based on 2012 American Community Survey microdata and Tax Year 2012 tax law.[4] We found that:

• Each proposal would significantly strengthen the credit for millions of workers.
  
  
• At least 15 states would double the number of filers eligible for the childless worker credit.
  
  
• Every major metro area would see thousands of workers benefit from an expanded EITC.

Our findings illustrate that, beyond the potential national impact of these expansions, it is important for policymakers, advocates, and practitioners to understand how such an expansion would play out across and within states. For one, the EITC represents a significant federal investment in low-wage workers and the communities in which they live and, just as low-income families and workers are not spread evenly across the country, EITC filers (including those who would be affected by its expansion) are not evenly distributed across communities and states. In addition, changes to the federal credit also have implications for the many states and the handful of localities that operate complementary versions of the credit, as well as for advocates and practitioners involved in outreach and education efforts to help ensure eligible filers claim the credit at tax time. 

Two Proposals for Expanding the Earned Income Tax Credit for Workers without Qualifying Children

The administration proposal and the Brown-Durbin/Neal legislation (the House and Senate bills adopt the same expansion parameters) each address the EITC’s current shortcomings by targeting two key provisions of the credit for workers without qualifying children (Figure 1).[5] Specifically, these proposals would:

1. Expand the eligible age parameters. Under current law, non-parents and noncustodial parents must be at least 25 and under 65 years of age to qualify for the EITC. Each expansion proposal lowers the minimum age to 21, in order to encourage and reward work in the critical early stages of young adults’ careers. (However, each remains consistent with current law in that anyone eligible to be claimed as someone else’s qualifying child or dependent would not be eligible to claim the EITC themselves, including full-time students who are financially dependent on their parents.[6]) The president’s proposal also increases the upper age limit from 65 to 67, to harmonize the credit with increases in Social Security’s full retirement age.

2. Increase the maximum credit and phase in/out range. As currently structured, the EITC for workers without qualifying children phases in and out at 7.65 percent (or 7.65 cents per dollar of earnings), reaching a modest maximum credit (about $500 in Tax Year 2015). Both the administration proposal and the Brown-Durbin/Neal legislation would double the phase in/out rate to 15.3 percent to fully offset payroll taxes. Although the proposals adopt different income levels at which phase-in ends and at which phase-out begins, each would appreciably increase the maximum credit. The president’s proposal would double the maximum credit to about $1,000 in Tax Year 2015, while the Brown-Durbin proposal would set the maximum benefit to roughly $1,400 in that year.

Both Proposals Would Significantly Strengthen the Credit for Millions of Workers

Based on our MetroTax model analysis of 2012 census data, we estimate that the president’s proposal to expand the EITC would benefit a total of 14.1 million taxpayers—extending eligibility to about 6.6 million tax filers and increasing benefits for roughly 7.6 million filers already eligible for the EITC (Figure 2).[7] The Brown-Durbin/Neal congressional proposals would also boost the credit for 7.6 million currently eligible filers but, because they would reach higher up the income ladder (in addition to broadening the age parameters), they would also extend eligibility to an additional 7.6 million tax units for a combined impact of 15.2 million filers.

The filers benefiting from these expansions—who are most likely to work in industries such as retail, accommodation and food service, health care, educational services, and administrative services—would see a significant increase in the size of the typical credit for which they would qualify. The president’s proposal would invest an additional $6.5 billion in these workers, raising the average benefit from about $260 to almost $600. The Brown-Durbin/Neal legislation would make these filers eligible for up to an additional $8.8 billion, which would increase the average credit for these workers to $710.

At Least 15 States Would Double the Number of Filers Eligible for the Childless Worker Credit

While every state would benefit from an expansion to the EITC for workers without qualifying children, several states stand to more than double their number of taxpayers eligible for this portion of the credit. Under the administration’s proposal, 15 states could see the number of filers claiming the credit for childless workers increase by roughly 100 percent or more, and as many as 35 states could at least double their number of eligible workers if the Brown-Durbin/Neal legislation is enacted.

Many of the states that lead the list for increases under both scenarios—including Vermont, Rhode Island, North Dakota, and Iowa—already have a higher-than-average share of childless workers claiming the credit under current law. An expanded EITC for childless workers could raise the average credit to these filers by $340 or more, bringing millions of dollars in additional investment into each state. (For detailed state data, see Appendix A.)

Under either expansion scenario, 61 percent of the filers who would benefit from a stronger EITC for childless workers live in the nation’s 100 largest metro areas, ranging from over 16,000 filers in the Ogden, Utah metro area (under the president’s proposal) to as many as 696,000 in metropolitan New York (under the Brown-Durbin/Neal legislation).[8] (For detailed metro area data, see Appendix B.)

Within the 100 largest metro areas, both expansions would boost benefits for nearly 4.7 million filers who are currently eligible for the credit. At the same time, the administration proposal would expand eligibility to an additional 3.9 million filers, while the Brown-Durbin/Neal proposals would increase the eligible population by 4.6 million. These expansions would increase the EITC dollars potentially claimed in these regions by between $3.9 billion (under the president’s proposal) and $5.4 billion (under Brown-Durbin/Neal legislation), with metro areas like Albany, Milwaukee, Rochester, and Pittsburgh experiencing some of the biggest percentage changes in EITC dollars for childless workers. (See the map.) 

While every major metro area would benefit from an expanded childless worker credit, the list of metro areas that would experience the biggest uptick in average credit amounts is similar under each proposal. These metro areas represent a diverse mix of regions, including Augusta, Baton Rouge, El Paso, and Louisville in the South; Grand Rapids, Milwaukee, and Minneapolis-St. Paul in the Midwest; Albany and New Haven in the Northeast; and Salt Lake City in the West.

Conclusion

Whether policymakers adopt the president’s proposal or the reforms outlined in the Brown-Durbin/Neal bills, it is clear that strengthening these two key components of the credits—broadening the age range over which workers qualify for the credit and increasing the maximum credit and phase in/out rates—would significantly increase the EITC’s impact for millions of workers without qualifying children. Modernizing this provision of the EITC by enacting these expansions would help ensure that the credit is as effective a work incentive and poverty alleviation tool for childless workers as it continues to be for working families.

Downloads

• State and Metro Data Appendix

     

 

 

In December 2013, President Obama gave a speech on economic mobility, in which he called income inequality and lack of upward mobility “the defining challenge of our time.”

That challenge is front and center in America’s big cities today. Obama’s speech followed a series of municipal elections in November 2013 in which inequality figured prominently as a campaign issue. Foremost among these was in New York City, where Bill de Blasio won a landslide election after campaigning to address what he called a “Tale of Two Cities.” Similar themes were sounded in the successful campaigns and first days in office of Marty Walsh in Boston, Ed Murray in Seattle, and Betsy Hodges in Minneapolis. The “Google Bus” in San Francisco’s Mission District has shone a spotlight on growing economic divisions within that city. And income inequality will no doubt be a central issue in mayoral elections during the next couple of years in cities like Chicago and Washington, D.C.

Inequality may be the result of global economic forces, but it matters in a local sense. A city where the rich are very rich, and the poor very poor, is likely to face many difficulties. It may struggle to maintain mixed-income school environments that produce better outcomes for low-income kids. It may have too narrow a tax base from which to sustainably raise the revenues necessary for essential city services. And it may fail to produce housing and neighborhoods accessible to middle-class workers and families, so that those who move up or down the income ladder ultimately have no choice but to move out.

There are many ways of looking at inequality statistically; one useful way to measure it across places is by using the “95/20 ratio.” This figure represents the income at which a household earns more than 95 percent of all other households, divided by the income at which a household earns more than only 20 percent of all other households. In other words, it represents the distance between a household that just cracks the top 5 percent by income, and one that just falls into the bottom 20 percent. Over the past 35 years, members of the former group have generally experienced rising incomes, while those in the latter group have seen their incomes stagnate.

The latest U.S. Census Bureau data confirm that, overall, big cities remain more unequal places by income than the rest of the country. Across the 50 largest U.S. cities in 2012, the 95/20 ratio was 10.8, compared to 9.1 for the country as a whole. The higher level of inequality in big cities reflects that, compared to national averages, big-city rich households are somewhat richer ($196,000 versus $192,000), and big-city poor households are somewhat poorer ($18,100 versus $21,000).

However, some cities are much more unequal than others. The big cities with the highest 95/20 ratios in 2012 were Atlanta, San Francisco, Miami, and Boston. In each of these cities, a household at the 95th percentile of the income distribution earned at least 15 times the income of a household at the 20th percentile. In Atlanta, for instance, the richest 5 percent of households earned more than $280,000, while the poorest 20 percent earned less than $15,000. In another six cities (Washington, D.C., New York, Oakland, Chicago, Los Angeles, and Baltimore), the 95/20 ratio exceeded 12. Overall, 31 of the 50 largest U.S. cities exhibited a higher level of income inequality than the national average.

Nor are all unequal cities created equally. For example, compare San Francisco and Miami, which have similar 95/20 ratios. San Francisco’s ratio is high because its wealthy households have very high incomes, considerably higher than in any other major city ($353,000 at the 95th percentile). Miami’s ratio is high primarily because its poor households have very low incomes, third-lowest among the 50 largest cities ($10,000 at the 20th percentile). Miami has a lot of very poor residents and neighborhoods, but manages to retain several very wealthy enclaves. In San Francisco, skyrocketing housing costs may increasingly preclude low-income residents from living in the city altogether.

Compared to cities with high levels of inequality, cities with relatively low levels of income inequality are much more similar to one another. Most are Southern and Western cities with expansive borders, and either include many “suburban” neighborhoods alongside a traditional urban core, or are themselves overgrown suburbs like Mesa, Arizona and Arlington, Texas (what UNLV’s Rob Lang calls “boomburbs”). Upper-end incomes in these cities range from $150,000 to $200,000, while lower-end incomes mostly register between $19,000 and $24,000.

Growing debate about urban inequality suggests that the problem has gotten worse in recent years. But while inequality in cities is somewhat worse today than before the Great Recession, the trend is neither profound nor uniform. Overall, the 95/20 ratio across the 50 largest cities rose from 10.0 in 2007 to 10.8 in 2012. Not surprisingly, San Francisco experienced the largest increase in its ratio from 2007 to 2012. Income for its typical 20th-percentile household dropped $4,000 during that period, while income for its typical 95th-percentile household soared by $28,000. No other city saw nearly as large an increase in its rich households’ incomes.

Only 18 other cities among the top 50 registered statistically significant increases in their inequality ratios over those five years. Interestingly, most were not places where the rich made astronomical gains, but where low-income households suffered most from the recession and weak recovery. Many are Southern and Western cities—including Sacramento, Charlotte, Tucson, Fresno, and Albuquerque—where house-price collapses reduced work opportunities for poor households. Inequality was also up in places like Cleveland, Indianapolis, and Milwaukee, where poverty deepened as local manufacturing industries declined during the recession.  In those cities, however, inequality has not become a leading political issue.

Inequality increased across cities despite the fact that rich households were less rich in 2012 than in 2007. In most cities (39 of 50), 95th-percentile incomes declined over the five-year period. But 20th-percentile incomes were also down, in most cities by larger proportions than incomes at the top. For instance, rich households in Jacksonville in 2012 earned nearly $19,000 (11 percent) less than five years prior. At the same time, incomes among the city’s poor households dropped nearly $8,000 (31 percent). In Jacksonville and many other cities, inequality rose not because the rich got richer while the poor got poorer—but because the rich became somewhat poorer while the poor got much poorer.

Seattle, where the inequality debate has fueled calls for a $15/hour minimum wage, turns out to have a relatively low inequality ratio (31st out of 50 cities). This fact is largely attributable to the relatively high incomes earned by its 20th-percentile households—$26,000, third-highest among the 50 cities. Like San Francisco, Seattle may have less poverty not only because people there earn more, but also because the region’s poor increasingly live in suburbia. For its part, the Emerald City experienced no measurable increase in inequality from 2007 to 2012, indicating that either its low-income households held their own during the recession, or that there were just fewer places for them to live in the city by 2012. If the latter is true, it seems as though residents of south King County may need a minimum wage boost at least as much as their central-city neighbors.

Large populations, diverse housing types, and generally progressive politics mean that most cities will always have higher shares of the rich and poor than smaller places. But the contemporary causes and consequences of inequality in cities vary greatly across the national map. Mayors who want to promote both economic diversity and economic mobility in their cities should take note.

Downloads

• Appendix
• Data

     

 

 

At the end of January the House of Representatives passed a new $1 trillion five-year Farm Bill, by 251 votes to 166. The bill, which is now on its way to the Senate where it is expected to pass in a vote, cuts $8.6 billion from the Supplemental Nutrition Assistance Program (SNAP, formerly food stamps) over the next 10 years—significantly less than House Republicans had previously proposed, but more than Democrats had initially agreed to. The main provision of the bill changes aspects of the SNAP benefit calculation that would affect benefits for roughly 850,000 households, who would see an average decline in monthly benefits of $90 according to the Congressional Budget Office. However, benefit levels for more than 96 percent of the nation’s 48 million SNAP recipients would not be affected under this compromise. 

That’s good news, as SNAP recipients already saw their benefits cut in November following the expiration of the 2009 Recovery Act expansion to the program. As recent news coverage has highlighted, the families and individuals affected by those cuts are already some of the country’s most vulnerable. An overwhelmingly large percentage (87 percent) of SNAP recipients live in households with children, seniors, or people with disabilities. Upwards of 21 million children in the United States—more than one in four nationally—live in households receiving monthly food support through SNAP.

This past summer, we pointed out that SNAP recipients are increasingly likely to reside in suburban areas. Just as poverty has shifted decidedly toward suburbs over the last several years, so has the geography of households receiving food assistance. According to our analysis of the latest American Community Survey data, the number of suburban households receiving SNAP benefits grew by 116 percent from the start of the Great Recession in 2007 to 2012, compared to a 79 percent growth rate in the country’s largest cities. By 2012, 55 percent of SNAP households in the country’s largest metropolitan areas were located in the suburbs, up from 51 percent in 2007.

The recent release of the Census Bureau’s Supplemental Poverty Measure (SPM) underscores the importance and effectiveness of the SNAP program in alleviating poverty: Each year between 2009 and 2012, the SNAP program lifted an average of almost 4.8 million people above the poverty line. Of those 4.8 million, over 2.1 million were children. Every state benefitted from SNAP—from Texas, where nearly 470,000 individuals were lifted out of poverty per year by the program, to the District of Columbia, where the corresponding figure was 14,000.

There are many steps that local leaders can take to more effectively address today’s geography of poverty, as outlined in our recent book Confronting Suburban Poverty in America. However, these efforts on their own—absent a functioning federal safety net—would be insufficient to address the scope and scale of today’s need. Effective federal programs like SNAP provide an essential foundation that helps working families meet their basic needs, regardless of where they live. As poverty rates remain stubbornly high years after the official end of the Great Recession, that foundation remains critical to the economic stability of millions of struggling families across the country.

     

 

 

On the 50th anniversary of President Johnson’s War on Poverty, leading Republicans have been taking to the speaking circuit calling for new solutions.

"I would give us a failing grade," Rep. Paul Ryan (R-Wis.), chairman of the House Budget Committee, told NBC News at an event last week. “It has failed. We should've done better than this. We can do better than this."

Speaking at Brookings this week at a summit on social mobility, Ryan said federal antipoverty programs take a “haphazard, Whack-a-Mole approach… because the federal government created different programs to solve different problems at different times.” He continued, “There is little to no coordination among them.”

Ryan, who’s been traveling to low-income neighborhoods across the country for the past year to talk to local leaders, called for a more streamlined approach that allows for leadership from community members and the poor themselves. “Washington does not have all the answers,” Ryan told the crowd at Brookings. “Only the people in the community can solve the problems facing their community.”

On his travels, Ryan may have seen that the landscape of poverty has changed a great deal since President Johnson was in office. For one thing, it has moved increasingly into the suburbs outside of cities like Milwaukee and Madison, not far from Ryan’s Wisconsin hometown of Janesville. More poor people now call the suburbs home than cities.

Yet federal programs designed to fight poverty two generations ago have not kept pace. Many suburbs have yet to build the civic infrastructure that cities have to help low-income families. Poverty in the suburbs often spreads across a larger geographic area than in cities, covering multiple jurisdictions that aren’t accustomed to working together. Federal antipoverty funding doesn’t do much to help spread necessary infrastructure, and presents obstacles to collaboration among providers and local governments.

Ryan’s remarks focused primarily on how people-based programs—like Medicaid, food stamps, and child care subsidies—could be blended to enhance coordination and remove work disincentives associated with program phase-outs. But that logic applies at least equally to place-based programs, such as those for affordable housing development, community health care, and low-income schools. Instead of giving small amounts of money to many fragmented on-the-ground actors, we can stretch limited federal investment further by encouraging greater collaboration and integrated problem solving at the state and metropolitan levels.

Ryan warned against policymakers who “sit in our think tanks in Washington and say, ‘Oh we’ve got the answer. It’s this program. It’s money here and money there.’” That being said, he might be pleased to read some of the case studies on our website and in Confronting Suburban Poverty in America. “Let’s talk to the people who are actually fighting poverty successfully,” Ryan told Brian Williams, “and see what we can do to support people there.”

We’ve talked to local leaders around the country, and it’s clear that we should invest more in organizations that are able to confront both urban and suburban poverty at scale. Greater Houston’s Neighborhood Centers is blending more than 30 federal government funding streams to serve clients at more than 60 sites across the region. IFF (formerly Illinois Facilities Fund) is providing crucial research and lending services to regions across the Midwest to help develop needed services like affordable and supportive housing in their communities. Those are bottom-up models worth spreading.

They are also one step ahead of Senator Marco Rubio (R-Fla.) who, in a speech last week, called for turning federal antipoverty funding over to the states in the form of a “Flex Fund”—block grants that would presumably combine all manner of people- and place-based antipoverty programs.

That’s a bridge too far. Federal programs like food stamps, Medicaid, and the EITC are effective (something that those who deem the War on Poverty a “failure” conveniently ignore) precisely because they work harder when poverty rises, something block grants don’t do. But some incremental steps in Rubio’s direction would undoubtedly help. Our proposed Metropolitan Opportunity Challenge would repurpose a fraction of existing place-based federal antipoverty funding to enable more regional solutions to poverty. The challenge would award resources to states though a competitive process, encouraging state and local governments to organize programs and delivery systems in creative ways that focus on real outcomes for people and places.

“It’s wrong for Washington to tell Tallahassee what programs are right for the people of Florida,” Rubio said. “But it’s particularly wrong for it to say that what’s right for Tallahassee is the same thing that’s right for Topeka and Sacramento and Detroit and Manhattan and every other town, city, and state in the country.”

The rise of suburban poverty adds relevance and urgency to Rubio’s and Ryan’s calls for greater local autonomy in the next War on Poverty. Far short of dismantling the federal safety net altogether, though, there are smart, bipartisan moves we can make right now that build on local successes in addressing the new landscape of poverty.

     

 

 

Fifty years after President Johnson called for an expanded minimum wage in his State of the Union speech that launched the War on Poverty, the nation is once again debating the merits of a minimum wage hike.

This is timely, if not overdue, as today’s federal minimum wage of $7.25 an hour is effectively $2.15 lower than it was in 1964, after adjusting for inflation. (Many states today do have minimum wages above the federal level.)

More than that, however, the profile of minimum wage workers has shifted dramatically in the last few decades. Rather than teens working after school or summer jobs, according to the Economic Policy Institute, the typical worker likely to be affected by a raise in the minimum wage today is a woman in her 30s working full-time, with a family to support.

And like most Americans, minimum wage workers are suburbanites.

They include parents like Shawndrakae Mack, a single mom of two teenagers who works at the McDonald’s on Edisto Island, a suburban beach community near Charleston, South Carolina, and earns $7.60 per hour. Mack told the Charleston Post and Courier that she relies on food stamps and Medicaid to supplement her income and has trouble affording the athletic equipment her kids need for school. 

Or they are workers like Semaj Ransom, 39, who was hired in February at Jack in the Box in the Bay Area suburb of Hayward, California, for a full-time position at $8.50 an hour. But, he says, he rarely gets a full schedule. Ransom told the San Jose Mercury News his hours fluctuate drastically week-to-week, “so you can't even save."

Like Mack and Ransom, roughly one in four workers living in the suburbs works in a low-wage occupation (i.e., an occupation where at least 25 percent of workers make less than $10 an hour). Many are employed in retail, restaurant, and other low-wage service jobs. In fact, according to our colleague Jane Williams’ analysis of American Community Survey data, suburbs are home to two-thirds of all workers employed in such jobs in the nation’s largest metro areas.  

Given that suburbs are where the bulk of low-wage work and workers are found, Alan Berube recently observed that “it stands to reason that measures to boost their wages, like minimum wage and living wage campaigns, could be important tools for addressing the economic hardships facing suburban workers and communities.”

Some argue that raising the minimum wage beyond $10 an hour will be a job killer. Others worry that a higher minimum wage could push up prices or create “border wars” with neighboring locales that keep wages low to attract businesses.

But as the Washington Post recently reported, new research from Arindrajit Dube at the University of Massachusetts-Amherst concludes that increasing the minimum wage would reduce poverty, without detectable impacts on employment.

Workers in suburban SeaTac in Washington State, where voters approved a raise in the minimum wage to $15 an hour, are certainly pleased. Many families say this measure will enable them to put healthier food on the table, afford car repairs or save for an emergency fund. (A recent court ruling, however, said that SeaTac voters do not have the authority to raise wages for SeaTac airport workers, who operate under the auspices of the local port authority.)

But as Alan pointed out, piecemeal efforts like SeaTac’s are not a long-term solution. Creative responses and jurisdictional collaboration are necessary to combat these new challenges and address suburban poverty at scale. That is also true for the minimum wage.

Washington, D.C., is a case in point. Local leaders there created a regional pact to all raise the minimum wage. The city council voted to increase the city's minimum wage in stages to $11.50, and the adjoining Maryland suburban counties of Montgomery and Prince George also voted to raise their minimum wages to $11.50.

Suburbs should be allies for larger policy efforts to raise minimum wages at the national and state levels. Five decades on from President Johnson’s speech, President Obama is likely to call for a federal minimum wage increase in his State of the Union address later this month. For the many suburban families who are working hard and struggling to survive on meager wages, those increases couldn’t come soon enough.