At a legislative conference in Cambridge, Ohio, Bruce Katz stressed the importance of cities and metro areas to the state's overall prosperity. Acknowledging the decline of Ohio's older industrial cities, Katz noted the area's many assets and argued for a focus on innovation, human capital, infrastructure, and quality communities as means to revitalize the region. 

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The Center for Neighborhood Technology, a Chicago-area nonprofit promoting urban sustainability, has a long-run vision of a Chicagoland building energy-efficiency system, which, if started up quickly, would help to effectively deploy relevant stimulus dollars in the near-term. Its activities focus on ramping up existing weatherization and retrofit programs in the short-term to take best advantage of current stimulus dollars while at the same time building the institutional capacity to launch and sustain a new regional initiative aimed at coordinating energy efficiency information, financing, and service delivery for the seven-county region over the long-term.

The Center for Neighborhood Technology (CNT) is using ARRA and other resources to work toward a long-run vision of a sustainable regional energy efficiency system. CNT envisions a centrally-coordinated initiative— either through a new stand-alone entity or a formalized network—to manage the financing, marketing, performance monitoring and certification, information provision, supply chain development, and customer assistance required to efficiently scale up the delivery of retrofit services for all types of buildings across the Chicago region.

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Bruce Katz presented a speech on demographic shifts in the country's largest 100 metropolitan areas and how various leaders, including those in Seattle, will meet the policy challenges of a changing nation.

Introduction:
Today, I would like to present our findings from a major research initiative at the Metropolitan Policy Program, which is accompanied by an interactive website: the State of Metropolitan America. Our report examines the demographic trends that have affected the top 100 metropolitan areas so far this decade, covering the year 2000 through the year 2008. We find a nation in demographic transformation along five dimensions of change.

Watch video of the speech on the Seattle Channel »

We are a growing nation.  Our population exceeded 300 million back in 2006 and we are now on our way to hit 350 million around 2025.

We are diversifying.  An incredible 83 percent of our growth this decade was driven by racial and ethnic minorities. 

We are aging.  The number of seniors and boomers exceeded 100 million this decade.

We are selectively educating. Whites and Asians are now more than twice as likely to hold a bachelors degree as blacks and Hispanics.

We are a nation divided by income. Low-wage workers saw hourly earnings decline by 8 percent this decade; high wage workers saw an increase of 3 percent.  

With this background, I will make three main points today.

First, America’s top 100 metropolitan areas are on the front lines of our nation’s demographic transformation.  The trends I’ve identified—growth, diversity, aging, educational disparities, income inequities—are happening at a faster pace, a greater scale and a higher level of intensity in our major metropolitan areas.  

Second, the shape and scale of demographic transformation is profoundly uneven across metropolitan America.  This variation only partially reflects the traditional division of our country into regions like New England or the Middle Atlantic or the Mountain West. Rather a new “Metro Map” of the nation is emerging that unites far flung communities by their demographic realities rather than their physical proximity. 

Finally, demographic transformation requires action at both the macro and metro scale.  The federal government and the states need to lead where they must to address the super-sized challenges wrought by fast change.  Metropolitan areas must innovate where they should in ways that are tailored to their distinct challenges and opportunities.  And the geography of transformation at the metro scale requires new institutions and ways of governing.

These policy and institutional changes will not be easy.

But let’s remember one thing.  In the global context, the United States is a demographically blessed nation.  Established competitors like Japan, Britain and Germany are either growing slowly or actually declining; rising nations like China remain relatively homogenous. 

In a fiercely competitive world, our growth and diversity may be America’s ace in the hole.

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Over the past two decades, the Puget Sound area’s innovation-driven economy has become a magnet for highly educated people from across the country and around the world. Drawn to the region by some of the nation’s most innovative companies—Microsoft, Boeing, Nintendo, Amazon, Genentech and the Fred Hutchinson Cancer Research Center, to name a few—the Puget Sound region ranks well on measures of educational attainment. Of the nation’s largest 100 metro areas, the Seattle-Tacoma-Bellevue area is 11th in bachelor’s degree holders and 17th in graduate degree attainment.

But for all its brainpower, the region has fallen behind in terms of cultivating homegrown talent, particularly in less affluent school districts located in South Seattle and South King County. Starting from an early age, low-income students and children of color in these communities tend to lag behind on important indicators of educational success. The effects of this achievement gap worsen with time, putting these students at a serious disadvantage that often affects their ability to find jobs and their earning potential. 

In an effort to address this achievement gap, the Community Center for Education Results has teamed up with the city of Seattle, the University of Washington, the Seattle Community Colleges District, the Puget Sound Educational Service District, the Bill & Melinda Gates Foundation and others to form the Road Map Project, a coalition working to double the number of South Seattle and South King County students pursuing a college diploma or career credential by 2020.

What’s innovative about the Road Map Project is its focus on collective action and community engagement. By bringing together key stakeholders to collaborate on shared goals, the project is creating a new model for efforts to reduce inequality in educational attainment. Its cradle-to-college-and-career approach aims to improve student outcomes beginning with access to prenatal care and kindergarten readiness all the way through to elementary and secondary schooling and beyond. Through a combination of community outreach and partnership building, data-driven goal-setting and performance management, the project supports area organizations working to boost student success and close the achievement gap in South Seattle and South King County.

In December, the Project released its baseline report, which provides a detailed snapshot of student achievement in the Road Map region during the 2009-2010 school year. With this initial data in hand, the project will be able to work with area organizations to encourage and track progress on a wide variety of indicators, ranging from birth weight and full-day kindergarten enrollment to proficiency in reading, math, and science, parent engagement to graduation rates and postsecondary enrollment. “Demographics should not determine the destiny of children in this region,” says Mary Jean Ryan, executive director of the Community Center for Education Results. “The children who grow up here deserve as good of an education as the people who show up here.”

      

When my wife and I relocated from D.C.’s Logan Circle to Capitol Hill five years ago, the most tumultuous change in our lifestyle (aside from my not being able to walk to Brookings every day) concerned the much farther distance we’d have to travel to the nearest supermarket. We had the luxury of shopping at a very nice, if spendy, grocery store about two blocks from our home, which meant that we often did “just-in-time” dinner shopping on the way home from work. Now we were moving to a house where the distance to the nearest supermarket was 1.5 miles, not so walkable at 7 pm.

Did we live in a “supermarket desert?” On the one hand, Capitol Hill is a pretty densely populated part of D.C., so 1.5 miles felt like a long way. And while the Hill is an economically diverse area, it’s large with significant pockets of affluence. On the other hand, like a lot of our neighbors, we own a car. So while nightly trips to the supermarket were out, it was hardly an onerous trip on the weekends.

There are, however, many communities nationwide in which that trip to the supermarket is a long one, and most have much lower incomes than the Hill. That’s the conclusion from new research we conducted with help from The Reinvestment Fund (TRF), a community development financial institution and research organization based in Philadelphia. TRF played a lead role in designing and implementing the Pennsylvania Fresh Food Financing Initiative, a program that provides grants and low-cost capital to facilitate the location of new supermarkets and fresh food retailers in that state’s underserved communities. That initiative is now the model for several other state and local programs, as well as the inspiration for a major new federal budget initiative that seeks to improve community health and economic development outcomes through supermarket attraction and expansion.

With TRF, we looked at 10 metro areas across the country, ranging in size from Jackson, Miss. to Los Angeles. Unlike a lot of previous research that attempted to identify “food deserts,” TRF’s analysis looks at factors beyond distance to a supermarket that matter for access, including a community’s population density and level of car ownership. And it uses household income and expenditure data to help pinpoint the communities that have a significant untapped local demand for supermarkets.

Across the 10 metro areas, about 1.7 million people (5 percent of total population) live in low- and moderate-income communities that are significantly underserved by supermarkets. African Americans, children, and very low-income families are over-represented in these areas. Greater Los Angeles alone accounts for half a million of the underserved; and in the Cleveland metro, more than one in nine residents lives in a low-supermarket-access community. Estimates suggest that upwards of $2.6 billion annually in grocery expenditures may “leak” out of these communities due to a lack of nearby supermarkets.

The real upside of this research project is that all of the results are viewable online, through TRF’s PolicyMap service. So local economic development officials, neighborhood-based organizations, retailers, and others can examine the location and characteristics of low-supermarket-access areas in their own communities. On Capitol Hill, the analysis suggests that we’re pretty well served. Lots of car owners, and it’s really not that far to the store. Cross the Anacostia River, however, and it’s another story altogether. Pinpointing and describing the untapped opportunities for supermarket development is hopefully a first step toward reducing market obstacles to higher-quality, lower-cost food options for residents of communities like Ward 7 and Ward 8 nationwide.

      

The Brookings Metropolitan Policy Program and The Reinvestment Fund (TRF) performed a detailed analysis of supermarket access in 10 metropolitan areas, and the results are discussed in a new video, “Getting to Market."

Results from the analysis encourage users to view the locations of, and generate reports about, low-supermarket-access communities within the 10 metropolitan areas. This is highly useful data for those working at the national and local levels to tackle the problem of inadequate access through public policy and private investment. You can also access these data alongside any of PolicyMap’s 10,000 data indicators and full functionality at www.policymap.com

For those interested in other metropolitan areas, TRF has made available a nationwide analysis of low-supermarket-access communities at www.trfund.com.

Media Memo »


Profiles of 10 Metropolitan Areas (PDFs)

Atlanta, GA	Little Rock, AR
Baltimore, MD	Los Angeles, CA
Cleveland, OH	Louisville, KY
Jackson, MS	Phoenix, AZ
Las Vegas, NV	San Francisco, CA

Below are samples of data found on our interactive map

Map of the San Francisco area showing Low Access Areas with the access score for the area. Access scores are the degree to which a low/moderate-income community's residents are underserved by supermarkets.

Map of Baltimore showing Low Access Areas against the estimated percentage of families that live in poverty.

Map of Cleveland showing Low Access Areas against the estimated population above the age of 65.

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At a legislative conference in Cambridge, Ohio, Bruce Katz stressed the importance of cities and metro areas to the state's overall prosperity. Acknowledging the decline of Ohio's older industrial cities, Katz noted the area's many assets and argued for a focus on innovation, human capital, infrastructure, and quality communities as means to revitalize the region. 

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Should increasing exports be part of the solution to Greater Cleveland's -- and the nation's -- economic doldrums? Can export growth make this recovery job-filled rather than jobless?

That's a counterintuitive proposition, but one that is gaining traction in Northeast Ohio. Cleveland, Youngstown and other metros often see themselves on the losing end of globalization, as manufacturing has moved abroad and trade barriers and currency manipulations impede the entry of U.S.-made goods into foreign markets.

But exports bring tremendous benefits to workers, companies and the nation as a whole. Exporting companies tend to be more innovative. They pay higher wages across all skill levels. And they are a response to a new global reality: 95 percent of the world's customers live outside the United States.

Any successful export strategy, including the one that the Obama administration is developing, must start with where U.S. exports come from. Our major metropolitan areas are the nation's export hubs. In 2008, they produced about 64 percent of U.S. exports, including more than 62 percent of manufactured goods and 75 percent of services.

Northeast Ohio's major metros are leaders in exports, oriented toward global consumers in a way that most American regions are not. Exports contribute more than 12 percent of the gross metropolitan product in Akron, 13 percent in Cleveland, and a jaw-dropping 18 percent in Youngstown, compared to a national metro average of 10.9 percent.

Exports are also a source of much-needed jobs in these metros. As of 2008 (the most recent year for which we have data) there were 110,000 export jobs in the Cleveland metro and about 30,000 each in greater Akron and Youngstown. Every $1 billion in exports from the average metropolitan area in 2008 supported 5,800 jobs.

To leverage the powerful export activity already occurring in Cleveland and elsewhere, the Obama administration should connect its macroeconomic vision for export growth with the metro reality where the doubling will mostly occur.

For example, the president's export advisory council should include state and local leaders, and revamp export guidance and support to meet the needs of small firms, which find it hard to enter new markets.

But Northeast Ohio metros have their own work to do. The rate of export growth between 2003 and 2008 in Cleveland and Akron is lackluster when compared to the large metro average. U.S. companies dominate the global market in service exports, and the nation actually has a generous service trade surplus, but service exports' share of overall output in Northeast Ohio metros is smaller than the large metro average, and growth in service exports is slower.

Most troubling, Cleveland and its neighbors are underperforming when it comes to innovation, which is a critical ingredient for future international success. Metros that are manufacturing-oriented or export-intensive (or both) tend to create patents at a rate of just over five patents per 1,000 workers. But Cleveland, Akron and Youngstown fall short, with 2.8, 4.5, and 1 patent per 1,000 workers, respectively.

Northeast Ohio must accelerate its efforts to increase the region's innovation and export capacity, through regional organizations such as NorTech and JumpStart. Just as the president set an export goal for the nation, Northeast Ohio should embrace the opportunity to set its own aggressive export goals. Business groups, the Fund for Our Economic Future, universities and regional economic development organizations have made a start but need to devote more resources and collaborate to achieve those goals.

The region can make this happen. Organizations like the Manufacturing and Advocacy and Growth Network (MAGNET) and its partners, with support from the Fund and chambers, are working directly with companies to increase manufacturing innovation in Northeast Ohio, with increasing exports one of their major emphases.

For too long, the debate over export policy has been the exclusive domain of macro policymakers in Washington and a narrow clique of trade constituencies. It is time to include a larger portion of the business sector and, just as importantly, the places like Northeast Ohio, where exporting companies can thrive.

       

There is a lot of hope around the potential of Big Data—massive volumes of data (such as cell phone GPS signals, social media posts, online digital pictures and videos, and transaction records of online purchases) that are large and difficult to process with traditional database and software techniques—to help achieve the sustainable development goals. The United Nations even calls for using the ongoing Data Revolution –the explosion in quantity and diversity of Big Data—to make more and better data usable to inform development analysis, monitoring and policymaking: In fact, the United Nations believes that that “Data are the lifeblood of decision-making and the raw material for accountability. Without high-quality data providing the right information on the right things at the right time; designing, monitoring and evaluating effective policies becomes almost impossible.” The U.N. even held a “Data Innovation for Policy Makers” conference in Jakarta, Indonesia in November 2014 to promote use of Big Data in solving development challenges.

Big Data has already played a role in development: Early uses of it include the detection of influenza epidemics using search engine query data or the estimation of a country’s GDP by using satellite data on night lights. Work is also under way by the World Bank to use Big Data for transport planning in Brazil.

During the Data for Development session at the recent NetMob conference at MIT, we presented a paper in which we jump on the Big Data bandwagon. In the paper, we use mobile phone data to assess how the opening of a new toll highway in Dakar, Senegal is changing how people commute to work (human mobility) in this metropolitan area. The new toll road is one of the largest investments by the government of Senegal and expectations for its developmental impact are high. In particular, the new infrastructure is expected to increase the flow of goods and people into and out of Dakar, spur urban and rural development outside congested areas, and boost land valuation outside Dakar. Our study is a first step in helping policymakers and other stakeholders benchmark the impact of the toll road against many of these objectives.

Assessing how the impact of the new toll highway differs by area and how it changes over time can help policymakers benchmark the performance of their investment and better plan the development of urban areas.

The Dakar Diamniadio Toll Highway

The Dakar Diamniadio Toll Highway (in red in Figure 1), inaugurated on August 1, 2013 is the first section (32 km or 20 miles) of a broader project to connect the capital, Dakar, through a double three-lane highway to a new airport (Aeroport International Blaise Diagne, AIBD) and a special economic zone, the Dakar Integrated Special Economic Zone (DISEZ) and the rest of the country.

Note: The numbers indicate the incidence of increased inter cell mobility and were used to calculate the percentage increase in mobility.

The cost of this large project is estimated to be about $696 million (FCFA 380.2 billion or 22.7 percent of 2014 fiscal revenues, excluding grants) with the government of Senegal having already disbursed $353 million. The project is one of the first toll roads in sub-Saharan Africa (excluding South Africa) structured as a public-private partnership (PPP) and includes multilateral partners such as the World Bank, the French Development Agency, and the African Development Bank.

In our study, we ask whether the new toll road led to an increase in human mobility and, if so, whether particular geographical areas experienced higher or lower mobility relative to others following its opening.

Did the Highway Increase Human Mobility?

Using mobile phone usage data (Big Data), we use statistical analysis in our paper to approximate where people live and where they work. We then estimate how the reduction in travel time following the opening of the toll road changes the way they commute to work.

As illustrated in the map of Figure 1, we find some interesting trends:

• Human mobility in the metropolitan Dakar area increased on average by 1.34 percent after the opening of the Dakar Diamniadio Toll Highway. However, this increase masks important disparities across the different sub-areas of the Dakar metropolitan areas. Areas in blue in Figure 1 are those for which mobility increased after the opening of the new road toll while those in red experienced decreased mobility.
• In particular, the Parcelles Assainies suburban area benefited the most from the toll road with an increase in mobility of 26 percent. The Centre Ville (downtown) area experienced a decrease in mobility of about 20 percent.

These trends are important and would have been difficult to discover without Big Data. Now, though, researchers need to parse through the various reasons these trends might have occurred. For instance, the Parcelles Assainies area may have benefited the most because of its closer location to the toll road whereas the feeder roads in the downtown area may not have been able to absorb the increase in traffic from the toll road. Or people may have moved from the downtown area to less expensive areas in the suburbs now that the new toll road makes commuting faster.

The Success of Big Data

From these preliminary results (our study is work in progress, and we will be improving its methodology), we are encouraged by the fact that our method and use of Big Data has three areas of application for a project such as this:

Benchmarking: Our method can be used to track how the impact of the Dakar Diamniadio Toll Highway changes over time and for different areas of the Dakar metropolitan areas. This process could be used to study other highways in the future and inform highway development overall.

Zooming in: Our analysis is a first step towards a more granular study of the different geographic areas within the Dakar suburban metropolitan area, and perhaps inspire similar studies around the continent. In particular, it would be useful to study the socio-economic context within each area to better appreciate the impact of new infrastructure on people’s lives. For instance, in order to move from estimates of human mobility (traffic) to measures of “accessibility,” it will be useful to complement the current analysis with an analysis of land use, a study of job accessibility, and other labor markets information for specific areas. Regarding accessibility, questions of interest include: Who lives in the areas most/least affected? What kind of jobs do they have access to? What type of infrastructure do they have access to? What is their income level? Answers to these questions can be obtained using satellite information for land prices, survey data (including through mobile phones) and data available from the authorities. Regarding urban planning, questions include: Is the toll diverting the traffic to other areas? What happens in those areas? Do they have the appropriate infrastructure to absorb the increase in traffic?

Zooming out: So far, our analysis is focused on the Dakar metropolitan area, and it would be useful to assess the impact of new infrastructure on mobility between the rest of the country and Dakar. For instance, the analysis can help assess whether the benefits of the toll road spill over to the rest of the country and even differentiate the impact of the toll road on the different regions of the country.

This experience tells us that there are major opportunities in converting Big Data into actionable information, but the impact of Big Data still remains limited. In our case, the use of mobile phone data helped generate timely and relatively inexpensive information on the impact of a large transport infrastructure on human mobility. On the other hand, it is clear that more analysis using socioeconomic data is needed to get to concrete and impactful policy actions. Thus, we think that making such information available to all stakeholders has the potential not only to guide policy action but also to spur it. 

References

Atkin, D. and D. Donaldson (2014). Who ’ s Getting Globalized ? The Size and Implications of Intranational Trade Costs . (February).

Clark, X., D. Dollar, and A. Micco (2004). Port efficiency, maritime transport costs, and bilateral trade. Journal of Development Economics 75(2), 417–450, December.

Donaldson, D. (2013). Railroads of the Raj: Estimating the Impact of Transportation Infrastructure. forthcoming, American Economic Review.

Fetzer Thiemo (2014) “Urban Road Construction and Human Commuting: Evidence from Dakar, Senegal.” Mimeo

Ji, Y. (2011). Understanding Human Mobility Patterns Through Mobile Phone Records : A cross-cultural Study.

Simini, F., M. C. Gonzalez, A. Maritan, and A.-L. Barab´asi (2012). A universal model for mobility and migration patterns. Nature 484(7392), 96–100, April.

Tinbergen, J. (1962). Shaping the World Economy; Suggestions for an International Economic Policy.

Yuan, Y. and M. Raubal (2013). Extracting dynamic urban mobility patterns from mobile phone data.

      

       

       

Executive Summary

Tax increment finance (TIF) is a popular and potentially powerful tool for places that need economic development the most yet have the least to spend. By allowing jurisdictions to use portions of their tax base to secure public-sector bonds, the mechanism allows fiscally strapped localities to finance site improvements or other investments so as to "level the playing field" in economic development.

However, poorly designed TIF programs can cause problems. Not only can they increase the incentives for localities to engage in inefficient, zero-sum competition for tax base with their neighbors. Also, lax TIF rules may promote sprawl by reducing the costs of greenfield development at the urban fringe. It is therefore critical that state legislatures design TIF rules well.

In view of this, an analysis of the way TIF is designed and utilized in Missouri shows that:

• Missouri law creates the potential for overuse and abuse of TIF. Vague definitions of the allowable use of TIF permit almost any municipality, including those market forces already favor, to use it. Weak limits on its use for inefficient inter-local competition for tax base touch off struggles between localities. And the inclusion of sales tax base in the program tilts it toward lower-wage jobs and retail projects, which rarely bring new economic activity into a region.
  
  
• Thanks to these flaws, TIF is used extensively in high-tax-base Missouri suburban areas with little need for assistance in the competition for tax base. This is especially true in the St. Louis metropolitan area. There, TIF money very frequently flows to purposes other than combating "blight" in disadvantaged communities' its classic purpose. In fact, less than half of the 21 St. Louis-area cities that were using TIF in 2001 were disadvantaged or "at-risk" when evaluated on four indicaters of distress. On another measure, just seven of the 20 suburban areas using TIF fell into the "at-risk" category.
  
  
• TIF is also frequently being used in the outer parts of regions' particularly in the St. Louis area. Most notably, only nine of the St. Louis region's 33 TIF districts lie in the region's core. Conversely, 14 of the region's 38 TIF districts lie west of the region's major ring road (I-270). These districts, moreover, contain 57 percent of the TIF-captured property tax base in the region. By contrast, the Kansas City region shows a pattern more consistent with the revitalization goals of TIF. The vast majority of the districts lie in the region's center city, though the huge size of the city means many are still geographically far-flung.

In sum, poorly designed TIF laws are being misused at a time when state and local fiscal pressures require every dollar be spent prudently. As a result, a potentially dynamic tool for reinvestment in Missouri's most disadvantaged communities threatens to become an engine of sprawl as it is abused by high-tax-base suburban areas that do not need public subsidies.

For these reasons, Missouri would be well-served by significant reforms in the laws governing TIF:

• The allowable purposes for TIF should be more strictly defined to target its use to places with the most need for economic development.
  
  
• Higher level review of local determinations that TIF subsidies will support net contributions to the regional or state economy (the "but-for" requirement) should be implemented.
  
  
• Local TIF administrators should be required to show that TIF subsidies are consistent with land-use and economic development needs both locally and in nearby areas.

If such reforms were put in place, TIF could be returned to its attractive main purpose: that of providing resources that would not otherwise be available to localities that badly need them to promote needed economic development and redevelopment.

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