Comprehensive Plan Subcommittee Evanston Plan Commission

COMPREHENSIVE PLAN SUBCOMMITTEE EVANSTON PLAN COMMISSION

Wednesday, May 22, 2013

7:30 A.M.

Lorraine H. Morton Civic Center, 2100 Ridge Avenue, Room 2403

AGENDA

1. CALL TO ORDER

2. DISCUSSION:

a. COMPLETE FRAMEWORK OF INITIAL ISSUES

b. IDENTIFY STAKEHOLDERS

c. COMPLETE STREETS

3. NEXT STEPS

4. ADJOURNMENT

Order of agenda items are subject to change. Information about the Plan Commission is available online at: http://www.cityofevanston.org/plancommission. Questions can be directed to the Neighborhood Planner, Susan Guderley, at 847-448-8675 or by e-mail at [email protected].

The City of Evanston is committed to making all public meetings accessible to persons with disabilities. Any citizen needing mobility or communications access assistance should contact the Community and Economic Development Department 48 hours in advance of the scheduled meeting so that accommodations can be made at 847-448-8683 (Voice) or 847-448-8064 (TYY). DRAFT – NOT APPROVED

MEETING NOTES COMP PLAN SUBCOMMITTEE Wednesday, April 24, 2012 7:30 A.M. Evanston Civic Center, 2100 Ridge Avenue, Room 2403

Members Present: Scott Peters, Richard Shure, David Galloway, Barbara Putta Members Excused: Lenny Asaro

Staff Present: Susan Guderley, Dennis Marino

1. CALL TO ORDER Chair Peters called the meeting to order at 7:35 A.M. The meeting notes of April 3, 2013 were approved, as written.

2. DISCUSSION  Reviewed a table displaying the population and employment densities within ¼-mile of Evanston’s CTA and Metra stations. The data was collected from the Center for Neighborhood Technology’s TOD Database.  Chair Peters reviewed his memo to the committee that suggested an approach to the comp plan update that was organized around issues and challenges facing Evanston as opposed to the 2000 Plan’s structure of functional components like Housing, Transportation, Land Use, etc. The desired future building environment would respond to the plan’s policy and action recommendations.  Member Shure noted that a prior committee discussion had suggested a similar approach that identified major problem areas for each chapter. He endorsed a issue/action approach as a structure for the revised plan. Member Galloway agreed that issues made a better organizational structure. Member Putta noted that the current plan’s organization is wordy, repetitive and dilutes the strategies and actions aimed at issues that straddle several functional silos. A plan organized around strategic actions could be more succinct.  At a prior meeting, the discussion had also suggested organizing around guiding principles or themes, some of which the committee has been exploring definitions: TOD, livability, sustainability, density, and mixed-use. The committee emphasized the need for a usable plan.  There was also interest in the concept of testing alternatives and identifying trade-offs. This type of discussion had been accommodated by CMAP’s local planning meetings leading up the Plan 2030, with the use of voting pads by their audiences. There would be a need to develop alternative local scenarios, along the lines of the ones developed by CMAP for the region.  Chair Peters suggested that committee members review the plan for Marin County, CA for its approach.  The goal is to create a plan that can be implemented – containing a ranked list of all recommended actions. In its discussion of the actions, the plan will distinguish between those which are feasible in the short term, those which require a longer planning horizon and those which may be unattainable but function as a goals.

Page 1 of 2 Comp Plan Subcommittee Notes DRAFT – NOT APPROVED  The Chair recognized a member of the public, Jessica Feldman, for comment. She urged the committee to elevate the profile of the project and their work.  Chair Peters’ memo suggested an initial list of issue areas for consideration in the Comp Plan, including: o Changes in city’s demographics; o Increased cost of oil and its impact on local land use and real estate market; o Need for economic development within a fully developed, land-locked city; o Opportunity to build on to existing transit and create transit oriented developments (TOD) and pedestrian friendly neighborhoods appealing to both baby-boomers and millennials o Opportunity to build on and integrate various, existing neighborhood plans; o Need to plan for economic development and TOD infill in west Evanston, as well as near existing CTA and Metra stations; o Need to identify and plan for areas of opportunity where economic development and diverse housing opportunities might be provided; o Protect the diversity of housing for various income levels, household type and characteristics, as well as unit types/tenure.  The Chair asked if anyone had suggested additions, those included: o Lake Michigan shoreline – role as iconic natural feature of Evanston, its roles as both an economic and recreational asset, and its relationship with adjacent neighborhoods; o Open space – issues include the existing deficit for both active/passive recreational use and its role as a critical design element to balance increased density; o Circulator to serve west Evanston and other potential TOD locations; o Northwestern University plans – what is the relationship between NU master planning and city’s own land use plan; o Future role and use of MWRD canal; o Quality of Life/Livability – encompasses some of the other topics mentioned: open space, transportation, walkability, etc  Chair asked for suggestions regarding the process for moving forward with the comprehensive plan revision. o Needed some organizational structure or “skeleton” for plan to share with public o Need public input process that: 1) Identifies and engages stakeholders (elected officials, Plan Commission, NU, business districts, others); 2) Key public meetings in the neighborhoods (Robert Crown, Fleetwood- Jourdain, etc); 3) Non-traditional public input techniques, e.g. COE web-based information, surveys and CMAP voting pads for scenarios.

3. NEXT STEPS NEXT MEETING – Wednesday, May 22, 7:30 a.m., Room 2403

Discussion items: Additional details about a planning process, debrief on meeting with WestEnd for discussion of local manufacturing.

4. ADJOURNMENT The meeting adjourned at 9:00 A.M.

Page 2 of 2 Comp Plan Subcommittee Notes

Memorandum

To: Members of the Comp Plan Subcommittee

From: Susan Guderley, Neighborhood Planner

Subject: Packet Materials – List of articles re TOD and Walkable Places

Date: May 10, 2013

1. Job Sprawl Stalls: The Great Recession & Metropolitan Employment Location, E. Kneebone, Brookings Institute, April 2013.

2. ‘Triumph of Suburbia’ is a Far-Fetched Story, R. Steuteville, Better!Cities&Towns (Blog post), April 30, 2013.

3. Walk This Way: The Economic Promise of Walkable Places in Metropolitan Washinton D.C., C. Leinberger, M. Alfonzo, Brookings Institute, May 2012.

4. Transit-Oriented Development in the Chicago Region: Efficient and Resilient Communities for the 21st Century, Center for Neighborhood Technology, April 2013.

5. What Does Peak VMT mean for the Twin Cities?, B. Lindeke, Twin City Sidewalks (Blog post), March 11, 2013.

6. What the Steamship and the Landline Can Tell Us About the Decline of the Private Car, E. Badger, Atlantic Cities (Online), March 11, 2013.

7. Inspired By Memphis, C. Marohn, Better! Cities&Towns (Blog Post), June 18, 2012.

8. Location Efficiency and Housing Type: Boiling it Down to BTUs, Jonathan Rose Companies, January 2011.

METROPOLITAN OPPORTUNITY SERIES Job Sprawl Stalls: The Great Recession and Metropolitan Employment Location

Elizabeth Kneebone

An analysis of the location of private-sector employment within 35 miles of downtown in the nation’s 100 largest metropolitan areas from 2007 to 2010, and across the 2000s, finds:

n Steep employment losses following the Great Recession stalled the steady decentraliza- “In the wake tion of jobs that characterized the early to mid-2000s. After dropping two percentage points from 2000 to 2007, the share of metropolitan jobs within three miles of downtown sta- of the Great bilized from 2007 to 2010. However, by 2010 nearly twice the share of jobs was located at least 10 miles away from downtown (43 percent) as within three miles of downtown (23 percent). Recession, n Job losses in industries hit hardest by the downturn, including construction and manu- policymakers facturing, helped check employment decentralization in the late 2000s. Together, construction, manufacturing, and retail—each among the most decentralized of major indus- and regional tries—accounted for almost 60 percent of all job losses between 2007 and 2010, with half of those losses occurring at least 10 miles from downtown. leaders have the n In all but nine of the 100 largest metro areas, the share of jobs located within three miles of opportunity to downtown declined during the 2000s. Only Washington, D.C. experienced an increase in both the number and share of jobs located in the urban core during the 2000s. At the same time, the make strategic share of jobs at least 10 miles from downtown rose in 85 regions between 2000 and 2010. decisions n A metro area’s total employment—and policy and planning decisions around land use, economic development, and zoning—help shape the location of its jobs. Employment is about how they more decentralized in metro areas with at least 500,000 jobs. But even large metro areas with high degrees of job decentralization like Chicago and Detroit concentrate many of their jobs in will pursue dense locations outside the urban core. metropolitan In the wake of the Great Recession, policymakers and regional leaders have the opportunity to make strategic decisions about how they will pursue metropolitan growth. If the next period of growth.” economic expansion reinforces low-density, diffuse growth in metropolitan America, it will be that much harder for metro areas to achieve sustainable and inclusive growth over the long term.

Introduction

n 2009, “Job Sprawl Revisited: The Changing Geography of Metropolitan Employment” documented the widespread decentralization of jobs in metropolitan America.1 That analysis found that, between 1998 and 2006, employment—whether growing or declining—steadily moved farther away from downtowns across most major metro areas, in almost every major industry, Iand especially toward suburban communities at least 10 miles from the downtown. This shift occurred

BROOKINGS | April 2013 1 continuously—as the economy boomed in the late 1990s, as it turned down in the early 2000s, and then as it moved through a mid-decade recovery. Yet that analysis left off shortly before the nation entered the worst recession since the Great Depression, which led to the loss of nearly 9 million jobs nationally.2 Though the first economic downturn of the decade did not stall the outward movement of metropolitan jobs, the second, much more disruptive, recession of the decade may very well have changed prevailing job location patterns. The changing location of employment within a metro area intersects with a range of policy issues— from transportation to workforce development to regional innovation—that affect a region’s long-term health, prosperity, and social inclusion. A number of factors can drive the decentralization of employment, which is neither an inherently positive nor negative trend. Suburban development can take place in ways that foster dense, mixed-use, and regionally-connected job centers.3 Or it may occur in less dense and less accessible ways, raising challenges like strained infrastructure, increased energy consumption, greater spatial mismatches between the location of jobs and low-income and minority residents. In addition, because low-density job development can be difficult to effectively serve with transit, job sprawl can limit transportation options, increasing commute times and congestion.4 Understanding the geography of metropolitan employment will prove particularly important in the emerging recovery, as policymakers and regional leaders work to grow jobs and connect residents to economic opportunity. This brief assesses recent trends in employment location in 2000, 2007, and 2010, documenting the impact of the Great Recession on the geographic distribution of metropolitan jobs during the 2000s.

Methods

his brief builds on and updates the methods used in 2009’s “Job Sprawl Revisited” to analyze employment location trends. It uses the Census Bureau’s ZIP Business Patterns data on private-sector employment from 2000, 2007, and 2010 (the most recent year of data available).5 It employs GIS software to allocate ZIP code employment data to three distance Tbands: within three miles of a central business district (CBD), three to 10 miles away from a CBD, and 10 to 35 miles from a CBD.6 Two methodological differences exist between this assessment and the 2009 analysis that affect comparability. First, the 2009 analysis focused on 98 of the 100 largest metro areas based on 2005 employment totals. The current analysis considers the 100 largest metro areas based on population in 2010. While there is a high degree of overlap in the two lists, differences exist.7 Second, the selection process for CBDs has been expanded in this analysis to more fully reflect metro areas that contain multiple employment centers. As with the previous analysis, 1982 CBDs (designated by the Census of Retail Trade) serve as the basis for the selection (Box 1). To designate CBDs for this analysis, a number of comparisons were made based on census tract-level job density and total employment estimates in 2010.8 For first-named cities in the official metropolitan statistical area name, if the densest employment tract in 2010 overlapped with the 1982 CBD, the equivalent of the 1982 CBD was used.9 If the densest tract in 2010 did not overlap with the 1982 CBD and had higher employment totals than the historical CBD, the densest tract in 2010 was selected as the CBD for this analysis. However, if the 2010 tract contained fewer jobs, the 1982 CBD was maintained. The same process was used to determine CBDs in any other city within the metro area that had an official CBD in 1982.10 Once secondary CBDs were determined, total employment within those CBDs was compared to the primary CBD. If the number of jobs in the secondary CBD was at least one-third of the amount located in the primary CBD in 2010, the secondary CBD was also included as a “downtown” in the analysis. (See Appendix A for a full list of CBDs included in this assessment.)

2 BROOKINGS | April 2013 Box 1. A Note about 1982 Central Business Districts

The U.S. Census Bureau last identified Central Business Districts based on the 1982 Census of Retail Trade, after which the program was discontinued. The Census Bureau defined a CBD as “an area of very high land valuation characterized by a high concentration of retail businesses, service businesses, offices, theaters, and hotels, and by a very high traffic flow,” which could be comprised of one or multiple census tracts.11 Though dated, the 1982 CBDs represent the last systematic identification of business districts at the national scale. Furthermore, the 1982 CBDs continue to exhibit significant overlap with the densest job centers in the nation’s major metro areas. Of the 100 metro areas in this analysis, 91 contained a 1982 CBD that overlapped with the highest job-density census tract in 2010. Nine (9) contained a 1982 CBD that coincided with the second-densest tract, which in each case had higher job totals than the first-ranked tract. Moreover, the continued relevance of the 1982 CBDs is apparent in the expanded list of downtowns used in this analysis. The 2009 paper limited potential downtowns to only places that appeared in the metropolitan area name, contained a 1982 CBD, and had at least half the number of jobs as the primary CBD. This analysis removes the name restriction and allows a place with a 1982 CBD to be a potential secondary job hub, as long as it contains at least one-third the number of jobs located in the primary CBD. Ultimately, the 2009 analysis identified 105 CBDs in 98 metro areas, while this analysis identifies 136 CBDs in 100 metro areas. To verify that this list of CBDs captures significant secondary job hubs in 2010, the selection process was run again, removing the 1982 CBD requirement. Tracts that were at least as dense as the primary CBD and contained at least one-third the jobs were considered. There were nine tracts in eight metro areas that met these criteria and were not directly adjacent to the 1982-identified CBD. All of these tracts fell within the primary city: seven fell within the three miles of the official CBD, and two within the 10 mile ring. None contained more jobs than the 1982-identified CBD. Thus, the 1982 CBDs continue to provide a robust baseline for selecting significant job centers across the nation’s largest metropolitan areas.

A. Steep employment losses following the Great Recession stalled the steady decentralization of jobs that characterized the early to mid-2000s. The late 2000s brought a protracted economic downturn and widespread job losses that touched almost every major metro area in the United States. The worst recession since the Great Depression and the weak recovery that followed caused the nation’s 100 largest metro areas to shed more than 5.8 million jobs within 35 miles of their downtowns from 2007 to 2010. Employment declined throughout these metro areas, from the urban core to outlying suburbs, but losses were not spread evenly (Table 1). The outer ring—more than 10 miles away from a CBD—lost jobs at a faster rate than the middle (between three and 10 miles) and inner (within three miles) rings. In fact, owing in part to the suburban- led nature of the housing market collapse and the downturn that followed, 45 percent of employment losses from 2007 to 2010 occurred more than 10 miles away from downtown. The Great Recession thus stalled the steady decentralization of metropolitan employment that marked much of the 2000s. Between 2000 and 2007, the share of jobs located more than 10 miles from downtown consistently grew, as the outer ring added employment at four times the rate of the middle ring, while the number of jobs located within three miles of a CBD actually fell. However, the job losses of the late 2000s effectively halted this trend, leaving the overall distribution of employment

Table 1. Employment Distribution Within 35 Miles of a Central Business District, 100 Metro Areas, 2000 to 2010

Number of Jobs 2000 2007 2010 2000 to 2007 2007 to 2010 2000 to 2010 Total Jobs 76,252,828 79,071,521 73,247,962 3.7% -7.4% -3.9% Within 3 Miles 18,698,287 17,907,472 16,752,320 -4.2% -6.5% -10.4% 3 to 10 Miles 26,369,343 26,985,109 24,948,689 2.3% -7.5% -5.4% 10 to 35 Miles 31,185,198 34,178,939 31,546,954 9.6% -7.7% 1.2%

Source: Brookings Institution analysis of ZIP Business Patterns data

BROOKINGS | April 2013 3 Figure 1. Change in the Geographic Distribution of Jobs Within 35 Miles of a Central Business District, 100 Metro Areas

10 to 35 Miles

3 to 10 Miles

2010 2007 Within 3 Miles 2000

- 5.0 10.0 15.0 20.0 25.0 30.0 35.0 40.0 45.0 50.0 Percent

Source: Brookings Institution analysis of ZIP Business Patterns data

relatively unchanged between 2007 and 2010 (Figure 1). The outsized impact of the recession on the outer ring led to a slight drop in the share of jobs located more than 10 miles away from downtown (-0.2 percentage points). At the same time, the middle ring also experienced a very small decline in job share (-0.1 percentage points), while the urban core exhibited a modest uptick (+0.2 percentage points) because it lost jobs slightly more slowly. Even with these late-decade trends, by 2010 jobs remained markedly more decentralized than in 2000. In 2010, more than three quarters of jobs within 35 miles of a downtown in the nation’s 100 largest metro areas located outside of the urban core. Roughly 17 million jobs fell within three miles of CBD (22.9 percent), while almost twice that number—31.5 million—located more than 10 miles from downtown (43.1 percent).

B. Job losses in industries hit hardest by the downturn, including construction and manufacturing, helped check employment decentralization in the late 2000s. The early to mid-2000s saw employment decentralize in nearly every major industry as the share of jobs in urban cores declined and the share in the outer ring grew. However, as the housing-led downturn deepened and spread, job losses in almost every major industry slowed that steady trend. Construction, manufacturing, and retail were among the industries hardest hit by job losses following the Great Recession. Together, those three industries accounted for 60 percent of the decline in total employment within 35 miles of downtown between 2007 and 2010.12 They were also among the most decentralized industries, locating roughly half of their jobs more than 10 miles from downtown in 2007 (Figure 2). As a result, roughly two-thirds of job losses in the outer ring of metropolitan areas came in construction, manufacturing, and retail. The collapse of the housing market also caused the real estate and finance industries—both of which had decentralized at a rapid pace earlier in the decade—to shed jobs at a faster-than-average rate, regardless of location. Amid these employment losses, jobs in these industries stopped their steady march outward in metropolitan areas. The share of construction, real estate, and finance jobs more than 10 miles from downtown dropped slightly between 2007 and 2010 (0.6 percentage points or less), while increasing slightly for manufacturing and retail (0.2 percentage points each).

4 BROOKINGS | April 2013 Figure 2. Job Location and Employment Change for Selected Industries within 35 Miles of Downtown, 100 Metro Areas, 2007 to 2010

Share of Jobs More Than 10 Miles from Downtown, 2007 Job Loss, 2007 to 2010

Construction

Manufacturing

Real Estate, Rental, and Leasing

Finance and Insurance Select Industry

Retail Trade

Health Care and Social Assistance

Educational Services

-40 -30 -20 -10 0 10 20 30 40 50 60 Percent

Source: Brookings Institution analysis of ZIP Business Patterns data

At the same time, as almost every other major industry shed employment, the health care and social assistance and educational services industries experienced notable job growth between 2007 and 2010, with increases shared across the three rings. The recession-era gains in health care and social assistance employment meant that jobs in that industry grew to account for roughly 17 percent of all jobs in the urban core by 2010—the largest share among major industry categories. However, those jobs continued to grow faster farther away from downtown. From 2007 to 2010, outer-ring health care and social assistance employment grew by 8 percent, versus 4 percent near downtown. In contrast, jobs in educational services grew slightly faster in the urban core than in other metropolitan locations toward the end of the decade. Still, longer-running trends meant that educational services joined 16 other major industries that ended the 2000s more decentralized than when the decade began. Together these industry dynamics helped contribute to an overall slowdown in job decentralization during the late 2000s. Ultimately, industry-specific losses and gains between 2007 and 2010 served to pause, but not reverse, the longer-running trend.

C. In all but nine of the 100 largest metro areas, the share of jobs located within three miles of downtown declined during the 2000s. Given the depth and length of the Great Recession, nearly every major metro area suffered job losses in the late 2000s. Between 2007 and 2010, 97 of the nation’s 100 largest metro areas lost employment within 35 miles of downtown.13 In many metro areas, these job losses changed the trajectory of employment location. Between 2000 and 2007, the share of jobs near downtowns declined in 95 of the 100 largest metro areas. But between 2007 and 2010, that share increased in more than half (54) of the nation’s largest metro areas (Table 2). However, in only four of those regions did the absolute number of jobs located in

BROOKINGS | April 2013 5 Table 2. Metro Areas with the Largest Increases in Urban Core and Outer-Ring Job Share, 2007 to 2010

Largest Increases in Share of Jobs within Largest Increases in Share of Jobs More Than 3 Miles of Downtown 10 Miles from Downtown Chattanooga, TN-GA 2.5 Cape Coral-Fort Myers, FL 3.0 New Orleans-Metairie-Kenner, LA 1.8 Little Rock-North Little Rock-Conway, AR 1.8 Louisville/Jefferson County, KY-IN 1.8 San Antonio-New Braunfels, TX 1.7 Charleston-North Charleston-Summerville, SC 1.7 Provo-Orem, UT 1.7 Cincinnati-Middletown, OH-KY-IN 1.6 El Paso, TX 1.6 Chicago-Joliet-Naperville, IL-IN-WI 1.6 Phoenix-Mesa-Glendale, AZ 1.5 San Jose-Sunnyvale-Santa Clara, CA 1.5 Oklahoma City, OK 1.5 Milwaukee-Waukesha-West Allis, WI 1.5 Charlotte-Gastonia-Rock Hill, NC-SC 1.5 Seattle-Tacoma-Bellevue, WA 1.3 Honolulu, HI 1.3 Austin-Round Rock-San Marcos, TX 1.3 Birmingham-Hoover, AL 1.3

Source: Brookings Institution analysis of ZIP Business Patterns data

the urban core actually grow: Austin, Charleston, Cincinnati, and New Orleans. Of these four regions, Austin was the only one that did not lose jobs overall during this time period. In the other 50 metro areas, the share of jobs near downtown increased because that ring lost jobs at a slower rate than the middle and outer employment rings. Even with these recession-related changes, 91 metro areas ended the decade with a lower share of jobs within three miles of downtown than in 2000 and two (Detroit and San Francisco) remained unchanged. Ultimately, the period following the downturn reversed the longer-running downward trend in urban core job share in just three metro areas. Between 2000 and 2007, Chicago, Oxnard, and Washington, D.C. each experienced declines in the share of jobs located within three miles of a CBD, but by 2010 had more than reversed those losses. These regions joined Milwaukee, where urban core job share held steady in the early 2000s, and Boston, Little Rock, and San Jose, where the share of jobs in the urban core had increased even before the Great Recession began. However, almost all of these regions (with the exception of Washington, D.C.) experienced net job losses over the course of the decade, with the increase in urban core job share occurring as the inner ring shed jobs at a slower rate than elsewhere. Notwithstanding the re-centralization of employment in a few places, job sprawl was the dominant metropolitan trend across the 2000s, especially in the West and South. Between 2007 and 2010, 56 metro areas experienced an uptick in outer-ring job share, led by regions including Cape Coral, Little Rock, and San Antonio, which shed jobs following the downturn, as well as El Paso, which managed to add jobs during this time period (Table 2). On the whole, the share of jobs in the outer ring increased in 85 of the nation’s largest metro areas from 2000 to 2010. Almost one-third of the nation’s largest metro areas (31) saw that share grow at more than twice the average rate (+2.2 percentage points), with Phoenix posting an increase of almost 11 percentage points (Table 3). Nine of the ten largest increases in outer-ring job share occurred in the South and West. With many jobs in fast-growing industries like construction, retail, and administrative support services, Phoenix, Oklahoma City, and Orlando, as well as the Texas metro areas of San Antonio, Houston, and Austin, each added jobs overall during the 2000s, particularly in the outer ring. Even employment losses following the downturn did not dampen decentralization in these metro areas, as each continued to see increases in outer-ring job shares between 2007 and 2010. In contrast, Dallas, Indianapolis, Memphis, and Jacksonville experienced a decline in total employment over the course of the decade, but gained jobs in the outer ring while losing them in closer-in places.

6 BROOKINGS | April 2013 Table 3. Metro Areas with the Largest Increases in Outer-Ring Job Share, 2000 to 2010

2000 to 2010 Within 3 Miles 3 to 10 Miles 10 to 35 Miles Phoenix-Mesa-Glendale, AZ -6.8 -4.0 10.8 San Antonio-New Braunfels, TX -5.4 -4.0 9.4 Austin-Round Rock-San Marcos, TX -2.7 -5.2 7.9 Houston-Sugar Land-Baytown, TX -3.3 -4.5 7.8 Dallas-Fort Worth-Arlington, TX -2.6 -5.1 7.7 Oklahoma City, OK -2.4 -4.8 7.2 Orlando-Kissimmee-Sanford, FL -2.8 -4.1 7.0 Indianapolis-Carmel, IN -2.9 -4.0 6.9 Memphis, TN-MS-AR -1.2 -5.6 6.8 Jacksonville, FL -3.8 -2.8 6.6

Source: Brookings Institution analysis of ZIP Business Patterns data

D. A metro area’s total employment—and policy and planning decisions around land use, economic development, and zoning—help shape the location of its jobs. A number of factors help determine where jobs locate with a region. As demonstrated by abrupt changes in employment levels following the Great Recession, the number of jobs—and whether that number is growing or declining—helps shape patterns and trends in the geographic distribution of employment. In fact, the number of jobs that a region contains matters more to its degree of employment decentralization than the actual geographic size of a metro area.

Map 1Map. Sh 1.a rSharee of Jofo bJobss 10 10 to to 3 355 M Milesiles fromfrom Downtown, Downto w100n, 1Metro00 M Areas,etro A 2010reas, 2010 Map 1. Share of Jobs 10 to 35 Miles from Downtown, 100 Metro Areas, 2010

4.2% - 20.0%

20.1% - 30.0% 4.2% - 20.0% 30.1% - 45.0% 20.1% - 30.0% 45.1% - 77.4% 30.1% - 45.0%

Source: Brookings Institution analysis45. 1of% ZIP- 77 .Business4% Patterns data Source: Brookings Institution analysis of ZIP Business Patterns data

Source: Brookings Institution analysis of ZIP Business Patterns data

BROOKINGS | April 2013 7 Table 4. Geographic Distribution of Jobs by Metro Area Employment Size, 100 Metro Areas, 2010

Share of Jobs Number of Total Number of Within Size Metro Areas Jobs Within 35 Miles 3 Miles 3 to 10 Miles 10 to 35 Miles Under 500,000 Jobs 58 15,764,185 30.3 45.2 24.4 Over 500,000 Jobs 42 57,483,777 20.8 31.0 48.2

All Metro Areas 100 73,247,962 22.9 34.1 43.1

Source: Brookings Institution analysis of ZIP Business Patterns data

In 2010, metro areas in the manufacturing belt that runs through the Midwest and Northeast exhibited some of the highest shares of jobs located more than 10 miles from downtown, though each major census region contains metro areas with above-average outer-ring employment shares (Map 1). In part, the industry mix of these manufacturing hubs may account for this larger regional pattern, but the Midwest and Northeast also contain many of the nation’s largest employment hubs. In general, the more jobs a metro area has, the more decentralized those jobs tend to be. On average, metro areas that contain fewer than 500,000 jobs have 30 percent of jobs in the urban core, outstripping the outer-ring job share by almost 6 percentage points (Table 4). In contrast, the 42 metro areas with more than 500,000 jobs (which are home to 78 percent of all jobs within 35 miles of a downtown in the 100 largest metro areas) locate an average of just 21 percent of jobs in the urban core, and more than 48 percent of jobs at least 10 miles from downtown. Notably, employment size matters much more than physical size, which is only weakly related to measures of decentralization.14 Among larger employment centers, three of the five most decentralized metro areas are Midwestern regions with a history of manufacturing (Table 5). Detroit leads the list, with over 77 percent of jobs located in the outer ring, with Chicago a distant second at 67 percent. In contrast, the most centralized large metro areas tend to be in the Sun Belt, with the exception of metropolitan New York, which located 31 percent of jobs within three miles of Manhattan’s central business district. San Jose regis- tered as the most centralized metro area by far in 2010, with 64 percent of jobs located within three miles of CBDs in San Jose, Palo Alto, and Sunnyvale. Among smaller employment centers, three of the five most decentralized metro areas ranked above the overall metro average for outer-ring job share in 2010—Memphis, Knoxville, and Worcester. However, Worcester also posted an above-average inner-ring job share, as did Stockton. At the other end of the spectrum, the most centralized smaller metro areas each located at least 46 percent of jobs within three miles of a central business district. Bridgeport exhibited the highest inner-ring job share among smaller employment centers, with 58 percent of jobs located in the urban core. Beyond employment size, political fragmentation—or the number of jurisdictions within a region—can also influence job location. Edward Glaeser and his colleagues found a significant relationship between the extent of a metro area’s fragmentation and its level of job sprawl. Jobs tend to locate farther from the city center in regions with more political units, as employers look for business-friendly tax rates and local governments beyond the central city.15 In keeping with these findings, many of the metro areas that rank among the most decentralized in Table 5 also exhibit higher levels of fragmentation (e.g., Chicago, Detroit, Philadelphia, and St. Louis), while many of the most centralized metro areas are less politically fragmented (e.g., Las Vegas, Salt Lake City, Virginia Beach, and San Jose). These patterns also underscore the importance of topography (e.g., the presence or absence of natural growth boundaries) and development decisions within metro areas in shaping employment location. Many of the most centralized metro areas in 2010 have more than one major employment hub. By contrast, the most decentralized metro areas are each anchored by one traditional CBD. But the most centralized list also includes a number of metro areas that have pursued growth management policies to encourage density and more centralized development. For instance, Honolulu and Salt Lake City each rank among the most centralized and each has only one CBD. Honolulu is hemmed in

8 BROOKINGS | April 2013 Table 5. Most Centralized and Decentralized Metro Areas by Employment Size, 100 Metro Areas, 2010

Most Centralized Most Decentralized Share of Jobs Share of Jobs # Within 3 to 10 to # Within 3 to 10 to of 3 10 35 Highest Share of 3 10 35 Highest Share Within 3 Miles CBDs Miles Miles Miles Beyond 10 Miles CBDs Miles Miles Miles Larger Employment Regions Larger Employment Regions San Jose-Sunnyvale-Santa Clara, CA 3 64.0 31.9 4.2 Detroit-Warren-Livonia, MI 1 7.3 15.3 77.4 Las Vegas-Paradise, NV 1 44.6 46.9 8.6 Chicago-Joliet-Naperville, IL-IN-WI 1 19.5 13.1 67.4 Virginia Beach-Norfolk-Newport News, VA-NC 3 32.4 53.2 14.4 Atlanta-Sandy Springs-Marietta, GA 1 9.9 25.6 64.6 Salt Lake City, UT 1 31.8 37.6 30.6 Philadelphia-Camden-Wilmington, PA-NJ-DE-MD 1 15.2 20.8 64.0 New York-Northern New Jersey-Long Island, NY-NJ-PA 1 30.9 23.0 46.1 St. Louis, MO-IL 1 13.2 25.6 61.2

Smaller Employment Regions Smaller Employment Regions Bridgeport-Stamford-Norwalk, CT 4 57.6 38.1 4.3 Memphis, TN-MS-AR 1 12.4 39.2 48.4 Honolulu, HI 1 53.9 28.3 17.8 Knoxville, TN 1 18.6 36.2 45.2 Allentown-Bethlehem-Easton, PA-NJ 3 50.3 35.2 14.4 Worcester, MA 1 31.0 24.9 44.1 Oxnard-Thousand Oaks-Ventura, CA 3 47.4 44.1 8.5 Stockton, CA 1 30.5 31.3 38.2 Scranton-Wilkes-Barre, PA 2 46.5 33.7 19.8 Charleston-North Charleston- Summerville, SC 1 21.7 40.2 38.1

Source: Brookings Institution analysis of ZIP Business Patterns data

Table 6. Share of Employment in High-Density ZIP Codes Outside the Urban Core, Selected Metro Areas, 2010

Metro Area % Los Angeles-Long Beach-Santa Ana, CA 76.7 San Diego-Carlsbad-San Marcos, CA 55.2 Chicago-Joliet-Naperville, IL-IN-WI 54.1 New York-Northern New Jersey-Long Island, NY 54.1 Tucson, AZ 53.3 Houston-Sugar Land-Baytown, TX 52.8 San Francisco-Oakland-Fremont, CA 52.4 Washington-Arlington-Alexandria, DC-VA-MD-WV 49.3 Detroit-Warren-Livonia, MI 49.0 Omaha-Council Bluffs, NE-IA 48.1 Phoenix-Mesa-Glendale, AZ 48.0 Dallas-Fort Worth-Arlington, TX 47.5 Miami-Fort Lauderdale-Pompano Beach, FL 45.3 Seattle-Tacoma-Bellevue, WA 45.3 Albuquerque, NM 44.8

Source: Brookings Institution analysis of ZIP Business Patterns data

by mountains and water, but it has also adopted urban growth boundaries to manage development. Salt Lake City, another region constrained by geography, has actively pursued denser forms of development in recent years and become a leader in transit-oriented development.

BROOKINGS | April 2013 9 To be sure, not all job decentralization is created equal. Traditional depictions of “sprawl” focus on patterns of diffuse, low-density greenfield development at the fringes of metropolitan regions, whether they are actually growing overall or just growing outward as populations decline. But many regions are seeing suburban development occurring in denser ways—whether in new places or through retrofitting older communities—that can, for instance, facilitate transit connections. Among the 100 largest metro areas, 42 have at least half of their jobs in high-density ZIP codes.16 And for many of these regions, a sizeable share of metro area jobs locate in high-density ZIP codes outside the urban core (Table 6). In the Los Angeles metro area, three-quarters of regional jobs fell in high-density ZIP codes more than three miles from downtown, while regions including San Diego, Chicago, and New York had more than half of their jobs in such ZIP codes. Moreover, Detroit, which topped the list for the most decentralized metro area, also ranks among the top 10 for the density of employment outside the urban core. At the other end of the spectrum, regions such as Augusta, GA; Chattanooga, TN; Greensboro, NC; Lakeland, FL; Poughkeepsie, NY; and Worcester, MA have no high job-density ZIP codes more than three miles from their downtowns. In those places, connecting people to jobs and transit may pose greater challenges than in more densely developed metro areas. (For detailed results, see Appendix D.)

Conclusion

he Great Recession led to net job losses in almost every major metro area and almost every major industry between 2007 and 2010. On the whole, these losses were felt throughout metropolitan regions—from the urban core to the metropolitan fringe. However, the housing- led downturn took the greatest toll on jobs outside the urban core, particularly those located Tmore than 10 miles away from downtown and those in the construction, manufacturing, and retail industries. The severity of the recession, and especially steep outer-ring job losses, helped drive a slight uptick in urban core job share in more than half of the nation’s largest metro areas between 2007 and 2010. Most of these increases reflect a rebalancing of the distribution as regions shed jobs, rather than actual job gains in the urban core. On the whole the magnitude of these recession-era changes was modest enough that they served to stall decentralization, not reverse longer-running trends: By 2010, 91 metro areas located a smaller share of employment within three miles of downtown compared to 2000, as job share shifted outward toward the middle ring and metropolitan fringe. These trends suggest that, as the economy recovers, the outward shift of employment will also likely resume within most major metro areas. However, efforts to encourage denser forms of suburban development and to attract jobs to the urban core have accelerated in recent years in regions like Boston, Chicago, Dallas, Denver, Minneapolis, San Francisco, and Washington, D.C. Such actions could succeed in eventually stemming longer-running trends toward decentralization in these regions, though it may be some time before the ultimate impact of these measures can be determined. In the wake of the Great Recession, policymakers and regional leaders have the opportunity to make strategic decisions about how they will pursue metropolitan growth. If the next period of economic expansion ushers in low-density, diffuse growth in metropolitan America, the negative consequences of decentralization will make it that much harder for metro areas to achieve sustainable and inclusive growth over the long term. On the other hand, denser forms of development, whether inside or outside of traditional downtowns, allow for more effective connections between people and jobs, as do comprehensive development plans that explicitly link up jobs, housing, and transportation. Because the location of employment relates to so many aspects of a metro area’s growth and performance, land use, zoning, and economic development strategies should be balanced with housing and transportation planning to ensure that regions are not just growing more jobs or better jobs, but they are locating jobs in ways that promote accessibility and connection.

10 BROOKINGS | April 2013 Endnotes 10. Based on density and job totals, the CBDs for six places— four primary CBDs (Las Vegas, Little Rock, Honolulu, and 1. Elizabeth Kneebone, “Job Sprawl Revisited: The Changing Nashville) and two secondary CBDs (Newport News and Geography of Metropolitan Employment” (Washington: Sunnyvale)—were changed away from the 1982 CBD. Brookings Institution, 2009). 11. See www.census.gov/geo/www/cbd.html. 2. Analysis of U.S. Bureau of Labor Statistics data, December 2007 to December 2010. 12. ZIP business patterns “classifies an establishment by its physical location”, thus employees may be 3. Robert Cervero, Yoshifumi Komada, and Andrew Krueger, allocated to the address of the main office, though “Suburban Transformations: From Employment Centers they work at project sites away from headquarters. to Mixed-Use Activity Centers,” University of California See www.census.gov/econ/cbp/methodology.htm. Working Paper (Berkeley, CA: 2010). 13. The three exceptions were the Texas metro areas of 4. For a more detailed review of the literature on these Austin, El Paso, and McAllen, each of which managed to effects, see Kneebone, “Job Sprawl Revisited.” weather this period with modest job gains within 35 miles of a CBD. 5. The data exclude information on the self-employed population, employees of private households, railroad 14. As noted in the methods section, bounding the analysis at employees, agricultural production workers, and most 35 miles helps to standardize measures across places of government employees. different physical size. In 2009, the correlation between share of jobs in the 10 to 35 mile ring and metropolitan 6. The 35 mile buffer captures 95 percent of all jobs located land area was fairly weak (0.34), and the correlation within the 100 largest metro areas. It serves to bound the between land area and change in outer-ring job share analysis and helps standardize measures across metro over the decade even weaker (0.26). areas of differing geographic size. For detailed explana- tions of the data cleaning and allocation process, see 15. Edward Glaeser, Matthew Khan, and Chenghuan Chu, “Job Kneebone, “Job Sprawl Revisited.” Sprawl: Employment Location in U.S. Metropolitan Areas” (Washington: Brookings Institution, 2001). 7. The metro areas included in the 2009 analysis that do not appear in this analysis include: Durham, NC; 16. “High-density” ZIP codes rank within the top quartile of Lansing-East Lansing, MI; Lexington-Fayette, KY; Portland- all metropolitan ZIP codes and have at least 1,330 jobs per South Portland-Biddeford, ME; and Trenton-Ewing, NJ. square mile. The metro areas appearing in this analysis that were not included in 2009 are: Lakeland-Winter Haven, FL; McAllen-Edinburg-Mission, TX; Modesto, CA; Ogden- Clearfield, UT; Palm Bay-Melbourne-Titusville, FL; Provo-Orem, UT; and Bridgeport-Stamford-Norwalk, CT.

8. Job density and total employment figures in 2010 come from Nielsen’s Business Facts database, and are provided at the census tract level, consistent with boundaries drawn based on Census 2000.

9. Three metro areas had first-named cities that did not have a defined CBD in 1982: Palm Bay, Virginia Beach, and North Port. For these cities, the densest tract based on 2010 job counts was selected as the primary CBD. The 1982 Census of Retail Trade used 1980 census tracts to designate CBDs. In cases where the 1982 CBDs were maintained, 1980 and 2000 census tracts were mapped together to identify the corresponding tracts in 2000, so that all CBDs used in the analysis are drawn from the same base year.

BROOKINGS | April 2013 11 Appendix A. List of Central Business Districts by Metro Area, 2010

Metro Area CBD City CBD Type*

Akron, OH Akron, Ohio Primary Albany-Schenectady-Troy, NY Albany, New York Primary Albany-Schenectady-Troy, NY Schenectady, New York Secondary Albuquerque, NM Albuquerque, New Mexico Primary Allentown-Bethlehem-Easton, PA-NJ Allentown, Pennsylvania Primary Allentown-Bethlehem-Easton, PA-NJ Easton, Pennsylvania Secondary Allentown-Bethlehem-Easton, PA-NJ Bethlehem, Pennsylvania Secondary Atlanta-Sandy Springs-Marietta, GA Atlanta, Georgia Primary Augusta-Richmond County, GA-SC Augusta, Georgia Primary Austin-Round Rock-San Marcos, TX Austin, Texas Primary Bakersfield-Delano, CA Bakersfield, California Primary Baltimore-Towson, MD Baltimore, Maryland Primary Baton Rouge, LA Baton Rouge, Louisiana Primary Birmingham-Hoover, AL Birmingham, Alabama Primary Boise City-Nampa, ID Boise City, Idaho Primary Boston-Cambridge-Quincy, MA-NH Boston, Massachusetts Primary Bridgeport-Stamford-Norwalk, CT Bridgeport, Connecticut Primary Bridgeport-Stamford-Norwalk, CT Danbury, Connecticut Secondary Bridgeport-Stamford-Norwalk, CT Norwalk, Connecticut Secondary Bridgeport-Stamford-Norwalk, CT Stamford Connecticut Secondary Buffalo-Niagara Falls, NY Buffalo, New York Primary Cape Coral-Fort Myers, FL Cape Coral, Florida Primary Cape Coral-Fort Myers, FL Fort Myers, Florida Secondary Charleston-North Charleston-Summerville, SC Charleston, South Carolina Primary Charlotte-Gastonia-Rock Hill, NC-SC Charlotte, North Carolina Primary Chattanooga, TN-GA Chattanooga, Tennessee Primary Chicago-Naperville-Joliet, IL-IN-WI Chicago, Illinois Primary Cincinnati-Middletown, OH-KY-IN Cincinnati, Ohio Primary Cleveland-Elyria-Mentor, OH Cleveland, Ohio Primary Colorado Springs, CO Colorado Springs, Colorado Primary Columbia, SC Columbia, South Carolina Primary Columbus, OH Columbus, Ohio Primary Dallas-Fort Worth-Arlington, TX Dallas, Texas Primary Dallas-Fort Worth-Arlington, TX Forth Worth, Texas Secondary Dayton, OH Dayton, Ohio Primary Denver-Aurora-Broomfield, CO Denver, Colorado Primary Des Moines-West Des Moines, IA Des Moines, Iowa Primary Detroit-Warren-Livonia, MI Detroit, Michigan Primary El Paso, TX El Paso, Texas Primary Fresno, CA Fresno, California Primary Grand Rapids-Wyoming, MI Grand Rapids, Michigan Primary Greensboro-High Point, NC Greensboro, North Carolina Primary Greensboro-High Point, NC High Point, North Carolina Secondary Greenville-Mauldin-Easley, SC Greenville, South Carolina Primary Harrisburg-Carlisle, PA Harrisburg, Pennsylvania Primary Hartford-West Hartford-East Hartford, CT Hartford, Connecticut Primary Honolulu, HI Honolulu, Hawaii Primary Houston-Sugar Land-Baytown, TX Houston, Texas Primary

12 BROOKINGS | April 2013 Appendix A. List of Central Business Districts by Metro Area, 2010 (continued)

Metro Area CBD City CBD Type*

Indianapolis-Carmel, IN Castleton, Indiana Primary Jackson, MS Jackson, Mississippi Primary Jacksonville, FL Jacksonville city, Florida Primary Kansas City, MO-KS Kansas City, Missouri Primary Knoxville, TN Knoxville, Tennessee Primary Lakeland-Winter Haven, FL Lakeland, Florida Primary Lakeland-Winter Haven, FL Winter Haven, Florida Secondary Lancaster, PA Lancaster, Pennsylvania Primary Las Vegas-Paradise, NV Las Vegas, Nevada Primary Little Rock-North Little Rock-Conway, AR Little Rock, Arkansas Primary Los Angeles-Long Beach-Santa Ana, CA Los Angeles, California Primary Los Angeles-Long Beach-Santa Ana, CA Long Beach, California Secondary Louisville/Jefferson County, KY-IN Louisville, Kentucky Primary Madison, WI Madison, Wisconsin Primary McAllen-Edinburg-Mission, TX McAllen, Texas Primary Memphis, TN-MS-AR Memphis, Tennessee Primary Miami-Fort Lauderdale-Pompano Beach, FL Miami, Florida Primary Miami-Fort Lauderdale-Pompano Beach, FL Fort Lauderdale, Florida Secondary Miami-Fort Lauderdale-Pompano Beach, FL Hollywood, Florida Secondary Miami-Fort Lauderdale-Pompano Beach, FL Pompano Beach, Florida Secondary Miami-Fort Lauderdale-Pompano Beach, FL West Palm Beach, Florida Secondary Milwaukee-Waukesha-West Allis, WI Milwaukee, Wisconsin Primary Minneapolis-St. Paul-Bloomington, MN-WI Minneapolis, Minnesota Primary Minneapolis-St. Paul-Bloomington, MN-WI St. Paul, Minnesota Secondary Modesto, CA Modesto, California Primary Nashville-Davidson-Murfreesboro-Franklin, TN Nashville-Davidson (consolidated) city, TN Primary Nashville-Davidson-Murfreesboro-Franklin, TN Berry Hill, Tennessee Secondary New Haven-Milford, CT New Haven, Connecticut Primary New Haven-Milford, CT Milford, Connecticut Secondary New Haven-Milford, CT Waterbury, Connecticut Secondary New Orleans-Metairie-Kenner, LA New Orleans, Louisiana Primary New York-Northern New Jersey-Long Island, NY-NJ-PA New York, New York Primary North Port-Bradenton-Sarasota, FL North Port, Florida Primary North Port-Bradenton-Sarasota, FL Bradenton, Florida Secondary North Port-Bradenton-Sarasota, FL Sarasota, Florida Secondary Ogden-Clearfield, UT Ogden, Utah Primary Oklahoma City, OK Oklahoma City, Oklahoma Primary Omaha-Council Bluffs, NE-IA Omaha, Nebraska Primary Orlando-Kissimmee-Sanford, FL Orlando, Florida Primary Oxnard-Thousand Oaks-Ventura, CA Oxnard, California Primary Oxnard-Thousand Oaks-Ventura, CA San Buenaventura (Ventura), California Secondary Oxnard-Thousand Oaks-Ventura, CA Thousand Oaks, California Secondary Palm Bay-Melbourne-Titusville, FL Palm Bay city, Florida Primary Palm Bay-Melbourne-Titusville, FL Cocoa, Florida Secondary Palm Bay-Melbourne-Titusville, FL Titusville, Florida Secondary Philadelphia-Camden-Wilmington, PA-NJ-DE-MD Philadelphia, Pennsylvania Primary Phoenix-Mesa-Glendale, AZ Phoenix, Arizona Primary Pittsburgh, PA Pittsburgh, Pennsylvania Primary

BROOKINGS | April 2013 13 Appendix A. List of Central Business Districts by Metro Area, 2010 (continued)

Metro Area CBD City CBD Type*

Portland-Vancouver-Hillsboro, OR-WA Portland, Oregon Primary Poughkeepsie-Newburgh-Middletown, NY Poughkeepsie, New York Primary Poughkeepsie-Newburgh-Middletown, NY Middletown, New York Secondary Poughkeepsie-Newburgh-Middletown, NY Newburgh, New York Secondary Providence-New Bedford-Fall River, RI-MA Providence, Rhode Island Primary Provo-Orem, UT Provo, Utah Primary Raleigh-Cary, NC Raleigh, North Carolina Primary Richmond, VA Richmond, Virginia Primary Riverside-San Bernardino-Ontario, CA Riverside, California Primary Riverside-San Bernardino-Ontario, CA San Bernardino, California Secondary Rochester, NY Rochester, New York Primary Sacramento-Arden-Arcade-Roseville, CA Sacramento, California Primary St. Louis, MO-IL St. Louis, Missouri Primary Salt Lake City, UT Salt Lake City, Utah Primary San Antonio-New Braunfels, TX San Antonio, Texas Primary San Diego-Carlsbad-San Marcos, CA San Diego, California Primary San Francisco-Oakland-Fremont, CA San Francisco, California Primary San Jose-Sunnyvale-Santa Clara, CA San Jose, California Primary San Jose-Sunnyvale-Santa Clara, CA Palo Alto, California Secondary San Jose-Sunnyvale-Santa Clara, CA Sunnyvale, California Secondary Scranton-Wilkes-Barre, PA Scranton, Pennsylvania Primary Scranton-Wilkes-Barre, PA Wilkes-Barre, Pennsylvania Secondary Seattle-Tacoma-Bellevue, WA Seattle, Washington Primary Seattle-Tacoma-Bellevue, WA Bellevue, Washington Secondary Springfield, MA Springfield, Massachusetts Primary Stockton, CA Stockton, California Primary Syracuse, NY Syracuse, New York Primary Tampa-St. Petersburg-Clearwater, FL Tampa, Florida Primary Tampa-St. Petersburg-Clearwater, FL St. Petersburg, Florida Secondary Toledo, OH Toledo, Ohio Primary Tucson, AZ Tucson, Arizona Primary Tulsa, OK Tulsa, Oklahoma Primary Virginia Beach-Norfolk-Newport News, VA-NC Virginia Beach city, Virginia Primary Virginia Beach-Norfolk-Newport News, VA-NC Newport News, Virginia Secondary Virginia Beach-Norfolk-Newport News, VA-NC Norfolk, Virginia Secondary Washington-Arlington-Alexandria, DC-VA-MD-WV Washington, District Of Columbia Primary Wichita, KS Wichita, Kansas Primary Worcester, MA Worcester, Massachusetts Primary Youngstown-Warren-Boardman, OH-PA Youngstown, Ohio Primary Youngstown-Warren-Boardman, OH-PA Warren, Ohio Secondary

*Primary CBDs are those located in the city that appears first in the official metropolitan statistical area name.

14 BROOKINGS | April 2013 4.3 35 43.1 30.9 17.0 13.4 14.4 64.6 32.2 36.9 16.9 50.2 31.1 32.5 24.4 47.2 30.6 21.1 38.1 43.0 24.0 67.4 52.8 46.5 14.8 28.0 35.4 57.5 22.0 36.7 11.0 77.4 23.9 14.4 10 to Miles Share Jobs of 34.1 44.3 46.7 59.9 35.2 25.6 43.0 38.8 42.8 32.3 53.8 36.2 36.2 23.6 38.1 51.3 43.3 40.2 33.5 43.5 13.1 29.5 38.1 52.2 41.9 43.4 29.2 53.4 41.8 51.5 15.3 57.6 62.5 CBD from Miles Share 10 3 to Jobs of 2010 9.9 7.3 22.9 24.9 36.3 26.7 50.3 24.8 24.3 40.2 17.5 15.1 31.3 39.4 29.2 57.6 18.1 35.6 21.7 23.5 32.6 19.5 17.7 15.4 33.0 30.1 21.2 13.3 24.5 21.5 37.5 18.5 23.1 Share Within CBD of 3 Miles Jobs of CBD Total 266,493 323,123 277,353 283,287 160,538 631,816 156,459 307,698 414,679 207,996 393,311 455,929 166,266 225,812 720,823 193,005 857,640 831,701 215,371 263,269 740,704 307,773 269,251 207,143 219,802 Jobs of of Miles Number 35 Within 1,864,067 1,045,722 2,041,857 3,374,483 2,436,904 1,034,107 1,380,896 73,247,962 4.0 43.2 32.0 16.8 14.3 15.0 65.0 35.0 36.6 16.3 50.0 30.1 31.2 25.3 47.7 30.0 18.1 37.6 41.5 24.7 69.0 53.9 46.3 14.0 27.9 35.0 56.2 21.7 36.5 10.8 77.4 22.3 13.6 CBD from Miles Share Jobs of 35 10 to 34.1 44.1 47.5 60.3 34.0 25.5 40.3 40.4 43.3 32.7 53.6 36.3 35.0 23.3 38.7 51.9 43.2 42.4 34.4 45.2 13.1 29.9 38.0 51.9 42.2 44.0 30.0 54.0 42.2 50.4 15.4 57.8 63.8 CBD from Miles Share 10 3 to Jobs of 2007 9.5 7.2 22.6 23.9 35.7 25.4 51.1 24.7 23.0 40.5 17.3 16.3 32.5 39.6 29.0 57.3 18.0 38.7 20.0 24.1 30.1 17.9 16.1 15.7 34.1 29.9 21.1 13.8 24.4 21.4 38.7 19.9 22.7 Share Within CBD of 3 Miles Jobs of 293,371 336,991 309,033 302,867 179,766 630,272 167,382 317,525 459,685 236,337 427,951 468,209 198,147 244,300 803,809 213,920 907,870 927,713 235,541 283,911 782,270 339,849 283,712 204,234 247,005 CBD Total 2,052,759 1,116,610 2,137,135 3,674,306 2,544,069 1,107,774 1,594,982 Jobs of of Miles Number 79,071,521 35 Within 3.5 9.6 40.9 29.1 15.3 11.4 16.0 60.4 35.2 29.0 16.8 45.5 28.4 26.9 23.7 47.7 28.3 14.8 32.5 37.8 24.3 67.7 49.5 43.0 25.0 30.4 49.7 19.6 30.9 10.1 76.1 17.8 14.8 CBD from Miles Share Jobs of 35 10 to 34.6 43.6 47.3 60.8 31.3 29.3 38.6 44.0 37.6 35.3 53.0 37.1 25.9 24.0 37.6 50.1 40.0 41.6 36.8 42.5 13.8 30.8 39.6 52.7 41.4 45.9 34.4 52.0 45.5 43.7 16.6 60.7 59.2 CBD from Miles Share 10 3 to Jobs of 2000 7.3 24.5 27.3 37.4 27.8 52.7 10.3 26.2 27.0 45.5 19.3 18.6 36.0 50.4 28.3 58.9 21.6 45.2 25.9 25.4 33.2 18.5 19.7 17.5 37.8 33.6 23.7 15.9 28.4 23.6 46.1 21.5 26.0 Share Within CBD of 3 Miles Jobs of Total 303,705 319,153 275,640 285,564 177,013 546,507 132,020 282,281 447,304 193,940 441,800 476,004 143,037 214,923 714,498 214,879 934,485 215,142 266,628 790,312 379,383 259,866 199,847 206,009 Miles CBD of Jobs of Number 1,983,368 1,017,497 2,172,971 3,803,451 1,041,380 2,489,338 1,067,547 1,856,487 35 Within 76,252,828 Area Metro 100 METRO TOTAL OH Akron, NY Albany-Schenectady-Troy, NM Albuquerque, PA-NJ Allentown-Bethlehem-Easton, GA Springs-Marietta, Atlanta-Sandy GA-SC County, Augusta-Richmond TX Marcos, Rock-San Austin-Round CA Bakersfield-Delano, MD Baltimore-Towson, LA Rouge, Baton AL Birmingham-Hoover, ID City-Nampa, Boise MA-NH Boston-Cambridge-Quincy, CT Bridgeport-Stamford-Norwalk, NY Falls, Buffalo-Niagara FL Myers, Coral-Fort Cape SC Summerville, Charleston, Charleston-North Hill, NC-SC Charlotte-Gastonia-Rock TN-GA Chattanooga, IL-IN-WI Chicago-Joliet-Naperville, OH-KY-IN Cincinnati-Middletown, OH Cleveland-Elyria-Mentor, CO Springs, Colorado SC Columbia, OH Columbus, TX Worth-Arlington, Dallas-Fort OH Dayton, CO Denver-Aurora-Broomfield, IA Moines, Des Moines-West Des MI Detroit-Warren-Livonia, TX El Paso, CA Fresno, Appendix B. Geographic Distribution of Jobs in the 100 Largest Metro Areas, 2000-2010 in the 100 Largest Metro of Jobs Appendix B. Geographic Distribution

BROOKINGS | April 2013 15 8.6 9.3 8.5 35 15.2 20.6 23.1 27.0 34.8 17.8 57.2 40.1 17.7 37.8 53.3 45.2 17.0 31.4 29.9 55.9 19.6 16.2 19.6 48.4 25.2 37.8 33.4 23.8 44.3 18.3 24.0 46.1 31.4 29.0 16.1 44.9 10 to Miles Share Jobs of 58.7 47.2 43.6 41.1 41.4 28.3 32.1 40.5 46.8 41.2 29.9 36.2 47.7 37.4 46.9 35.5 34.2 51.5 53.7 46.8 39.2 50.5 38.1 41.5 30.7 28.7 36.4 44.5 23.0 50.3 38.0 44.6 60.6 42.4 44.1 CBD from Miles Share 10 3 to Jobs of 2010 9.9 26.0 32.2 33.3 31.8 23.8 53.9 10.7 19.5 35.5 21.0 16.9 18.6 35.3 31.2 44.6 34.5 28.9 30.1 33.6 12.4 24.3 24.1 25.1 45.5 27.0 45.3 31.6 30.9 40.4 30.6 26.4 23.3 12.8 47.4 Share Within CBD of 3 Miles Jobs of CBD Total 307,195 294,641 247,348 258,775 515,407 335,929 732,061 194,394 453,213 831,452 284,256 158,959 207,280 712,598 271,753 507,568 252,870 167,167 490,626 731,212 121,468 625,265 311,869 424,539 198,338 142,183 435,233 393,547 844,450 238,637 Jobs of of Miles Number 35 Within 2,020,868 4,719,962 1,809,699 1,530,794 6,437,814 8.0 8.9 8.5 15.4 20.9 23.2 27.2 34.9 16.5 56.2 39.3 18.3 36.6 52.5 44.5 16.7 31.3 28.1 56.3 20.3 16.7 19.6 48.2 24.8 38.3 33.6 24.1 44.0 18.3 23.8 47.1 32.1 27.5 15.8 43.9 CBD from Miles Share Jobs of 35 10 to 58.8 46.7 43.7 40.8 40.6 28.1 32.3 41.4 45.2 41.7 30.5 36.4 49.0 38.1 47.5 35.2 34.2 52.7 54.1 45.3 39.7 50.5 39.0 42.5 30.1 29.1 35.7 46.5 22.2 51.5 38.3 46.8 59.8 43.0 44.4 CBD from Miles Share 10 3 to Jobs of 2007 9.5 25.8 32.4 33.1 32.1 24.5 55.4 11.5 19.3 36.5 21.7 17.0 19.0 34.3 30.7 44.5 36.6 27.1 29.2 35.1 12.2 24.7 22.6 24.0 45.8 26.9 46.0 29.8 30.7 39.6 29.6 25.7 24.3 13.1 47.1 Share Within CBD of 3 Miles Jobs of 340,138 328,844 275,655 270,753 554,100 357,636 781,476 204,844 514,623 888,255 305,068 174,455 218,878 841,954 292,663 541,477 265,301 160,977 531,553 788,352 139,019 687,997 343,045 434,206 228,787 156,159 461,959 398,162 935,709 277,707 CBD Total 2,076,874 5,194,610 2,025,204 1,648,302 6,793,961 Jobs of of Miles Number 35 Within 7.0 7.8 8.4 13.9 21.7 22.5 26.3 33.7 13.6 49.4 33.1 12.0 31.2 48.0 41.8 16.3 31.8 25.9 55.8 16.8 18.2 20.4 41.5 21.6 35.4 29.4 24.0 38.1 17.8 18.0 47.0 29.3 21.8 11.8 37.9 CBD from Miles Share Jobs of 35 10 to 57.7 42.8 39.1 39.8 39.4 30.7 36.6 44.5 42.3 44.0 31.5 36.3 43.6 36.0 42.1 40.3 34.2 53.0 48.3 36.2 44.9 51.7 42.0 44.5 23.8 31.9 35.2 48.3 21.4 40.4 32.3 49.4 61.1 46.5 44.2 CBD from Miles Share 10 3 to Jobs of 2000 28.3 35.6 38.4 34.0 27.0 55.7 14.0 22.3 45.6 24.7 20.5 21.9 40.1 32.2 50.9 33.8 10.0 30.2 33.5 43.4 13.6 26.7 22.6 26.1 52.2 30.0 47.0 33.8 31.5 51.9 38.3 28.8 27.1 15.6 47.4 Share Within CBD of 3 Miles Jobs of Total 355,313 340,253 284,273 255,942 557,094 316,532 771,115 208,677 455,009 877,876 275,146 161,979 213,295 615,490 282,888 545,865 236,342 114,903 547,167 784,375 120,253 633,843 337,944 509,337 239,670 133,264 420,702 380,659 799,534 242,819 Miles CBD of Jobs of Number 1,818,667 5,144,060 1,910,885 1,592,547 6,766,972 35 Within Area Metro MI Rapids-Wyoming, Grand NC Point, Greensboro-High SC Greenville-Mauldin-Easley, PA Harrisburg-Carlisle, CT Hartford, Hartford-East Hartford-West Honolulu, HI TX Land-Baytown, Houston-Sugar IN Indianapolis, MS Jackson, FL Jacksonville, MO-KS City, Kansas TN Knoxville, FL Haven, Lakeland-Winter PA Lancaster, NV Las Vegas-Paradise, AR Conway, Rock, Little Rock-North Little Ana, CA Beach-Santa Angeles-Long Los KY-IN County, Louisville-Jefferson WI Madison, TX McAllen-Edinburg-Mission, TN-MS-AR Memphis, FL Beach, Lauderdale-Pompano Miami-Fort WI Allis, Milwaukee-Waukesha-West MN-WI Paul-Bloomington, Minneapolis-St. CA Modesto, TN Nashville-Davidson-Murfreesboro-Franklin, CT Haven-Milford, New LA Orleans-Metairie-Kenner, New Island, NY -NJ-PA Jersey-Long New York-Northern New FL North Port-Bradenton-Sarasota, UT Ogden-Clearfield, OK Oklahoma City, NE-IA Bluffs, Omaha-Council FL Orlando-Kissimmee-Sanford, CA Oaks-Ventura, Oxnard-Thousand Appendix B. Geographic Distribution of Jobs in the 100 Largest Metro Areas, 2000-2010 (continued) in the 100 Largest Metro of Jobs Appendix B. Geographic Distribution

16 BROOKINGS | April 2013 7.3 4.2 35 64.0 46.0 45.2 29.5 24.5 49.6 26.6 31.5 33.4 56.2 22.0 46.3 61.2 30.6 33.7 53.1 55.4 19.8 45.6 29.1 38.2 21.7 34.8 21.4 16.0 25.5 14.4 47.1 14.0 44.1 27.5 10 to Miles Share Jobs of 50.5 20.8 35.9 29.5 46.8 38.3 28.7 39.6 53.1 47.0 31.6 47.3 35.2 25.6 37.6 52.4 34.6 19.5 31.9 33.7 27.0 38.1 31.3 40.5 45.0 54.8 64.8 55.2 53.2 31.0 49.7 24.9 45.1 CBD from Miles Share 10 3 to Jobs of 2010 42.2 15.2 18.1 25.2 23.8 37.2 21.7 33.8 15.4 19.6 12.3 30.7 18.5 13.2 31.8 13.8 12.3 25.2 64.0 46.5 27.4 32.8 30.5 37.8 20.2 23.8 19.2 19.3 32.4 21.8 36.3 31.0 27.3 Share Within CBD of 3 Miles Jobs of CBD Total 166,033 981,789 863,135 196,855 582,629 142,681 406,506 465,268 791,754 397,181 586,318 522,087 702,726 838,902 227,421 224,714 160,037 245,149 905,865 250,628 301,467 356,112 584,420 250,118 270,450 198,787 Jobs of of Miles Number 35 Within 2,309,658 1,412,678 1,083,419 1,041,789 1,747,221 1,383,910 2,165,605 6.8 4.4 63.8 44.5 45.3 30.3 24.4 49.5 24.9 31.5 32.9 56.6 21.3 47.4 61.6 31.5 32.0 53.8 57.0 20.4 48.8 27.9 38.4 21.7 35.6 21.6 14.7 24.7 14.2 47.6 13.9 43.9 27.8 CBD from Miles Share Jobs of 35 10 to 51.1 20.9 36.7 28.7 45.3 38.7 29.0 40.6 52.9 47.0 31.2 48.1 35.3 24.8 37.4 53.8 34.6 18.9 33.1 34.5 25.1 39.4 30.2 40.9 44.3 53.9 65.0 56.3 52.5 31.2 50.1 24.5 46.0 CBD from Miles Share 10 3 to Jobs of 2007 42.1 15.3 18.8 25.9 24.4 36.9 21.5 34.5 15.6 20.1 12.2 30.6 17.3 13.6 31.1 14.2 11.6 24.1 62.5 45.2 26.1 32.7 31.4 37.4 20.1 24.6 20.3 19.0 33.3 21.2 36.0 31.6 26.2 Share Within CBD of 3 Miles Jobs of 183,752 926,786 204,041 638,508 150,609 428,381 512,435 940,505 417,471 680,229 563,426 707,291 906,190 237,854 230,659 177,762 253,863 994,529 277,422 330,765 378,023 630,470 256,625 292,394 214,239 CBD Total 2,457,437 1,660,229 1,013,025 1,168,959 1,130,030 1,893,415 1,498,013 2,248,179 Jobs of of Miles Number 35 Within 5.9 3.4 61.5 35.2 44.1 26.4 23.1 48.6 20.3 25.7 28.3 55.6 19.7 41.8 57.6 24.1 24.3 51.5 57.1 19.7 47.1 25.2 36.4 21.4 33.9 18.9 10.2 20.1 12.7 45.5 12.9 43.7 25.8 CBD from Miles Share Jobs of 35 10 to 50.3 21.8 40.0 29.7 47.5 37.2 29.0 40.5 56.1 50.3 29.6 45.5 38.6 27.5 39.9 56.5 34.8 17.7 34.3 32.1 24.9 40.2 27.5 40.2 45.0 54.8 67.0 55.1 52.5 32.7 49.1 23.7 44.0 CBD from Miles Share 10 3 to Jobs of 2000 43.8 16.7 24.8 26.2 26.1 39.7 22.4 39.2 18.2 21.4 14.8 34.8 19.6 14.9 36.0 19.2 13.7 25.2 62.3 48.2 28.1 34.6 36.1 38.4 21.1 26.2 22.8 24.8 34.8 21.7 38.0 32.6 30.2 Share Within CBD of 3 Miles Jobs of Total 157,417 860,172 182,994 603,488 135,049 367,111 480,379 705,966 426,067 579,560 497,017 623,492 987,478 231,855 235,675 153,433 267,548 997,557 285,719 292,048 365,158 576,871 257,502 293,779 237,221 Miles CBD of Jobs of Number 2,440,502 1,351,956 1,005,045 1,149,391 1,003,940 1,990,334 1,407,401 2,001,037 35 Within Area Metro FL Bay-Melbourne-Titusville, Palm PA-NJ-DE-MD Philadelphia-Camden-Wilmington, AZ Phoenix-Mesa-Glendale, PA Pittsburgh, OR Portland-Vancouver-Hillsboro, NY Poughkeepsie-Newburgh-Middletown, RI-MA River, Bedford-Fall Providence-New UT Provo-Orem, NC Raleigh-Cary, Richmond, VA CA Bernardino-Ontario, Riverside-San NY Rochester, CA Sacramento-Arden-Arcade-Roseville, MO-IL Louis, St. UT City, Lake Salt SC Antonio-Mauldin-Easley, San CA Marcos, Diego-Carlsbad-San San CA Francisco-Oakland-Fremont, San CA Clara, Jose-Sunnyvale-Santa San PA Scranton-Wilkes-Barre, WA Seattle-Tacoma-Bellevue, Springfield, MA CA Stockton, NY Syracuse, FL Petersburg-Clearwater, Tampa-St. OH Toledo, AZ Tucson, OK Tulsa, VA-NC News, Beach-Norfolk-Newport Virginia DC-VA-MD-WV Washington-Arlington-Alexandria, KS Wichita, MA Worcester, OH-PA Youngstown-Warren-Boardman, Appendix B. Geographic Distribution of Jobs in the 100 Largest Metro Areas, 2000-2010 (continued) in the 100 Largest Metro of Jobs Appendix B. Geographic Distribution

BROOKINGS | April 2013 17 1.7 1.6 1.9 4.2 7.9 0.1 4.8 2.7 5.6 0.7 0.8 2.3 6.3 5.6 5.2 3.3 3.5 5.2 3.0 5.0 7.7 2.5 5.8 0.9 1.3 6.1 1.3 0.6 2.2 -1.6 -2.9 -0.4 -0.3 -0.3 -0.5 -1.1 35 10 to Miles Share Jobs of 0.7 3.9 4.4 5.2 0.8 0.5 1.2 3.3 1.0 0.5 1.5 7.7 3.3 1.0 4.4 4.4 -0.6 -0.8 -3.8 -5.2 -3.0 -0.9 -0.4 -1.4 -3.2 -0.7 -1.4 -1.4 -0.4 -2.4 -5.1 -3.6 -1.4 -3.1 -0.5 10.2 CBD Share 10 3 to Jobs of from Miles 0.9 1.0 0.0 -2.5 -1.1 -1.1 -2.4 -0.4 -1.4 -2.7 -5.3 -1.8 -3.5 -4.7 -1.3 -3.6 -9.6 -4.2 -2.0 -0.6 -1.9 -2.1 -4.8 -3.5 -2.5 -2.6 -3.9 -2.1 -8.6 -3.0 -2.8 -2.3 -3.3 -5.1 -1.7 -10.9 Share Within CBD of 3 Miles Jobs of Change 2000-2010 229 3,970 1,714 6,324 9,385 7,296 -2,277 -3,359 CBD 85,309 24,438 28,225 25,417 14,056 23,229 10,889 13,793 Total -37,213 -16,475 -32,625 -48,489 -20,075 -21,873 -76,845 -49,608 -52,434 -71,610 -33,440 -48,119 -45,612 -36,925 Jobs of of Miles Number -119,301 -131,114 -428,968 -209,680 -475,591 35 Within -3,004,866 0.2 0.3 0.7 0.2 1.1 1.3 0.3 0.6 3.0 0.5 1.5 0.2 0.8 0.1 0.4 1.3 0.4 0.2 0.2 0.1 1.6 0.8 -1.2 -0.9 -0.5 -0.5 -2.7 -1.0 -0.5 -0.7 -1.6 -1.1 -0.1 -0.3 -0.1 -0.2 CBD from Miles Share Jobs of 35 10 to 0.2 1.3 0.1 2.7 0.2 1.1 0.3 0.1 0.0 0.1 0.3 1.0 0.5 -0.8 -0.4 -1.6 -0.4 -0.5 -0.1 -0.6 -0.6 -2.2 -0.8 -1.8 -0.5 -0.3 -0.6 -0.8 -0.5 -0.4 -0.1 -0.2 -1.3 -0.1 -0.1 -0.1 CBD from Miles Share 10 3 to Jobs of 0.2 1.0 0.6 1.3 0.4 0.1 1.3 0.2 0.1 0.3 0.0 1.7 2.5 1.6 1.6 0.2 0.2 0.1 0.1 0.1 0.5 0.2 0.2 -0.7 -0.2 -1.3 -1.2 -0.2 -3.1 -0.6 -0.3 -1.1 -0.5 -1.2 -1.4 -0.2 Share Within CBD of 3 Miles Jobs of Change 2007-2010 1,544 2,909 -9,827 CBD Total -26,878 -13,868 -31,679 -19,580 -19,228 -10,924 -70,888 -45,005 -28,341 -95,278 -34,641 -12,280 -31,881 -18,488 -82,986 -20,915 -50,229 -96,013 -20,170 -20,642 -41,566 -32,076 -73,667 -14,460 -27,202 -32,944 -34,203 -28,307 Jobs of -188,691 -299,823 -107,165 -214,086 of Miles Number 35 Within -5,823,559 2.9 1.4 2.8 4.6 7.6 4.5 1.7 4.3 1.7 0.0 0.5 1.8 3.2 5.1 3.8 0.4 1.3 4.4 3.3 4.4 2.9 4.5 6.5 2.1 5.5 0.7 1.3 4.5 1.4 0.7 2.3 -1.0 -0.2 -0.6 -1.3 -0.8 CBD from Miles Share Jobs of 35 10 to 0.5 0.2 2.6 1.7 5.7 0.6 9.1 1.1 1.8 3.2 0.8 2.7 0.8 2.0 6.7 4.6 1.1 3.9 4.6 -0.4 -3.8 -3.6 -2.5 -0.8 -0.8 -2.4 -0.7 -0.9 -1.5 -0.7 -1.9 -4.4 -3.3 -1.2 -2.9 -0.5 CBD from Miles Share 10 3 to Jobs of 0.7 0.0 -3.4 -1.6 -2.4 -1.6 -0.8 -1.5 -4.0 -5.1 -2.0 -2.2 -3.5 -1.6 -3.6 -6.5 -5.8 -1.4 -3.1 -0.6 -3.5 -1.8 -3.7 -3.7 -2.7 -2.1 -4.1 -2.3 -7.4 -1.6 -3.3 -2.5 -3.2 -5.3 -1.9 -10.8 Miles Share CBD of Jobs of 3 Within Change 2000-2007 -959 2,753 4,387 -7,795 -8,042 -8,618 17,838 33,393 17,303 69,390 83,766 35,362 99,113 35,244 12,380 42,397 55,111 29,377 89,311 20,399 17,283 54,731 40,227 23,846 40,995 -10,334 -35,836 -13,848 -26,616 -39,534 -15,175 -11,409 Total -129,145 -113,667 -261,505 CBD of Miles 35 2,818,693 Number of Within Jobs Austin-Round Rock-San Marcos, TX Marcos, Rock-San Austin-Round Akron, OH Akron, NY Albany-Schenectady-Troy, NM Albuquerque, PA-NJ Allentown-Bethlehem-Easton, GA Springs-Marietta, Atlanta-Sandy GA-SC County, Augusta-Richmond CA BBakersfield-Delano, MD Baltimore-Towson, LA Rouge, Baton AL Birmingham-Hoover, ID City-Nampa, Boise MA-NH Boston-Cambridge-Quincy, CT Bridgeport-Stamford-Norwalk, NY Falls, Buffalo-Niagara FL Myers, Coral-Fort Cape SC Summerville, Charleston, Charleston-North Hill, NC-SC Charlotte-Gastonia-Rock TN-GA Chattanooga, IL-IN-WI Chicago-Joliet-Naperville, OH-KY-IN Cincinnati-Middletown, OH Cleveland-Elyria-Mentor, CO Springs, Colorado SC Columbia, OH Columbus, TX Worth-Arlington, Dallas-Fort OH Dayton, CO Denver-Aurora-Broomfield, IA Moines, Des Moines-West Des MI Detroit-Warren-Livonia, TX El Paso, CA Fresno, MI Rapids-Wyoming, Grand NC Point, Greensboro-High SC Greenville-Mauldin-Easley, Area Metro 100 METRO TOTAL Appendix C. Change in the Geographic Distribution of Jobs in the 100 Largest Metro Areas in the 100 Largest Metro of Jobs Appendix C. Change in the Geographic Distribution

18 BROOKINGS | April 2013 0.7 1.1 4.2 7.8 6.9 5.6 6.6 5.3 3.4 0.7 1.6 4.1 0.1 2.9 6.8 3.6 2.3 4.0 6.2 0.5 6.0 1.6 2.1 7.2 4.4 7.0 0.0 1.5 2.5 1.1 3.1 -0.4 -2.1 -0.8 -0.2 -0.9 35 10.8 10 to Miles Share Jobs of 1.4 2.1 4.4 4.1 1.4 4.8 0.0 5.4 6.9 1.2 1.6 9.9 5.6 0.2 -2.4 -4.5 -4.0 -2.8 -1.6 -0.1 -4.8 -1.5 -5.6 -1.2 -3.8 -3.0 -3.2 -3.8 -4.8 -0.5 -4.1 -0.1 -1.0 -4.0 -0.1 -0.8 10.6 CBD Share 10 3 to Jobs of from Miles 0.7 1.5 0.1 -2.1 -3.2 -1.8 -3.3 -2.9 -3.8 -3.6 -3.3 -4.8 -1.0 -6.4 -0.1 -1.3 -3.4 -9.8 -1.2 -2.4 -1.0 -6.7 -3.0 -1.7 -2.2 -0.7 -7.7 -2.4 -3.9 -2.8 -1.6 -1.5 -6.8 -0.9 -2.3 -10.1 -11.4 Share Within CBD of 3 Miles Jobs of Change 2000-2010 9,111 1,215 8,919 8,616 2,963 2,833 -1,796 -3,020 -6,015 -8,578 -4,182 CBD 19,397 97,108 16,528 52,264 14,531 12,887 44,916 60,723 Total -41,687 -39,053 -14,283 -46,424 -11,134 -38,296 -56,541 -53,163 -61,753 -26,075 -84,797 -41,333 -23,255 202,202 Jobs of of Miles Number -424,098 -101,187 -329,158 -130,844 35 Within 1.3 1.0 0.7 1.2 0.8 0.6 0.3 0.1 0.6 1.8 0.0 0.2 0.4 0.4 0.1 0.2 0.4 1.5 0.3 1.0 0.0 0.5 0.2 1.5 -0.1 -0.6 -0.4 -0.6 -0.6 -0.5 -0.2 -0.3 -0.9 -0.6 -0.1 -0.8 -0.2 CBD from Miles Share Jobs of 35 10 to 0.4 0.8 0.2 1.6 0.3 0.0 1.4 0.0 0.6 0.7 0.8 0.8 0.8 1.4 -0.2 -0.9 -0.5 -0.6 -0.2 -1.3 -0.7 -0.6 -1.2 -0.4 -0.4 -0.9 -0.9 -0.4 -2.0 -1.2 -0.3 -2.1 -0.7 -0.3 -0.6 -0.1 -0.8 CBD from Miles Share 10 3 to Jobs of 0.2 1.0 0.6 0.0 0.4 1.8 0.9 0.2 1.5 1.1 0.0 1.8 0.2 0.9 1.0 0.6 0.3 0.1 -0.7 -1.5 -0.8 -1.0 -0.7 -0.2 -0.4 -2.1 -1.4 -0.4 -0.3 -0.7 -1.1 -0.4 -0.1 -0.7 -0.7 -0.6 -0.2 Share Within CBD of 3 Miles Jobs of Change 2007-2010 6,191 -9,667 -4,615 CBD Total -11,978 -38,693 -21,707 -56,005 -49,414 -10,450 -61,409 -56,803 -20,811 -15,496 -11,598 -20,909 -33,909 -12,431 -40,927 -57,140 -17,551 -62,732 -31,175 -30,449 -13,977 -26,726 -91,259 -39,070 -17,719 -31,236 -63,651 Jobs of -129,355 -474,647 -215,505 -117,508 -356,147 -147,778 -247,551 of Miles Number 35 Within 1.2 3.0 6.8 6.2 6.2 5.4 4.5 2.8 0.4 1.0 2.2 0.5 3.5 6.7 3.2 2.9 4.2 0.1 5.9 0.5 5.8 0.0 1.2 2.7 5.7 4.1 6.0 0.1 1.0 2.3 9.3 1.2 3.9 0.9 -0.5 -1.5 -0.8 CBD from Miles Share Jobs of 35 10 to 1.3 2.8 0.1 5.3 2.1 5.4 0.0 5.8 9.2 6.3 0.5 0.8 6.0 0.2 0.8 1.0 -2.6 -4.3 -3.2 -2.3 -1.0 -5.1 -0.3 -5.2 -1.2 -2.9 -2.0 -2.8 -1.8 -2.7 -1.3 -3.5 -0.9 -3.2 -1.0 -2.2 11.1 CBD from Miles Share 10 3 to Jobs of 2.8 0.0 -2.5 -0.4 -2.5 -3.0 -9.1 -3.1 -3.5 -2.9 -5.8 -1.5 -6.4 -0.5 -3.1 -4.3 -8.4 -1.4 -2.0 -2.2 -6.4 -3.1 -1.0 -4.0 -0.8 -8.7 -3.1 -2.8 -2.5 -0.2 -1.7 -1.4 -6.0 -0.2 -1.7 -1.9 -12.3 Miles Share CBD of Jobs of 3 Within Change 2000-2007 5,583 9,775 3,977 5,100 7,981 -2,993 -3,833 -4,388 14,811 41,104 10,361 59,613 10,379 29,922 12,475 50,550 28,959 46,073 55,755 18,767 54,154 26,989 22,895 41,257 17,502 34,888 26,335 16,934 66,614 -15,614 -75,130 -10,883 Total 258,207 226,463 114,319 136,175 308,274 CBD of Miles 35 Number of Within Jobs Hartford-West Hartford-East Hartford, CT Hartford, Hartford-East Hartford-West Honolulu, HI TX Land-Baytown, Houston-Sugar IN Indianapolis, MS Jackson, FL Jacksonville, MO-KS City, Kansas TN Knoxville, FL Haven, Lakeland-Winter PA Lancaster, NV Las Vegas-Paradise, AR Conway, Rock, Little Rock-North Little Ana, CA Beach-Santa Angeles-Long Los KY-IN County, Louisville-Jefferson WI Madison, TX McAllen-Edinburg-Mission, TN-MS-AR Memphis, FL Beach, Lauderdale-Pompano Miami-Fort WI Allis, Milwaukee-Waukesha-West MN-WI Paul-Bloomington, Minneapolis-St. CA Modesto, TN Nashville-Davidson-Murfreesboro-Franklin, CT Haven-Milford, New LA Orleans-Metairie-Kenner, New Island, NY Jersey-Long New York-Northern New -NJ-PA FL North Port-Bradenton-Sarasota, UT Ogden-Clearfield, OK Oklahoma City, NE-IA Bluffs, Omaha-Council FL Orlando-Kissimmee-Sanford, CA Oaks-Ventura, Oxnard-Thousand FL Bay-Melbourne-Titusville, Palm PA-NJ-DE-MD Philadelphia-Camden-Wilmington, AZ Phoenix-Mesa-Glendale, PA Pittsburgh, OR Portland-Vancouver-Hillsboro, Area Metro PA Harrisburg-Carlisle, Appendix C. Change in the Geographic Distribution of Jobs in the 100 Largest Metro Areas (continued) in the 100 Largest Metro of Jobs Appendix C. Change in the Geographic Distribution

BROOKINGS | April 2013 19 1.4 1.0 6.3 5.8 5.1 0.6 2.3 4.4 3.6 6.5 9.4 1.6 0.7 0.1 3.9 1.9 0.3 0.9 2.5 5.8 5.4 1.7 1.6 1.1 0.4 1.7 -1.8 -1.5 35 10 to Miles Share Jobs of 1.0 2.0 1.8 1.8 1.6 2.1 3.7 0.3 0.0 0.1 0.7 0.7 1.2 1.1 -0.3 -0.9 -3.0 -3.2 -3.3 -1.9 -2.3 -4.0 -0.2 -2.4 -2.1 -0.1 -2.2 -1.7 CBD Share 10 3 to Jobs of from Miles 0.0 1.7 0.1 -2.5 -0.8 -5.4 -2.8 -1.9 -2.5 -4.1 -1.1 -1.7 -4.2 -5.4 -1.4 -1.7 -0.6 -1.8 -5.6 -0.6 -1.0 -2.5 -3.6 -5.5 -2.3 -1.8 -1.6 -2.9 Share Within CBD of 3 Miles Jobs of Change 2000-2010 7,632 6,758 6,604 9,419 7,548 -4,434 -9,045 -7,385 CBD 13,861 39,395 85,788 25,070 79,234 37,849 Total -20,860 -15,112 -28,885 -65,972 -23,491 -10,961 -22,399 -91,692 -35,091 -23,329 -38,434 164,568 Jobs of of Miles Number -243,113 -148,576 35 Within 0.2 0.1 1.7 0.0 0.5 0.7 1.7 1.2 0.0 1.3 0.8 0.2 0.1 0.1 -0.4 -1.1 -0.4 -0.8 -0.7 -1.6 -0.3 -0.6 -3.2 -0.2 -0.8 -0.1 -0.5 -0.3 CBD from Miles Share Jobs of 35 10 to 0.3 0.0 0.4 0.0 0.7 0.2 0.0 0.5 1.8 1.1 0.7 0.9 0.7 0.5 -0.5 -0.3 -1.0 -0.8 -1.4 -1.2 -0.7 -1.3 -0.4 -0.2 -1.1 -0.2 -0.3 -0.9 CBD from Miles Share 10 3 to Jobs of 0.3 0.2 0.0 0.1 1.2 0.7 0.7 1.1 1.5 1.3 1.3 0.1 0.4 0.1 0.3 0.7 0.2 1.2 -0.8 -0.2 -0.5 -0.3 -0.3 -1.0 -0.8 -1.1 -0.8 -0.6 Share Within CBD of 3 Miles Jobs of Change 2007-2010 -7,187 -7,928 -4,566 -5,945 -8,714 -6,508 CBD Total -55,879 -21,875 -47,167 -20,290 -93,911 -85,540 -41,339 -88,241 -67,288 -10,433 -17,725 -88,664 -26,795 -29,298 -21,910 -46,050 -82,573 -21,944 -15,451 Jobs of -148,751 -146,193 -114,103 of Miles Number 35 Within 1.3 0.9 4.5 5.8 4.6 1.0 1.6 5.6 4.0 7.3 7.7 2.3 1.0 0.7 1.7 2.7 2.0 0.3 1.7 2.7 4.5 4.6 1.5 2.1 1.0 0.2 2.0 -0.1 CBD from Miles Share Jobs of 35 10 to 1.5 0.0 0.1 1.6 2.6 1.3 2.3 0.3 2.6 0.7 1.2 0.0 1.0 0.7 2.0 -3.3 -3.3 -3.3 -2.6 -2.4 -2.6 -0.2 -1.2 -0.8 -0.7 -1.0 -2.0 -1.5 CBD from Miles Share 10 3 to Jobs of 0.2 -2.8 -0.9 -4.6 -2.5 -1.4 -2.6 -4.2 -2.3 -1.3 -4.9 -5.0 -2.1 -1.1 -3.0 -1.9 -1.9 -4.7 -1.0 -1.0 -1.7 -2.5 -5.8 -1.5 -0.6 -2.0 -1.0 -4.1 Miles Share CBD of Jobs of 3 Within Change 2000-2007 -877 6,000 -8,596 -5,016 -3,028 -8,296 -1,385 21,048 35,020 15,560 61,270 32,056 19,568 66,409 83,799 90,612 24,330 38,717 12,865 53,598 -96,919 -81,287 -13,685 -22,983 Total 234,539 100,670 126,090 247,141 CBD of Miles 35 Number of Within Jobs Area Metro NY Poughkeepsie-Newburgh-Middletown, RI-MA River, Bedford-Fall Providence-New UT Provo-Orem, NC Raleigh-Cary, Richmond, VA CA Bernardino-Ontario, Riverside-San NY Rochester, CA Sacramento-Arden-Arcade-Roseville, MO-IL Louis, St. UT City, Lake Salt TX Braunfels, Antonio-New San CA Marcos, Diego-Carlsbad-San San CA Francisco-Oakland-Fremont, San CA Clara, Jose-Sunnyvale-Santa San PA Scranton-Wilkes-Barre, WA Seattle-Tacoma-Bellevue, Springfield, MA CA Stockton, NY Syracuse, FL Petersburg-Clearwater, Tampa-St. OH Toledo, AZ Tucson, OK Tulsa, VA-NC News, Beach-Norfolk-Newport Virginia DC-VA-MD-WV Washington-Arlington-Alexandria, KS Wichita, MA Worcester, OH-PA Youngstown-Warren-Boardman, Appendix C. Change in the Geographic Distribution of Jobs in the 100 Largest Metro Areas (continued) in the 100 Largest Metro of Jobs Appendix C. Change in the Geographic Distribution

20 BROOKINGS | April 2013 Appendix D. Employment Located in High-Density ZIP codes, 100 Metro Areas, 2010

Metro Area Number of Number of Share of Number of High Share of Jobs ZIP Codes High Density Jobs Within Density ZIP Within High Density Within ZIP Codes High Density Codes More than ZIP Codes More 35 Miles Within 35 ZIP Codes 3 Miles than 3 Miles of CBD Miles of CBD (%) from CBD from CBD (%)

Akron, OH 55 7 15.5 0 0.0 Albany-Schenectady-Troy, NY 118 13 46.0 3 18.4 Albuquerque, NM 39 7 60.7 5 44.8 Allentown-Bethlehem-Easton, PA-NJ 80 8 37.5 2 6.5 Atlanta-Sandy Springs-Marietta, GA 161 36 51.9 28 43.7 Augusta-Richmond County, GA-SC 47 1 1.6 0 0.0 Austin-Round Rock-San Marcos, TX 86 20 59.2 13 39.6 Bakersfield-Delano, CA 35 2 27.4 1 14.5 Baltimore-Towson, MD 153 33 52.7 23 33.8 Baton Rouge, LA 75 7 51.6 4 38.8 Birmingham-Hoover, AL 95 9 41.6 3 13.5 Boise City-Nampa, ID 35 2 18.1 0 0.0 Boston-Cambridge-Quincy, MA-NH 230 76 64.3 51 36.5 Bridgeport-Stamford-Norwalk, CT 48 17 58.2 2 9.5 Buffalo-Niagara Falls, NY 84 24 53.6 15 37.6 Cape Coral-Fort Myers, FL 38 2 19.9 1 9.9 Charleston-North Charleston, Summerville, SC 36 4 38.1 2 22.7 Charlotte-Gastonia-Rock Hill, NC-SC 81 13 43.5 5 19.5 Chattanooga, TN-GA 57 5 25.5 0 0.0 Chicago-Joliet-Naperville, IL-IN-WI 286 133 74.2 116 54.1 Cincinnati-Middletown, OH-KY-IN 151 30 51.2 21 34.6 Cleveland-Elyria-Mentor, OH 100 22 46.6 18 34.7 Colorado Springs, CO 47 7 48.9 4 19.8 Columbia, SC 49 5 35.2 1 7.9 Columbus, OH 107 18 47.8 11 32.2 Dallas-Fort Worth-Arlington, TX 240 66 60.1 52 47.5 Dayton, OH 76 7 26.4 3 11.3 Denver-Aurora-Broomfield, CO 110 39 64.6 29 43.1 Des Moines-West Des Moines, IA 75 7 48.4 3 25.5 Detroit-Warren-Livonia, MI 176 44 55.8 39 49.0 El Paso, TX 28 8 55.9 5 41.6 Fresno, CA 53 9 51.7 6 40.0 Grand Rapids-Wyoming, MI 57 7 55.6 5 37.0 Greensboro-High Point-Mauldin-Easley, SC 52 3 18.8 0 0.0 Greenville, SC 43 4 44.3 2 13.3 Harrisburg-Carlisle, PA 61 8 37.2 1 4.7 Hartford-West Hartford-East Hartford, CT 98 14 27.8 7 5.8 Honolulu, HI 35 6 61.5 0 0.0 Houston-Sugar Land-Baytown, TX 187 55 63.1 44 52.8 Indianapolis, IN 107 13 41.5 9 27.7 Jackson, MS 46 5 20.8 1 1.3 Jacksonville, FL 57 5 24.3 1 6.4 Kansas City, MO-KS 169 27 46.6 17 32.8 Knoxville, TN 56 4 20.4 1 9.6

BROOKINGS | April 2013 21 Appendix D. Employment Located in High-Density ZIP codes, 100 Metro Areas, 2010 (continued)

Lakeland-Winter Haven, FL 35 0 0.0 0 0.0 Lancaster, PA 52 3 29.2 2 1.5 Las Vegas-Paradise, NV 67 19 72.9 12 26.7 Little Rock-North Little Rock, Conway, AR 60 5 36.7 2 9.9 Los Angeles-Long Beach-Santa Ana, CA 375 246 86.5 216 76.7 Louisville-Jefferson County, KY-IN 112 17 50.2 8 28.1 Madison, WI 58 8 41.5 3 14.8 McAllen-Edinburg-Mission, TX 22 2 30.8 1 13.8 Memphis, TN-MS-AR 73 15 51.5 11 40.4 Miami-Fort Lauderdale-Pompano Beach, FL 183 82 67.0 54 45.3 Milwaukee-Waukesha-West Allis, WI 81 21 53.1 13 29.6 Minneapolis-St. Paul-Bloomington, MN-WI 193 55 61.8 32 37.6 Modesto, CA 24 2 30.3 0 0.0 Nashville-Davidson-Murfreesboro-Franklin, TN 91 12 35.0 2 10.9 New Haven-Milford, CT 43 5 27.0 0 0.0 New Orleans-Metairie-Kenner, LA 67 16 55.1 7 26.0 New York-Northern New Jersey-Long Island, NY-NJ-PA 633 367 84.6 320 54.1 North Port-Bradenton-Sarasota, FL 45 3 17.6 1 4.3 Ogden-Clearfield, UT 24 0 0.0 0 0.0 Oklahoma City, OK 90 14 39.9 5 15.5 Omaha-Council Bluffs, NE-IA 111 17 64.3 11 48.1 Orlando-Kissimmee-Sanford, FL 93 21 55.9 15 43.6 Oxnard-Thousand Oaks-Ventura, CA 34 2 24.4 1 13.9 Palm Bay-Melbourne-Titusville, FL 28 3 27.5 1 4.3 Philadelphia-Camden-Wilmington, PA-NJ-DE-MD 319 103 56.3 85 41.8 Phoenix-Mesa-Glendale, AZ 136 41 66.1 30 48.0 Pittsburgh, PA 253 32 37.6 20 12.4 Portland-Vancouver-Hillsboro, OR-WA 120 32 61.8 21 39.7 Poughkeepsie-Newburgh-Middletown, NY 70 2 18.1 0 0.0 Providence-New Bedford-Fall River, RI-MA 111 27 47.7 17 27.9 Provo-Orem, UT 26 3 22.8 2 15.8 Raleigh-Cary, NC 57 7 31.8 4 21.5 Richmond, VA 101 9 35.9 5 23.4 Riverside-San Bernardino-Ontario, CA 115 13 35.8 9 27.7 Rochester, NY 96 15 47.0 5 22.0 Sacramento-Arden-Arcade-Roseville, CA 93 17 47.0 10 33.6 St. Louis, MO-IL 175 29 48.1 21 34.6 Salt Lake City, UT 48 18 66.4 10 41.4 San Antonio-New Braunfels, TX 104 17 52.6 12 42.3 San Diego-Carlsbad-San Marcos, CA 92 30 66.2 23 55.2 San Francisco-Oakland-Fremont, CA 162 79 77.1 62 52.4 San Jose-Sunnyvale-Santa Clara, CA 68 34 78.4 8 10.2 Scranton-Wilkes-Barre, PA 69 6 17.8 1 1.9 Seattle-Tacoma-Bellevue, WA 149 46 71.0 33 45.3 Springfield, MA 80 6 23.8 1 1.1

22 BROOKINGS | April 2013 Appendix D. Employment Located in High-Density ZIP codes, 100 Metro Areas, 2010 (continued)

Stockton, CA 33 4 28.3 2 19.6 Syracuse, NY 84 9 45.5 3 16.3 Tampa-St. Petersburg-Clearwater, FL 127 33 59.6 26 41.5 Toledo, OH 66 7 36.8 4 23.3 Tucson, AZ 45 10 61.4 8 53.3 Tulsa, OK 76 11 51.3 7 38.1 Virginia Beach-Norfolk-Newport News, VA-NC 113 18 46.9 7 25.8 Washington-Arlington-Alexandria, DC-VA-MD-WV 232 75 71.9 54 49.3 Wichita, KS 77 8 40.4 1 9.5 Worcester, MA 83 7 29.4 0 0.0 Youngstown-Warren-Boardman, OH-PA 81 4 9.0 1 3.1

Acknowledgements

The author thanks Oleg Firsin and Jane Williams for their excellent research assistance, and Alan Berube, Anthony Downs, Robert Puentes, and Adie Tomer for their comments on drafts of this brief.

The Metropolitan Policy Program at Brookings thanks the Ford Foundation for its generous support of the program’s research on city and suburban poverty and opportunity, the Annie E. Casey Foundation for its support of the program’s research on low-income working families, and the John D. and Catherine T. MacArthur Foundation, the George Gund Foundation, the Heinz Endowments, the Kresge Foundation, and the Surdna Foundation for their general support of the program, as well as the members of the Metropolitan Leadership Council.

The Brookings Institution is a private non-profit organization. Its mission is to conduct high quality, independent research and, based on that research, to provide innovative, practical recommendations for policymakers and the public. The conclusions and recommendations of any Brookings publication are solely those of its author(s), and do not reflect the views of the Institution, its management, or its other scholars.

Brookings recognizes that the value it provides to any supporter is in its absolute commitment to quality, independence and impact. Activities supported by its donors reflect this commitment and the analysis and recommendations are not determined by any donation.

BROOKINGS | April 2013 23 For More Information About the Metro Opportunity Series Elizabeth Kneebone Launched in 2009 the Metropolitan Opportunity Fellow Series documents the changing geography of poverty Brookings Metropolitan Policy Program and opportunity in metropolitan America, analyzes its [email protected] drivers and implications, and offers policy recommendations to enhance the well-being of lower-income families and communities in both cit- For General Information ies and suburbs. This study and other publications, Metropolitan Policy Program at Brookings speeches, presentations, and commentary in the 202.797.6139 series are available at: www.brookings.edu/metro/ www.brookings.edu/metro MetropolitanOpportunity.aspx

1775 Massachusetts Avenue NW Washington D.C. 20036-2188 About the Metropolitan Policy telephone 202.797.6139 Program at the Brookings Institution fax 202.797.2965 Created in 1996, the Brookings Institution’s Metropolitan Policy Program provides decision makers with cutting-edge research and policy ideas for improving the health and prosperity of cities In the Series and metropolitan areas including their component • Job Sprawl Revisited: The Changing Geography of Metropolitan cities, suburbs, and rural areas. To learn more visit: Employment www.brookings.edu/metro. • Job Sprawl and the Suburbanization of Poverty • Missed Opportunity: Transit and Jobs in Metropolitan America

BROOKINGS 1775 Massachusetts Avenue, NW Washington D.C. 20036-2188 telephone 202.797.6000 fax 202.797.6004 web site www.brookings.edu

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Home › News and Opinion › Blogs › 'Triumph of suburbia' is a far-fetched story › 'Triumph of suburbia' is a far-fetched story

Blog post by Robert Steuteville on 30 Apr 2013

Robert Steuteville, Better! Cities & Towns

Joel Kotkin is on a roll in the past few weeks, now making the case that the revival of cities and decline of suburbs is a fraud perpetrated by a long list of elites and urbanists including Edward Glaeser, Richard Florida, Alan Ehrenhalt, Christopher Leinberger, James Howard Kunstler, Peter Katz, and many others. Those he names should feel honored, because he traces what he calls "a hate affair with suburbia" back to Jane Jacobs and William H. Whyte.

Kotkin's latest evidence is a report from the Brookings Institution that in 91 of 100 largest US metropolitan areas the share of regional jobs in downtowns declined from 2000 to 2010, while the distant suburbs gained in this category. The report coined the term "job sprawl" to describe the trend.

"A funny thing happened on the way to the long-trumpeted triumph of the city: the suburbs not only survived but have begun to regain their allure as Americans have continued aspiring to single-family homes," Kotkin says.

The cities that bucked the trend were many of the largest metro areas, and the "job sprawl" diminished in the latter part of the decade when sprawl itself slowed to a crawl.

As I pointed out last week when the report came out, this comparison means little because of the method used. Brookings drew a bull's eye around the primary downtown of each metro region and counted jobs within three miles, from three to 10 miles, and from 10 to 25 miles out. The area between 10 and 25 miles of these downtowns is 58 times larger than the core area.

With so much more land — and a greater population and far lower jobs density — it's not surprising that the share of jobs in the outer suburbs rose relative to downtown. Leading up to the housing crash in 2007-2008, there were an awful lot of businesses like Lowe's, Bed Bath & Beyond, and Arby's built in the outer-ring areas. Measured in this way, downtowns will likely continue to decline in share of regional jobs even if there is a modest amount of outward growth of metro areas.

In his analysis, Kotlin ignores many inconvenient facts and trends that don't fit his narrative of an inexorable, historical march to lower density in generation after generation. Real estate values have declined in the automobile-oriented suburbs relative to compact, mixed-use neighborhoods. There's a growing preference for rental housing, and multifamily development has recovered far more quickly than single-family development. Multifamily development has taken on a new character in recent years. In the 1990s it was garden apartments in the suburbs. Now it is being built in urban, transit-served neighborhoods. Mostly Kotkin ignores, or doesn't understand, that the issue is not single-family versus multifamily, or suburb versus city. It's not even higher density versus lower density. The urban-rural Transect includes a range of walkable places, from suburban to urban core.

The issue is really walkable places versus auto-oriented places. Walkable urban places, which are where the market is trending according to many industry sources including the Urban Land Institute, Emerging Trends in Real Estate, and the National Association of Realtors, can be located downtown, in urban neighborhoods far from downtown, and in the suburbs.

These walkable urban neighborhoods often include single-family houses — but they are also mixed-use, more compact, and better connected than the far suburbs. There's a big difference between a small-lot single-family house in a mixed-use neighborhood and a large-lot house that is isolated in the far suburbs. There's a difference between a strip mall and a main street, an office park and a mixed-use workplace building.

Last week I stayed in a neighborhood called Allentown in Buffalo, New York. The city is a poster child for urban depopulation having lost most of its residents since 1950. But Allentown, which was languishing and down-on-its-heels 25 years ago, is now thriving, and downtown Buffalo is coming back. Allentown is close to downtown, but many walkable neighborhoods far from downtown in the nation's sizable metro areas are thriving, too.

In the Washington, DC, area, for example, a rising share of commercial development is taking place in walkable urban places (WalkUPs), mostly served by transit. The majority of these places are located in the suburbs. These WalkUPs command a 75 percent premium of auto-oriented commercial development, whereas a quarter- century ago, suburban office parks carried the premium. Forty-eight percent of DC commercial development is taking place in WalkUPs, which amount to less than 1 percent of the land area.

Philadelphia, a city that is not one of the "Big 6" real estate markets and is struggling in many ways, is seeing similar trends, according to a University of Pennsylvania study. Compact, urban places, both downtown and in the suburbs, performed better during the Great Recession.

Reading between the lines, Kotkin alludes to a few important trends that urbanists should pay attention to. How to accommodate single-family housing in walkable neighborhoods is something that new urbanists have been working on for three decades. Yet they haven't entirely solved this problem, and some smart growth advocates ignore it completely. We need sustainable single-family housing and Kotkin is right that a large number of Americans prefer a separate house on a lot.

Second, the suburbs are growing more diverse and many immigrants and minorities are moving beyond cities. That's great, but it doesn't mean that the new suburban residents don't also want access to transit and walkability. And this diversity, combined with a trend towards rental housing in subdivisions, may be a double- edged sword for suburbs — which have always sold isolation and exclusivity.

Kotkin will no doubt continue to rail against those he disagrees with, but his attempt to change the narrative is hardly convincing.

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Walk this Way: The Economic Promise of Walkable Places in Metropolitan Washington, D.C.

Christopher B. Leinberger and Mariela Alfonzo1

“Emerging Findings

evidence points An economic analysis of a sample of neighborhoods in the Washington, D.C. metropolitan area using walkability measures finds that: to a preference n More walkable places perform better economically. For neighborhoods within metropolitan for mixed- Washington, as the number of environmental features that facilitate walkability and attract pedestrians increase, so do office, residential, and retail rents, retail revenues, and for-sale use, compact, residential values.

amenity-rich, n Walkable places benefit from being near other walkable places. On average, walkable neighborhoods in metropolitan Washington that cluster and form walkable districts exhibit higher transit-accessible rents and home values than stand-alone walkable places.

neighborhoods n Residents of more walkable places have lower transportation costs and higher transit access, but also higher housing costs. Residents of more walkable neighborhoods in metro- or walkable politan Washington generally spend around 12 percent of their income on transportation and 30 percent on housing. In comparison, residents of places with fewer environmental features that places.” encourage walkability spend around 15 percent on transportation and 18 percent on housing.

n Residents of places with poor walkability are generally less affluent and have lower educational attainment than places with good walkability. Places with more walkability features have also become more gentrified over the past decade. However, there is no significant difference in terms of transit access to jobs between poor and good walkable places.

The findings of this study offer useful insights for a diverse set of interests. Lenders, for example, should find cause to integrate walkability into their underwriting standards. Developers and investors should consider walkability when assessing prospects for the region and acquiring property. Local and regional planning agencies should incorporate assessments of walkability into their strategic economic development plans and eliminate barriers to walkable development. Finally, private foundations and government agencies that provide funding to further sustainability practices should consider walkability (especially as it relates to social equity) when allocating funds and incorporate such measures into their accountability standards.

BROOKINGS | May 2012 1 Introduction

he Great Recession highlighted the need to change the prevailing real estate development paradigm, particularly in housing. High-risk financial products and practices, “teaser” underwriting terms, steadily low-interest rates, and speculation in housing were some of the most significant contributors to the housing bubble and burst that catalyzed the recession. But an oversupplyT of residential housing also fueled the economic crisis. However, a closer look at the post-recession housing numbers paints a more nuanced picture. While U.S. home values dropped steadily between 2008 and 2011, distant suburbs experienced the stark- est price decreases while more close-in neighborhoods either held steady or in some cases saw price increases.2 This distinction in housing proximity is particularly important since it appears that the United States may be at the beginning of a structural real estate market shift. Emerging evidence points to a preference for mixed-use, compact, amenity-rich, transit-accessible neighborhoods or walkable places. According to the National Association of Realtors, 58 percent of homebuyers surveyed prefer mixed-use neighborhoods where one can easily walk to stores and other businesses. Further, 56 percent expressed a preference for communities with amenities such as a mix of housing types, various destinations within walking distance, public transportation options, and less parking. The trend is swinging away from neighborhoods that contain primarily large-lot single-family housing, few sidewalks, ample parking, and where driving is the primary means of transportation. Sixty percent of those swinging toward newer amenities do so for the convenience of being within walking distance to shops and restaurants and two-thirds of buyers factor walkability into their home purchase decision.3 Changing demographic trends— retiring baby boomers, first-time buyers preferring walkable places, and a rising number of households without children—are one reason for the increased housing market segment driven by walkability.4 In fact, the demand for walkable places may outpace its supply.5 While this research is still emerging, one study posits that small-lot and attached housing units are under-supplied by 11 percent and 8 percent respectively, or an estimated 12 and 13.5 million units, while large-lot housing is over-supplied by an estimated 18 percent, accounting for approximately 28 million units.6 Another study conducted in Atlanta found that only 35 percent of those who preferred to live in a walkable neighborhood actually did so.7 Large price premiums attached to walkability, seemingly tied partly to a supply-demand mismatch, was revealed by additional research.8 Real estate listings and Internet house-listing sites such as Zillow now assign Walk Score rankings to their properties, signaling the growing interest of consumers.9 Despite increasing demand for walkability, the real estate industry has yet to fully embrace the concept since some public- and private-sector barriers complicate walkable development. Many municipal policies, zoning ordinances, public funding biases, and planning policies still encourage low- density, suburban type development.10 Walkable urban places remain complex developments that still carry high risk and, as such, costly capital (both equity and debt financing.) The financial community continues to have difficulty underwriting high-density, mixed-use, walkable urban development. Banks, investors, and Wall Street analysts have traditionally adhered to investment and underwriting silos that reflect 19 standard product types, none of which speak to the nuances involved with walkable developments.11 Overall, the real estate finance industry lacks the experience, institutional mission or even fiduciary latitude to appropriately consider walkable development investments or loans.12 We consider walkability to be a mechanism by which to increase a place’s triple bottom line: profit (economics), people (equity), and planet (environment). On economics, recent studies show that both residential and commercial properties in neighborhoods with greater walkability have greater resale value.13 For people, research shows clear links between elements of walkable communities and better public health outcomes.14 In terms of the environment, while research on the direct relationship between walkability and greenhouse gas emissions from transportation is still nascent, there is evidence that walkability is related to decreased driving and increased walking and that CO2 emissions are linked to vehicle miles traveled.15 Despite the emerging evidence of the links between walkability and the triple bottom line, we lack an operational definition and performance metrics for walkable urban places that would facilitate their proliferation. In fact, the absence of a clear classification of the mix of residential, office, and retail

2 BROOKINGS | May 2012 elements that comprise walkable urban places or of the built environment components (including area, density, land use characteristics, transportation facilities, etc.) necessary to produce sustainable, economically viable, socially equitable places has been one of the most significant barriers to addressing their demand..16 Metrics to gauge walkable urban places’ performance that could guide investment decisions and public policy development have also been absent. This study seeks to establish an operational definition of walkable urban places that lays out observable, measurable factors that characterize them. It also seeks to develop a valid and reliable set of economic and social equity performance metrics that create a framework for stakeholders to consider the development of walkable urban places where most appropriate and applicable. We also sought to understand the differences between regional-serving and local-serving places, as they are thought to play different but complementary roles in promoting sustainable, economic growth in metropolitan areas. The Washington D.C. metropolitan area, which previous research identified as having a high number of walkable places per capita, serves as the focal place.17

Methodology

his study combines primary data on the built environment with a variety of secondary real estate, fiscal, demographic, transportation, and business data to establish an operational definition of, and performance metrics for, walkable urban places. A 2007 Brookings study surveyed U.S. real estate and planning experts to help identify walkable urban places within T30 U.S. metropolitan areas. That work conceptually defined walkable urban places as those considered to be regional serving, high density, mixed-use, and between 50 and 400 acres.18 For the current work, we employed a variety of exploratory, qualitative, and quantitative methods, including a literature review, industry and expert advisory panels, archival analysis, and an on-site built environment audit to help layout an objective, measurable definition of walkable urban places and identify key real estate, economic, and social equity benchmarks. While this study does not delineate all of the walkable urban places in metropolitan Washington, it employs a methodology that can be adapted for wider use in other U.S. metros. We first set out to identify the universe of potential walkable urban places in metropolitan Washington. We catalogued over 400 comprehensive, sector, and small area plans as well as business improvement districts (BIDs), locally-defined regional activity centers, neighborhoods and other specially funded areas.19 From these, we identified 201 walkable urban place candidates.20 The criteria for inclusion were: 1. Located within the jurisdictions that are part of the Metropolitan Washington Council of Governments;21 2. Has an existing plan (e.g. special district overlay) that aimed to increase walkability, density, or mixed uses that was not restricted to small area road corridor based plans or is a neighborhood that contains a Metrorail subway station; 3. Not located in Census-designated rural blocks.22 We conducted archival analysis of existing land use plans, special district overlays, and other planning documents to determine whether a neighborhood met the second criteria.23 We used established definitions of neighborhoods, when available, to delineate a place’s boundaries. Some places (e.g. widely-known neighborhoods, such as Dupont Circle, without established jurisdictional boundaries) lacked official planning agency or documented definitions. In those cases, we used multiple methods to establish a place’s boundaries, including census blocks and block groups, school districts, political districts, neighborhood commissions and local neighborhood organizations or blogs.24

BROOKINGS | May 2012 3 Figure 1. Neighborhoods Included in Study and their Walkability Scores and their Walkability 1. Neighborhoods Included in Study Figure

4 BROOKINGS | May 2012 Figure 1. Map Key

Map ID Walkability Map ID Walkability number Neighborhood Acreage Level number Neighborhood Acreage Level 1 Adams Morgan 268 4 37 King Street 299 4 2 Addison Road 274 3 38 Landover Road Metro Area 384 1 3 Bailey’s West 120 3 39 Logan Circle 232 n/a 4 Ballston 351 4 40 M Square Research Park 346 4 5 Beacon/Groveton 195 2 41 Mathis Avenue 367 2 6 Beauregard 485 4 42 Minnesota Avenue 458 3 7 Benning Road 169 3 43 Mount Vernon 156 4 8 Bethesda 505 4 44 National Harbor 182 5 9 Bladensburg Town Center 131 2 45 Naylor Road 111 1 10 Burnt Mills Commercial Center 34 3 46 New Carrollton 559 2 11 Carlyle 607 4 47 New York Avenue 22 1 12 Chevy Chase Lake 355 3 48 NoMa 378 4 13 Cleveland Park 424 4 49 Paint Branch 142 3 14 Columbia Heights 417 4 50 Penn Quarter/Chinatown 164 5 15 Congress Heights 361 3 51 Prince George’s Plaza 282 4 16 Courthouse 247 5 52 Prince William Gov’t Center 1,530 3 17 Crystal City 226 4 53 Rhode Island Avenue Metro 508 4 18 Downtown DC 443 5 54 Rockville 529 4 19 Downtown Manassas 483 3 55 Rolling Acres 228 3 20 Dulles West 2,740 3 56 Rosslyn 292 n/a 21 Dupont Circle 315 4 57 Saint Elizabeth’s 363 3 22 FedEx Field 211 3 58 Shirlington 37 4 23 Flint Hill Suburban Center 166 3 59 South County Center CBC 197 2 24 Foggy Bottom 261 n/a 60 SW Federal Center 257 4 25 Fort Totten 209 3 61 SW Waterfront 356 4 26 Gateway Arts District 395 2 62 U Street/Shaw 330 4 27 Georgetown 472 5 63 Van Dorn Transit Area 196 3 28 Glenmont 693 3 64 Vienna Transit Station Area 361 4 29 Glover Park 244 4 65 Walter Reed 65 3 30 H Street/Atlas District 347 3 66 Washington Highlands 307 3 31 Historic Fairfax City 449 4 67 West End 83 4 32 Judiciary Square 145 5 68 West Falls Church Transit Area 267 3 33 Kalorama 144 4 69 West Hyattsville 347 4 34 Kensington 407 3 70 Wheaton 441 3 35 Kentlands 108 4 71 White Flint 443 3 36 King Farm 495 4

We drew a sample from the 201 places selected as candidates for walkable urban places for which we would collect detailed data. As such, we generated Walk Score rankings for each of the 201 places to establish an initial continuum of walkability from which to draw our sample.25 We then employed a modified stratified random sampling scheme, ultimately selecting a sample of 66 places that vary from low to high walkability.26 We used the mean and standard deviation of the Walk Score rankings for the population of candidates (N=199; M= 62.4, SD=18.8), eliminating outliers (N=2; with scores of zero), to establish five preliminary levels of walkability. We oversampled (at 100 percent) from the highest level (Walk Score rankings > 90.6, representing 2.5 SD above the mean) and selected a random representative sample from the remaining strata (levels). Walk Score, used as a tool to help generate our sample, is a metric that measures the walkability levels of any U.S. address on a scale from 0 to 100 based on the number of destinations present within

BROOKINGS | May 2012 5 a specified distance. It differs from the walkability measure we ultimately employed in our sample in that Walk Score is based on solely on the number of destinations within walking distance (although the StreetSmart Beta version employed here also accounts for the type of destination and the connectivity of the walking route) whereas the walkability measure we ultimately employed for this study is based on a more robust set of micro-scale built environment features related to walkability, as discussed in the next section. Using data drawn from this sample (see description of metrics below), we established our operational definition of walkable urban places, tested the relationship between walkability and economic performance, and compared various indicators of social equity between places with low and high levels of walkability. We also sought to distinguish between regional-serving and local-serving places since these subsec- tions serve different economic functions within metropolitan areas. In particular, we aimed to better operationalize the universe of options of metropolitan land use, which is based on form (walkability) and function (economic.)27 Our sample was drawn from places with established policies to promote walkability, density, or a mix of uses. (We recognize that this sampling technique may have weeded out places with low walkability relative to the region.) Further, we created five Walk Score levels based on the range in our population. Our sample included all places that scored 90 or better on Walk Score and a representative sample from the remaining Walk Score levels. The criteria for inclusion in our population and our sampling strategy produced a sample that likely contained a greater number of high walkable places relative to low walkable. As a result, the low walkable places in our sample tended to be closer-in urban places (that in some cases happened to be near a metro subway stop) as opposed to far-flung suburban places. In fact, many of the places in our sample that had “poor” or “very poor” walkability had average household incomes that were lower than the region as a whole. We anticipate the need to further explore the issue of social equity in places with low walkability across varying income levels. This study employed four sets of metrics—walkability, regional serving, economic performance, and social equity—described below.

Walkability To assess walkability and establish the operational definition of walkable urban places, we employed a 162-item audit tool—the Irvine Minnesota Inventory (IMI)—that collects objective data on built environment characteristics hypothesized to be related to physical activity.28 We collected IMI data for a sample of blocks within each of the 66 places.29 We relied upon a scoring system that calculates a composite walkability rating along ten urban design dimensions adapted from the findings of a meta- review study that outlined key environmental factors empirically linked with walkability:30 1. Aesthetics (attractiveness, open views, outdoor dining, maintenance) 2. Connectivity (potential barriers such as wide thoroughfares) 3. Density (building concentrations and height) 4. Form (streetscape discontinuity) 5. Pedestrian amenities (curbcuts, sidewalks, street furniture) 6. Personal safety (graffiti, litter, windows with bars) 7. Physical activity facilities (recreational uses) 8. Proximity of uses (presence of non-residential land uses) 9. Public spaces and parks (playgrounds, plazas, playing fields) 10. Traffic measures (signals, traffic calming) The scores for each dimension are calculated based on the absence or presence of specific built environment features related to that dimension, providing easily identifiable high-score/low-score components that influence the overall score. This allows a user to understand how walkable a place is as well as why it is walkable. It explains why places with approximately the same overall IMI score may differ with respect to their scores along each of the ten dimensions. For example, while Downtown D.C. and National Harbor have similar IMI scores, the former has a higher proximity score while the latter has a higher traffic safety score. Based on total IMI scores, we identified five levels of walkability and established an operational definition of walkable urban places that we applied to our stratified random sample of places in

6 BROOKINGS | May 2012 Table 1. Irvine-Minnesota Inventory (IMI) Levels Based on a Sample of Washington D.C. Metropolitan Neighborhoods

Classification Levels 1 2 3 4 5 IMI Total (Mean= -3.39) Lowest thru -43.39 -43.4 thru -23.39 -23.4 thru -3.39 -3.4 thru 23.39 23.4 thru Highest Region-Serving Places 0 (0%) 4 (12.1%) 8 (24.2%) 16 (48.5%) 5 (15.2%) Example N/A New Carrollton White Flint Bethesda Downtown D.C. Local-Serving Places 3 (10.7%) 2 (7.1%) 16 (57.1%) 7 (25%) 0 (0%) Example Naylor Road Bladensburg Town West Falls Church Cleveland Park N/A Center Transit Area Walkability Classification Very poor walkability Poor walkability Fair walkability Good walkability Very good walkability Not Walkable Urban Places Walkable Urban Places

metropolitan Washington (Table 1). IMI scores ranged from –55.62 for the New York Avenue neighborhood to 39.39 for Downtown D.C.)31

Distinctions Between Regional- and Local-Serving Places Regional-serving and local-serving places serve complementary but distinct roles within the metropolitan economy. The former, with a higher concentration of jobs that generate income from outside the region and regional-serving jobs (e.g. lawyers, bankers, hospital workers), act as significant economic engines for the region, while the latter, with a larger proportion of local-serving jobs (teachers, phar- macists, dentists), may support a region’s day-to-day activities and contribute to overall quality of life. Classifying places based on their roles within the metropolitan region may help the private and public real estate industry and urban planners tailor their investment, lending, policy, planning, and design intervention strategies based on their needs and interests. There is a lack of consensus, however, regarding what indicators—and at what thresholds—best serve to delineate between regional- and local-serving places. Conceptually, regional-serving places may contain one or more of the following: a significant amount of retail with a large catchment area; regional employment centers; industrial hubs; high concentrations of government activity; higher education uses; medical institutions; cultural/sport/recreational activities; civic uses; transportation hubs; or entertainment (e.g. theaters, movie theaters) uses. Local-serving places tend to contain a higher percentage of residential uses than do regional-serving places; primarily have neighborhood-oriented retail uses and services such as grocery stores, and medical offices; and have primary and secondary educational uses, post offices, libraries and other neighborhood supporting services. Building on the literature and findings from the advisory panels, we established a working definition for regional-serving places: A place that is a key economic contributor to a metropolitan area in terms of employment, entertainment, retail, education, or other institutional production, and has reached critical mass (or the point at which a place is self-sustaining and does not need government subsidies for subsequent development). Based on that, we developed a classification system for regional- and local-serving places. First, we classified a place as regional serving based on the presence of any of the following non-commercial uses: educational (e.g. Georgetown University), regional entertainment (e.g. Nationals Ballpark), or civic use (e.g. Superior Court of D.C.). Next, we considered the concentration of commercial uses. We identified two tiers (Table 2) of regional-serving places based on the total rentable building area for both office and retail.32 Specifically, we found the tipping point for office and retail concentrations at which a statistically significant difference in office rents and retail sales, respectively, was observed as these are considered to be important indicators of real estate and economic performance.33

BROOKINGS | May 2012 7 Table 2. Levels of Office and Retail-Based Regional Serving Places with Examples from Metropolitan Washington

Super Regional Serving (Tier 1) Regional Serving (Tier 2) Local Serving Office (based on statistically significant >6 million square feet RBA >1.4 million square feet RBA <1.4 million square feet RBA difference in average office rents) (ex. Tysons Corner) (ex. King Street) (ex. Cleveland Park) Retail (based on statistically significant >2.3 million square feet RBA >340,000 square feet RBA <340,000 square feet RBA difference in retail sales) (ex. Pentagon City) (ex. U Street) (ex. Mount Pleasant)

RBA=rentable building area

Economic Performance To understand the relationship between economics and walkability, we ran a hedonic regression analysis to measure the impact of a place’s IMI score on various economic indicators, controlling for average household income as well as independent value t-tests (for capitalization rates.) Our original list of performance metrics was vast and fairly comprehensive. We narrowed the number to six, including retail rents, office rents, retail sales, residential rents, residential price per square foot, and capitalization (cap) rates. Limited availability of relatively easily accessible, national data sets guided the selection of metrics, as we aimed to establish a replicable methodology for identifying and evaluating walkable urban places nationwide.

Social Equity While there is a lack of consensus around a definition for social equity, we outlined five related indicators: diversity, income, education, affordability, and accessibility. We chose these metrics from a number of other potential indicators as they are consistently measurable and the data is generally widely available in multiple metropolitan areas. ➤ Affordability: percent of average median income (AMI) spent on transportation costs, percent of AMI on housing, and percent of AMI on housing and transportation; ➤ Income: average household income, per capita income, disposable income, and unemployment rates; ➤ Diversity: the Census-defined diversity index, and racial and ethnic composition; ➤ Education: percent of the population with a high school degree, bachelors degree, and graduate degree; ➤ Accessibility: access to transit, access to parks, number of transit lines, number of bus routes, average headway, and share of jobs reachable within 90 minutes. To examine social equity performance, we compared places scoring poorly on walkability (those with IMI levels of 1 and 2) to places scoring at fair to very good on walkability (IMI levels 3, 4, and 5.)34 We chose to examine the differences between those places with the most substandard walkability relative to those with at least fair walkability to better understand the social equity within the least walkable places in our sample.35 Some places that fell within IMI level 3 (fair) may be on an upward trajectory in terms of walkability as many of the places in our sample have plans to become more walkable. We deemed it was more appropriate to examine differences between those places that currently have at best poor walkability relative to those with at least fair walkability. Much more effort would be required to retrofit the former to become more walkable, thus potentially exacerbating social equity issues. As such, we felt it was particularly important to examine these most vulnerable places. All of these metrics were also compared across the average for metropolitan Washington to provide a basis of comparison.

8 BROOKINGS | May 2012 Findings

A. More walkable places perform better economically. Based on our sample of places within metropolitan Washington, a neighborhood’s walkability score relates positively to several key economic indicators.36 Higher walkability, as measured by a place’s IMI score, is related to higher economic performance, controlling for a place’s household income (Table 3).37 Specifically, considering the magnitude of influence that walkability has on economic performance, a one-level (or approximately 20 pt) increase in walkability (out of a range of 94 points) translates into a $8.88 value premium in office rents, a $6.92 premium in retail rents, an 80 percent increase in retail sales, a $301.76/square foot premium in residential rents, and a $81.54/square foot premium in residential housing values.

Table 3. The Relationship between Walkability and Economic Performance38

1 IMI level increase (~20 pt. IMI) Mean & Standard Deviation Avg. office rent/square foot *** $8.88 M=$32.47 SD=$10.21 Avg. retail rent/square foot ** $6.92 M=$33.24; SD=11.94 Percent Retail sales** 80% See footnote Avg. residential rent/month *** $301.76 M=$1,550.64 SD=$538.41 Avg. for-sale home value/square foot *** $81.54 M=$295.93 SD=$140.57

p-values: ~=.10; *<.05; **<.01; ***<.001

While the relationship between walkability and economic performance is continuous (increases in the former relate to increases in the latter), the economic value of walkability is perhaps best illustrated by the impact of moving from one level of walkability (e.g. Wheaton at a level 3 with “fair” walkability) up to the next (e.g. Adams Morgan at a level 4 with “good” walkability), holding housing values constant. For example: Places with higher walkability perform better commercially. A place with good walkability, on average, commands $8.88/sq. ft. per year more in office rents and $6.92/sq. ft. per year higher retail rents, and generates 80 percent more in retail sales as compared to the place with fair walkability, holding household income levels constant. Places with higher walkability have higher housing values. For example, a place with good walkability, on average, commands $301.76 per month more in residential rents and has for-sale residential property values of $81.54/sq. ft. more relative to the place with fair walkability, holding household income levels constant. An examination of the impact of walkability on capitalization rates focused on the differences between places that were classified as walkable urban (levels 4 and 5) and those that were not (levels 3 and under). We found that: Capitalization rates are lower in places that qualify as walkable urban places than in those that do not, especially in the period after the Great Recession.39 Development in places with higher walkability has lower capitalization rates. The underlying value of real estate assets in walkable places is higher, facilitating private market financing (Figure 2).40 On average, before the recession (2000 to 2007), retail and office space in walkable urban places had a 23 percent premium per square foot valuation. During the recession (2008 to 2010) that premium nearly doubled to 44.3 percent.

BROOKINGS | May 2012 9 Figure 2. Capitalization Rates Before and After the Recession for Places with Above Average vs. Below Average Walkability

10 ______9 ______8 ______7 ______6 n Non-walkable urban places ______(IMI level 3 and below) 5 ______4 ______n Walkable urban places 3 (IMI level 4 and higher) ______2 ______1 ______0 2000–2007 2008–2010

Table 4. Economic Performance of Walkable Districts vs. Single Walkable Places

Walkable Urban Place Districts Stand-alone Walkable Urban Places Average office direct gross rent*** $ 41.98 $ 29.81 Average retail direct gross rent*** $ 42.10 $ 28.59 Retail sales** $ 2,303,980 $ 1,030,259 Average residential rent** $ 2,016.56 $ 1,544.04 Average for-sale home value/sf*** $ 465.95 $ 250.33 Assessed taxes $ 3,241.30 $ 3,163.25 Percent retail* 4.6% 11.7% Percent office 41.1% 24.8% Percent residential 52.9% 55.7% --Percent rental residential 10.2% 20.2% --Percent for sale residential 42.7% 35.5% Cap rate before recession 7.78 7.70 Cap rate after recession 6.37 6.85 Average # of rail stops 1.57 .75

p-values: ~=.10; *<.05; **<.01; ***<.001. Note: retail sales were normalized into z-scores within the analysis.

B. Walkable urban places benefit from being near other walkable urban places. Within metropolitan Washington, many of the places in the study sample with above-average walkability have clustered together. For example, within the District, Dupont Circle is adjacent to Georgetown, Adams Morgan, Kalorama, West End, Columbia Heights, U Street, Logan Circle, and Downtown D.C. All of these neighborhoods were classified as walkable urban places and have either an IMI level of 4 or 5. In northern Virginia, the adjacent neighborhoods of Clarendon, Virginia Square, Courthouse, and Ballston also form a walkable urban place district. Comparing the sample’s clustered walkable urban places to those that stand alone, such as Bethesda, we found that those clustered into a district performed better across a number of economic indicators (Table 4). For example, the clustered neighborhoods commanded nearly 41 percent more in office rents, 47 percent more in retail rents, and nearly 31 percent more in residential rents. Additionally, residential values in walkable urban place districts were on average 86 percent higher on a per square foot basis than in stand-alone walkable places.

10 BROOKINGS | May 2012 Average retail sales in walkable urban place districts do not differ statistically from that of other walkable urban places. This may be due to the fact that places that do not cluster have a higher percentage of retail uses (11.75 percent) relative to the individual walkable urban places within a cluster (4.6 percent), which may help to make up for the difference in retail sales. But there is no difference in cap rates between clustered and single walkable urban places, nor is there a difference in transit access as measured by rail.

C. Residents of more walkable places have lower transportation costs and higher transit access, but also higher housing costs than residents of less walkable places Based on data from the Center for Neighborhood Technology, we found that places with fair to very good walkability have significantly lower transportation costs than do places with poor to very poor walkability (Table 5). Alternatively, walkable areas have significantly higher housing costs than those with fewer environmental amenities. This finding affirms other studies that have indicated that living in more compact, mixed-use neighborhoods is related to reduced vehicle miles traveled and lower transportation costs. A composite set of built environment characteristics (accounted for by the IMI) is important with respect to household transportation expenditures. This includes more than just macro- level planning factors such as proximity to non-residential destinations, density, and connectivity. Micro-scale urban design features including pedestrian amenities, traffic safety, safety from crime, and aesthetics are also important.41

Table 5. Percent of Area Median Household Income Spent on Housing and Transportation, By Walkability Level

IMI Level 1 2 3 4 5 Region %AMI Transportation Costs 14.7 15.9 15.7 12.7 12.3 13.8 %AMI Housing Costs 16.9 19.0 24.7 30.1 31.7 37.1

Source: Data for the neighborhoods from the Center for Neighborhood Technology; metro area data from Bureau of Labor Statistics

When compared to the overall metropolitan Washington area, places in the study sample with fair- to-very-good walkability spend 28 percent less of their average monthly income on transportation but 17 percent more on housing. Places with poor-to-very-poor walkability within our sample also see transportation savings relative to the region and spend 12 percent less on housing costs. The nature of our sample, insofar as it does not contain many far-flung suburban places, likely helps explain why all of the places observed have lower transportation costs relative to the region. Finally, accessibility to jobs, transit, and recreation varies according to walkability. While overall there are no significant differences with respect to access between places with fair to very good walkability and places with poor to very poor walkability, there are important differences between the specific levels of walkability.42 For example, residents of places at walkability level 4 on average can access over 15 percent more jobs in the region within 90 minutes than residents in places at level 3, and 21 percent more than residents in places at level 2. Additionally, places at level 5 have 3.4 and 2.4 times more bus lines, respectively, than places at level 2 or 3.43 Moreover, level 5 places contain 3.4 to 3.6 times more parks on average than do places with fair or poor walkability.44 This analysis points to significant differences in access that vary with a place’s walkability level. While the relationship outlined here between walkability and accessibility is not causal, the fact that they occur in tandem is problematic from a social equity standpoint. That is, residents of places with low walkability are not only faced with living in places that are not very walkable, they are also dealing with a lack of access to jobs, transit, and recreational amenities, relative to what is available to residents of places with higher walkability. When comparing our sample to the region overall, no significant differences emerge between poor to very poor walkable places and fair to very good walkable places relative to the total share of jobs accessible within 90 minutes and average headway, indicating that there are places in the region that are worse off from an accessibility standpoint (Appendix Table 1). Again, the lack of a significant difference may be attributable to the nature of our sample;

BROOKINGS | May 2012 11 if we were to include more places, it is likely that we would find a significant difference with respect to accessibility. Nevertheless, the discrepancies in access identified here are quite important from a social equity standpoint.

D. Residents of places with poor walkability are generally less affluent and have lower educational attainment than places with good walkability. Based on the sample, households in places with fair-to-very-good walkability have higher incomes, education levels, and employment rates than places with poor to very poor walkability.45 Indicators (Appendix table) related to income, education, and unemployment point to similar concerns as those related to accessibility. Within the sample, residents of places with poor or very poor walkability had lower average, disposable, and per capita incomes, constraining their housing choices. Further exacerbating this constraint is the fact that housing prices within fair to very good walkable places are higher than that of poor to very poor walkable places. Simply, if residents of the poor to very poor walkable places in the sample wanted to live in a more walkable place, it is unlikely they could afford to do so. This presents a serious social equity issue, especially considering the other health, social, and economic benefits that have been empirically linked to walkability. Further, the decreased accessibility within poor to very poor walkable places (relative to that of fair to very good walkable places) is especially disconcerting, as not only do the latter lack appropriate walkable amenities within their neighborhoods, their access to amenities (including jobs) within other neighborhoods is also limited.

Implications and Conclusion

onsidering the economic benefits, walkability should be a critical part of all strategic growth plans. The implications of this study cut across the federal and state, metropolitan, and place levels. Public policy should become more favorable toward walkable placemaking. Currently, manyC federal and state subsidies substantially favor low-density development and tip the scales against walkable development. Further, many local zoning codes make walkable development illegal, necessitating costly and time-consuming zoning changes with no guarantee of success. Federal, state, and local policy makers should conduct a systematic review of existing public policies that are biased against walkable development, and adopt new measures aimed at facilitating (or at least removing roadblocks to) this type of development. For their part, local and regional planning agencies should incorporate assessments of walkability into their strategic economic development plans. Planning entities should identify where regional- serving and local-serving walkable urban places exist within a metropolitan area, seek out those places that are positioned to become more walkable, and determine potential locations of future walkable places. This type of assessment will help determine where infrastructure and other built environment improvements are needed. Since high-density walkable urban places seem to account for a small amount of a metropolitan area’s existing land mass, it is probable that the infrastructure cost per dwelling unit or commercial square foot will be a fraction of that of existing low-density drivable suburban infrastructure costs.46 At the same time, the apparent supply-demand mismatch for walkable places may be contributing significantly to the price premium these places demand. To the extent that this is the case, the short- and medium-term shortage of walkable places makes them inaccessible (unaffordable) to many people who desire to live in such places. As such, it is important to have an affordable housing strategy in place while those improvements are being implemented. Beyond the direct and indirect policy implications, the results of this study should also inform five sets of stakeholders: private developers and investors, social equity advocates, the public sector, place managers (such as business improvement districts and redevelopment agencies), and citizen-led groups/activists. The first type of stakeholder, including investors, real estate developers, financers, lenders, etc., can use the walkability metrics to guide their investment and development decisions. The walkability

12 BROOKINGS | May 2012 continuum based on IMI scores provides a classification system that is tied to economic performance. As such, a real estate developer and his investors may decide that they would like to target their investment into places at level 3 along the continuum, hopefully growing into a “4” because it may represent a place that is about to experience a significant increase in underlying property value. Stakeholders can clearly delineate what places fall under level 3 as well as track its progress against established metrics. A risk-sensitive institutional investor may decide that it only wants to purchase real estate assets in level 5 places since they have a proven track record of walkability and resulting high economic performance. For advocates, a place’s social equity performance level could help socially responsible investors focus on walkable urban places and projects where the need for increased affordable housing is most pressing or help highlight inequities that need to be addressed. In addition, stakeholders could measure the effectiveness of social equity policies, such as an affordable or workforce housing strategic plan. Public stakeholders primarily provide the capital improvements for infrastructure and the operating funding for social service and public safety activities. The walkability, economic, and social equity metrics can inform funding allocation decisions and can be used to measure the effectiveness of that spending. For example, the U.S. Department of Housing and Urban Development could use these metrics not only to guide their selection of grantees for the next round of Sustainability Challenge Grants, but also to empirically track the progress of their grantees and hence establish further accountability standards. Federal and state departments of Transportation could require local jurisdictions to meet local economic and social equity standards in their grant applications and monitor their progress relative to these self-selected goals when determining whether to approve funding requests. Further, other granting agencies may only be interested in awarding funding to those places that already meet certain equity standards, but would like to enhance their economic performance related to walkability. Alternately, agencies may decide to invest in places that are advanced in their walkability standings but need to further social equity goals. The next set of stakeholders includes on the ground place managers, public and private, that provide the strategy for and management of these places. For example, a BID may look to the walkability continuum to understand their current standing and set a goal to move to up a level. As such, these organizations can clearly lay out a roadmap for how to move further along the continuum with inbuilt justification (either for internal use by the organization or external use to secure funding) for implementing a strategy to do so. Additionally, planning agencies can use this continuum to evaluate their jurisdictions and establish strategic plans for strengthening (or increasing the number of) walkable urban places within their domain. The final set of stakeholders is citizen-led groups and activists who can use their neighborhoods’ IMI scores to better understand their strengths and weakness and, as such, to leverage positive, pedestrian-oriented change. By helping to diagnose neighborhoods’ walkability, the IMI provides a tool for “tactical” and “Do-It-Yourself” (DIY) urbanites to engage communities, not only to advocate for change but also to actually begin to improve their neighborhoods. There is also the opportunity for all five stakeholders to learn from comparable walkable urban places in their metropolitan area or other metropolitan areas. It is common for various local jurisdictions, a chamber of commerce and other regional organizations to sponsor visits to other metropolitan areas to exchange lessons learned and generate new ideas. Using the walkable urban place definition and performance metrics, they can compare performance in much more depth and on an apples-to-apples basis. Evidence is beginning to show that demand for walkable places is on the rise. We believe the supply is already falling short of the demand and the findings outlined here around economic performance justify ameliorating this mismatch by facilitating this kind of placemaking.

BROOKINGS | May 2012 13 I. Appendix

Appendix Table 1. Social and Economic Statistics in the Washington D.C. Metropolitan Area Based on Walkability Levels

Walkability Classification Levels 1 2 3 4 5 Washington Metro Area Per capita income (2010)a $21,687 $25,173 $34,097 $49,075 $56,247 $36,618 Average household income (2010)a $53,068 $69,252 $88,395 $93,145 $103,145 $81,213 Average disposable income (2010)a 41,773 $55,799 $69,364 $74,234 $77,523 N/A Unemployment rate (2010)a 23.2% 9.1% 10.5% 8.4% 11.2% 7.5% Diversity index (2010)a 23.0% 74.6% 51.8% 48.4% 47.1% 70.3% % Change white (2000 to 2010)b -20.6% -33.1% 38.7% 122.8% 148.9% 2.19% % Change black (2000 to 2010)b 66.4% -.03% 20.8% -31.8% -.05% 12.41% % High school as highest degree (2010)b 22.2% 17.8% 12.7% 7.8% 11.2% 13.2% % Bachelors as highest degree (2010)b 9.3%% 9.2%% 14.7%% 22.2% 17.6% 16.8% % Graduate/ professional as highest degree (2010)b 2.3% 7.7% 13.5% 28.0% 27.8% 14.8% Average headwayc (in minutes) 5.55 5.92 6.66 4.16 4.47 6.6 Share of jobs in region accessible within 90 minc 52% 39.2% 45.2% 60.3% 61.2% 36.6% Average number of parks (2010)a 0 1.33 1.42 2.3 4.8 2.11

Sources: a: ESRI Demographics, b: Census 2010, c: Adie Tomer and others, “Missed Opportunity: Transit and Jobs in Metropolitan America,” Washington: Brookings, 2011.

Further discussion of the methodology At the onset of this study, we conducted a literature review of the relationship between the built environment and walkability, including examining preliminary operational definitions for walkability. We also surveyed literature on the concept of regional significance/serving, attempting to identify established, defining parameters for the term. Further, we reviewed the literature on social equity and related definitions and measures for such. Primarily, the literature review served to inform the development of an expert panel (Delphi panel) survey and related overview materials. We identified and invited 20 potential Delphi panel participants, including academic and academic- affiliated experts on a range of topics related to walkable urban places, such as urban economics, sustainability, urban design, social equity, transportation, walkability, urban planning, housing, geography, and demography. Delphi panelists were to provide feedback that would inform the development of an operational definition of walkable urban places. Specifically, the Delphi Panel survey presented participants with a preliminary list of potential walkable urban place parameters (based on the results of a literature review) and asked them to rate each parameter’s importance relative to “walkable urban placemaking” as well as comment on potential measurement methods, data sources, and appropriate “scoring” mechanisms for each factor. Another key objective of the Delphi panel was to elicit input that would contribute to the development of a list of economic and social equity metrics with which to gauge walkable urban places’ performance. Delphi Panel participants were asked to react to a list of potential social equity and economic metrics. Additionally, we asked panelists to provide input as to the best methodology by which to measure walkability and define neighborhood boundaries. We also solicited their help with defining several related terms, including “regional significance/serving” and “critical mass.” The survey also allowed participants to suggest other potential parameters critical to the development and success of walkable urban places.

Economics/Development Panel We convened 13 economic development and real estate industry experts for a four-hour panel in which we discussed the criteria for walkable urban places and key economic performance metrics and gathered feedback regarding a preliminary list of walkable urban place candidates and their boundar-

14 BROOKINGS | May 2012 ies. Discussion centered primarily on the issue of regional significance, in terms of its definition and measurement; how regionally significant places differed fundamentally from locally serving places; and its overall importance as a criterion for distinguishing walkable urban place types.

Government Agency Panel We convened 12 representatives of federal and local government agencies (including U.S. departments of housing and transportation, the Green Building Council, and the Washington Metropolitan Area Transit Authority) for a four-hour session. The federal panelists focused their discussion primarily on implementation issues (how they would integrate our methodology and results into their agendas and decision-making processes) and the identification of key performance measures.

Social Equity Panel We convened 13 social equity experts for a four-hour panel. Social equity panelists focused primarily on identifying the most appropriate social equity metrics for walkable urban places. They suggested establishing metrics that were relative to their corresponding region as well as considering contextual issues in defining metrics, or rather, a set of metrics.

Finance Panel We convened six representatives of the real estate finance community for a four-hour panel in which we discussed the decision-making process for real estate finance, especially as it relates to walkable urban places. The purpose of the panel was to ensure that the walkable urban places study produced a methodology and deliverable that the finance community can incorporate into their underwriting and/ or lending approval and selection process.

Walkability – The Irvine Minnesota Inventory (IMI) The IMI, one of the first micro-scale audit tools to be developed, measures a comprehensive set of built environment features, and has been widely used in the urban planning, design and public health fields. Auditors received in-class and on-site training; they collected data on test segments, which were then tested for reliability and validity. Auditors for this study included George Washington University undergraduate geography students who participated as part of a service learning partnership and other independent contractors.

Real Estate and Social Equity Data Collection and Sources CoStar served as the primary database for commercial property data. We obtained nearly 1,200 real estate performance data points, including, but not limited to, square footage, vacancy, leasing and rental rates, and absorption rates. We collected this data for a variety of property types, including office (class A-F), flex, industrial and retail, across multiple time points. Longitudinal (yearly and quarterly) data was available for most variables dating back to 2000 (retail data was provided historically to 2006). While CoStar provided a robust set of economic indicators, it does not include owner-occupied related data. Tax Assessor Data served as the starting point from which we estimated the floor area of government-owned buildings and owner-user occupied space. While other real estate data sources such as CoStar and REIS do not provide this data, most tax assessors do assign valuations to government- owned buildings and other tax-exempt properties from which floor area may be derived. To calculate approximate floor area, we aggregated building valuations by land use type and divided them by an assumed value per square foot.47 Tax assessment data is collected and maintained at the county level, however. As such, significant inconsistencies between assessors datasets exist that limit their usefulness for estimating floor area. Zillow provided point based data reflecting for-sale owner occupied residential property specific to the boundaries defined by the study. This data set includes square footage of residential property, assessed value, and tax information for 2005 and 2010. This data is categorized based on type of dwelling (single family, condo, duplex/triplex, and other). REIS provided the total floor area of rental apartments housed in buildings with 40 or more dwelling units. The dataset includes building-specific data including building age, total units, average rent

BROOKINGS | May 2012 15 per unit, number of bedrooms per unit, and comparable rents over a 5-year period within a defined area. REIS does not account for small rental apartment properties, however. As such, this dataset does not accurately represent gross rental apartment space in areas where the apartment stock is primarily housed in small buildings. ESRI Demographic data served as the primary source of demographic data. With the elimination of the long form Census in 2010, we were unable to customize census data to our defined geographies. ESRI data, available at the block group geography, included social equity-related measures such as income, unemployment, and education attainment. We did obtain absolute count data regarding race and ethnicity at the smallest geography available (block) for 2000 and 2010 directly from the Decennial Census. Brookings Institution Transit Accessibility Data provided information on the availability of public transit, average wait times, and percent of metropolitan jobs accessible at the block group geography. We aggregated block groups based on our geographies and produced a population-weighted value for each place. Center for Neighborhood Technology (CNT) commissioned by the D.C. Office of Planning provided block group level data of housing and transportation costs as a percent of area median income, which were used to measure social equity. ESRI Business data served as a source of industry sector and business data, including retail sales and employment data. Data were collected based on our geographies. Compared to other existing databases reporting on similar data, ESRI business data seemed incomplete. As such, we used (stan- dardized) Z-scores for variables from this dataset rather than the actual raw numbers provided.

16 BROOKINGS | May 2012 Endnotes Reformed: A Review of the Land Use Regulations in the Nation’s 50 Largest Metropolitan Areas,” (Washington: 1. Christopher B. Leinberger is a nonresident senior fellow Brookings, 2006); Robert Lang, Jennifer Lefurgy, and at Brookings, Charles Bendit Distinguished Scholar and Steven Hornberg, “From Wall Street to Your Street: research professor at the George Washington University New Solutions for Smart Growth Finance,” Alexandria: School of Business, and president of LOCUS, a national Metropolitan Institute of Virginia Tech, 2005; and Center network of real estate developers and investors. Mariela for Transit-Oriented Development and others, “Fostering Alfonzo is a research fellow at the Polytechnic Institute of Equitable and Sustainable Transit-Oriented Development: New York University and president of Urban Imprint. Note, Briefing Papers for a Convening on Transit-Oriented the name of the Brookings affiliate is listed first. Development,” February 24-25, 2009.

2. Joe Cortright, “Driven to the Brink: How the Gas Price 11. Christopher Leinberger, “Financing Progressive Spike Popped the Housing Bubble and Devalued the Development,” (Washington: Brookings, 2001). Suburbs,” Chicago: CEOs for Cities, 2008; and Matthew Strozier, “Mapping Home-Value Drops by Zip Code,” The 12. Center for Transit-Oriented Development and oth- Wall Street Journal, June 28, 2011. Available at http:// ers, 2009; Christopher Leinberger and Sarah Kavage, blogs.wsj.com/developments/2011/06/28/mapping-home- “Barriers to Developing Walkable Urbanism and Possible value-drops-by-zip-code. Solutions,” (Washington: Brookings, 2007).

3. National Association of Realtors, “The 2011 Community 13. Gary Pivo and Jeffrey Fisher, “The Walkability Premium Preference Survey: What Americans are Looking for When in Commercial Real Estate Investments,” Real Estate Deciding Where to Live,” Washington, 2011. Available at Economics, 39, (2), 185–219, 2011; and Cortright, 2009. http://www.realtor.org/research. 14. Nancy Wells and others, “Environment, Design, and 4. John McIllwain, “Housing in America: The Next Decade,” Obesity: Opportunities for Interdisciplinary Collaborative (Washington: Urban Land Institute, 2010) Research,” Environment Behavior, 39 (1), 6-33, 2007; and Larry Frank and Peter Engelke, “How Land Use and 5. Jonathan Levine, Aseem Inam, and Gwo-Wei Torng, “A Transportation Systems Impact Public Health: A Literature Choice-Based Rationale for Land Use and Transportation Review of the Relationship between Physical Activity and Alternatives: Evidence from Boston and Atlanta,” Journal Built Form,” Centers for Disease Control, 2000. of Planning Educating and Research, 24: 317–330, 2005. 15. A comprehensive study revealed that shifting 60 percent 6. Arthur C. Nelson, “Resetting the Demand for Multifamily of development toward places that encompass the com- Housing: Demographic & Economic Drivers to 2020,” ponents of walkable urban places would save 85 million Presentation to National Multi Housing Council, 2010. metric tons of CO2 annually, by 2030. Reid Ewing and others, Growing Cooler: The Evidence on Urban Development 7. Jonathan Levine and Larry Frank, “Transportation and and Climate Change, Washington, Urban Land Institute: Land-Use Preferences and Residents’ Neighborhood 2008; Larry Frank, and others, “Carbonless Footprints: Choices: The Sufficiency of Compact Development on the Promoting Health and Climate Stabilization through Atlanta Region. Transportation 34(2):255-274, 2007. Active Transportation,” Preventive Medicine, 50, S99- S105, 2010. 8. Joe Cortright, “Walking the Walk: How Walkability Raises Home Values in U.S. Cities,” Chicago: CEOs for Cities, 16. Gary Pivo and Jeffrey Fisher, “Toward Sustainable and 2009. Responsible Property Investment Indices,” Prepared for Strengthening the Green Foundation: Research and Policy 9. One study revealed that one additional Walk Score point Directions for Development and Finance held at Tulane was associated with a $500-$3,000 increase in home sale University, New Orleans, March 10-11, 2011. value. On the commercial side, a ten-point increase in Walk Score was tied to a 9 percent increase in office and 17. Christopher Leinberger, “Footloose and Fancy Free: A retail property values. Field Survey of Walkable Urban Places in the Top 30 U.S. Metropolitan Areas,” (Washington: Brookings, 2007). 10. See Levine, Inam, & Torng, 2005; Rolf Pendall, Robert Puentes, and Jonathan Martin, “From Traditional to 18. Leinberger, 2007.

BROOKINGS | May 2012 17 19. These were areas funded as part of Washington 25. Walk Score generated a population-weighted score D.C.’s Neighborhood Investment Fund. Available at for each of our neighborhoods based on our defined http://dmped.dc.gov/DC/DMPED/Opportunities/ boundaries. Grant+Opportunities/Neighborhood+Investment+Fund 26. Seven of the neighborhoods for which IMI data was col- 20. Our initial list included over 400 potential places to study. lected—Ballston, Courthouse, M Square Research Park, As the fieldwork and analysis of the built environment Minnesota Avenue, Prince George’s Plaza, U Street/Shaw, features is intense and time-consuming, we developed and West Hyattsville—were ultimately not “selected” into a rubric by which to define and narrow the potential our sample. However, as the IMI scores were generated for “universe” of places. We decided to use neighborhoods’ them, we are reporting here for information only. These Walk Score rankings to place them along a walkability con- neighborhoods were not included in the regression. We tinuum. Walk Score is ideal since it does not require first- collected data for three other neighborhoods—Rosslyn, hand onsite data collection. However, to do so, we drew Foggy Bottom, and Logan Circle—that proved faulty so boundaries for each place within that “universe” so that they were eliminated from the analysis. a Walk Score could be generated. As such, we delineated the three criteria outlined herein to arrive at a manage- 27. To help us operationalize the difference between regional able number of places from which we would later sample: and local-serving places, we collected economic perfor- one established the geographical areas from which we mance data from CoStar. We gathered this data for the would draw; the second addressed our original aim to same 66 places in the sample for which built environment focus on places that were either walkable or aspired to data was collected and also for an additional 37 places be; the third reflected this project’s focus on urbanized that were part of a convenience sample. places. 28. Kristen Day and others, “The Irvine-Minnesota Inventory 21. According to its website, the Metropolitan Washington to Measure Built Environments: Development. American Council of Governments is an independent association of Journal of Preventive Medicine 30(2):144-52, 2006. “elected officials from 22 local governments, members of the Maryland and Virginia state legislatures, and members 29. Using GIS, we determined the total number of segments of the U.S. Congress.” The local governments members present within each of the 66 places. We selected a sam- are: the District of Columbia; Bowie, College Park, Charles ple of segments for each site in order to minimize data County, Frederick, Frederick County, Gaithersburg, collection time, as, on average, it takes 8-10 minutes to Greenbelt, Montgomery County, Prince George’s County, observe a segment. For places larger than 400 acres, we Rockville, and Takoma Park in Maryland; and Alexandria, sampled 20 percent of the segments; for places between Arlington County, Fairfax, Fairfax County, Falls Church, 250-400 acres, we sampled 25 percent of segments; for Loudoun County, Manassas, Manassas Park, and Prince places smaller than 250 acres, we sampled 30 percent of William County in Virginia. segments, and for places with less than 75 segments, we sampled 35 percent of segments. We sampled a minimum 22. We chose to eliminate Census designated rural blocks of 10 segments and a maximum of 50 segments from to create a more manageable population of places from each site. On average, we collected data on 25 percent of which to eventually sample and thus keep within the the segments within a neighborhood. Data were cleaned scope of our study. Future studies may examine the appli- and entered into SPSS. Note, the IMI was designed to cability of our findings within rural areas. collect built environment data at the block (or segment) scale. See the Appendix for a more thorough description 23. We did not include closed campuses (such as traditional of the methods. universities and military bases.) 30. Mariela Alfonzo, Jennifer Wolch, and Genevieve Dunton, 24. Note that the neighborhoods in our sample vary in “Streamlining Walkability Audits for Smart Growth- acreage; we did not set an upper limit with respect to Physical Activity Assessments,” Presentation to Society neighborhood size but rather followed the respective for Behavioral Medicine Annual Conference, April 29, planning entity’s definition for a specific neighborhood. 2007; Mariela Alfonzo, “A Mall in a Former Life: How We believe that defining neighborhoods based on existing Converting Failing Malls Into Mixed-use Neighborhoods governmental/jurisdictional boundaries produces more Impacts Sense of Community,” PhD dissertation, policy-relevant findings than does using an a priori range University of California, Irvine, 2007; Mariela Alfonzo (e.g. ¼ mile radius) or arbitrary neighborhood size. and J. Kaplan “State of Place,” Houston Magazine, 2005; Brian E. Saelens and Susan L. Handy, “Built Environment

18 BROOKINGS | May 2012 Correlates of Walking: A Review,” Journal of Medicine and places (levels 4 & 5) and non-walkable urban places (levels Science in Sports and Exercise, 40(7S), S550–566 (2005). 3 and under).

31. We have collected IMI data on all 66 places in our sample. 37. Household income served as a proxy for other factors – Currently, however, we are reporting on only 61 of those crime, educational quality, etc. – that could also impact because problems and irregularities in the data for five economic performance. Future studies should control for neighborhoods in the sample could not be corrected for other neighborhood and regional level factors that could inclusion in this study. also impact economic performance.

32. The differences between these categories are statistically 38. A percentage rather than an actual figure is presented for significant. For example, tier one regional-serving office Average Retail Sales because we believe there may have places are significantly different from tier two regional- been consistent underreporting of retail revenues (based serving office places with respect to office rents; tier one on the database we used) and therefore it is more appro- regional-serving office places are also significantly differ- priate to report the magnitude of this difference rather ent from local-serving places. Tier 1 regional-serving retail than the actual number. places are significantly different from tier two regional- serving retail places with respect to retail revenues. 39. Capitalization Rate is the net operating income of a real estate property divided by the market value. In other 33. Throughout this study, the term statistically significant words, the capitalization rate serves as an indicator of the refers to a finding that has less than a 5 percent prob- current market value of a real estate property on the basis ability of being attributed to chance. In other words, the of net operating income. It is an indirect measure of how finding is not random. quickly a property will pay for itself – or be fully capital- ized. A cap-rate is a commonly used tool for investors to 34. To analyze the relationship between walkability and social quickly value a property, evaluate risk, and estimate his or equity, we chose to implement an independent sample her potential rate of return. t-test (that compares the average difference between two groups on a given variable– such as income). This approach 40. We used CoStar data from 2000-2010 to derive capitaliza- is different from the analysis we implemented to analyze tion rates for the walkable urban places in our sample, the relationship between walkability and economic perfor- splitting them into before the recession (pre 2007) and mance (linear regression, which analyzes the amount of after the recession. We had data for 27 places from before variance accounted for by one variable – walkability – in 2007 and 13 places from after 2007 for which IMI scores predicting another variable – retail sales). Because we did had been calculated. not believe that the relationship between walkability and social equity was a linear one, but rather were interested 41. Mariela Alfonzo and others, “The Relationship of in how more walkable neighborhoods vs. less walkable Neighborhood Built Environment Features and Walking,” neighborhoods faired with respect to social equity, we felt Journal of Urban Design, 13, 1, 29-51 (2008). that a t-test was more appropriate. 42. While there do seem to be some large differences between 35. IMI level 1 is more than two standard deviations away from IMI levels with respect to some of the transit indicators, the mean; IMI level 2 is more than one standard devia- in some cases, we do not have enough places within our tion from the mean. Places within these two levels have sample to indicate whether the differences observed poor to very poor walkability, respectively. Note that there are due to chance or are statistically significant. We will were a limited number of places in our sample that had an continue to explore this issue in future research that will IMI level of 1 or 2. As such, we may have been unable to collect more data from a variety of different neighbor- detect statistically significant differences. More research is hoods across several metropolitan areas. needed to better understand how places with low and very low walkability fare with respect to social equity. 43. Since our sample included all places with a Metrorail stop automatically, it is likely that these numbers reflect a 36. The findings for office rents, retail rents, retail sales, for- higher average than the region overall. sale housing values, and residential rents are based on linear regression analyses of a place’s IMI score and each 44. These are just illustrative examples meant to convey the individual economic indicator. The findings for cap rates point that we need to further explore the relationship were based on an independent samples t-test that exam- between social equity indicators and walkability. ined the differences in cap rates between walkable urban

BROOKINGS | May 2012 19 45. A statistically significant finding has a p-value of less than 5 percent, which means that there is less than a 5 percent probability that the a finding is due to chance alone. A trend has a p-value between 5 and 10 percent and as such, is not as strong of a finding. However, in the case of unemployment rates, we may not have enough variability in our sample to observe statistically significant differences. Differences in unemployment will be further explored in Phase Two of this study.

46. Infrastructure provision, whether roads, sewer and water lines, transit, electric distribution, police and fire services, etc., are all linear functions. The cost per mile of running a sewer line is roughly the same for walkable urban versus drivable sub-urban provision (it may cost fractionally more for walkable urban but in the final analysis, that cost difference is not consequential). In a drivable suburban environment, that fixed cost per mile is spread over anywhere from four dwelling units per acre to 0.5 dwelling units per acre and less. In a walkable urban environment, that similar fixed cost per mile is spread over anywhere from 10 units per acre to hundreds of units per acre.

47. Based on current construction costs in the Washington MSA, we assume an average value of $180 per square foot of built space for drivable suburban places, or those with IMI scores below 3.39. For walkable urban places with IMI scores over 3.39, we assume an average of $225 per square foot.

20 BROOKINGS | May 2012 Acknowledgements The authors thank those who directly worked on this study, including members of the Metropolitan Policy Program: Nicole Svajlenka, Martha Ross, and Alice Rivlin. A special thanks to David Wood, director of the Initiative for Responsible Investment at Harvard University’s John F. Kennedy School of Government, for his continued guidance, key insights, and input throughout and to Lisa Rother for coordinating the non-academic panels. Joe Cortright, Daniel Rodriguez, Robert Puentes, and Alan Berube provided valuable comments on earlier drafts of the paper, Susan Kellam provided editorial assistance, Alec Stewart also contributed to the data collection, synthesis, and graphics. Finally, thanks to Daniel Taytslin, Anthony Colello, and Lauryn Douglas for their data collection efforts. We also wish to thank the over 80 members of the five panels who contributed their time and wisdom to our understanding of the multitude of issues relevant to this research.

The Metropolitan Policy Program at Brookings thanks the Rockefeller Foundation, the Summit Foundation, and the Prince Charitable Trusts for their support of this project and the John D. and Catherine T. MacArthur Foundation, the George Gund Foundation, the F.B. Heron Foundation, the Rockefeller Foundation, and the Heinz Endowments, for their general support of the program. The authors thank the ULI Foundation, Capitol Riverfront BID, and Jair Lynch Development Partners for additional support.

Finally, we wish to thank the program’s Metropolitan Leadership Council, a bipartisan network of individual, corporate, and philanthropic investors that provide us financial support but, more importantly, are true intellectual and strategic partners. While many of these leaders act globally, they retain a commitment to the vitality of their local and regional communities, a rare blend that makes their engagement even more valuable.

For More Information For General Information Christopher B. Leinberger Metropolitan Policy Program at Brookings Non-Resident Senior Fellow 202.797.6139 Metropolitan Policy Program at Brookings www.brookings.edu/metro 202.797.6000 [email protected] 1775 Massachusetts Avenue NW Washington D.C. 20036-2188 telephone 202.797.6139 fax 202.797.2965

The Brookings Institution is a private non-profit organization. Its mission is to conduct high quality, independent research and, based on that research, to provide innovative, practical recommendations for policymakers and the public. The conclusions and recommendations of any Brookings publication are solely those of its author(s), and do not reflect the views of the Institution, its management, or its other scholars.

BROOKINGS | May 2012 21 About the Metropolitan Policy Program at the Brookings Institution Created in 1996, the Brookings Institution’s Metropolitan Policy Program provides decision makers with cutting- edge research and policy ideas for improving the health and prosperity of cities and metropolitan areas including their component cities, suburbs, and rural areas. To learn more visit: www.brookings.edu/metro.

Brookings 1775 Massachusetts Avenue, NW Washington D.C. 20036-2188 telephone 202.797.6000 fax 202.797.6004 web site www.brookings.edu

telephone 202.797.6139 fax 202.797.2965 web site www.brookings.edu/metro Transit-Oriented Development in the Chicago Region Efficient and Resilient Communities for the 21st Century CONTENTS

2 Executive Summary 15 Income 2 Transit-Oriented Development in the Chicago Region, 17 Families 2000–2010 18 Renters and Owners 5 Introduction 19 Changes in Transportation Patterns 5 What is Transit-Oriented Development? 26 Changes in Jobs 5 TOD In The Region 29 Comparing Transit Zones in Chicago 7 Performance Measures 30 Chicago Region Transit Zones by Type 8 Methodology 32 Performance by Transit Zone Type 8 Evaluating TOD Performance in the Chicago Regions 36 Transit Zone Metrics 10 Analysis 37 TOD Typology Methodology 10 Household Growth Not Keeping Up in Transit Zones 38 Case Studies 14 Cost of Living 52 Policy Recommendations 15 Benefits of Transit Are Not Equitably Distributed

ACKNOWLEDGEMENTS

Transit Oriented Development in the Chicago Region: Efficient and Resilient Communities for the 21st Century was developed by the Center for Neighborhood Technology as an assessment and plan of action for the Chicago Region’s transit shed. This report identifies the strengths and weaknesses of our regional transit shed’s performance over the last decade and develops policies to optimize our fixed rail public transit assets. This report was written by Yonina M. Gray with guidance and support from CNT’s Transportation and Community Development Department and their Geography, Research, Information Department (GRID). In particular, the input of Sofia Becker, Albert Benedict, Scott Bernstein, Sarah Campbell, David Chandler, Cindy Copp, Paul Esling, Cecilia Gamba, Jacky Grimshaw, Michael Healy, Adam Mays, Jen McGraw, Taylor McKinley, Steve Perkins, Jared Pilbeam, Kyle Smith, Iris Thomas, and Linda Young was greatly appreciated. The report was designed by Kathrine Nichols of CNT, with copy editing by Bill Hurd and Ryan Kilpatrick. This report was commissioned and made possible by the Regional Transportation Authority with generous support from the Searle Funds at the Chicago Community Trust and The Grand Victoria Foundation. CNT wishes to thank the following individuals and organizations who provided input to the development of this report: Joel Bookman, Local Initiatives Support Corporation (LISC) Mike Holzer, LEED Council David Brint, Brinshore Catherine Kannenberg, Metra Anne Canby, One Rail Coalition Angela Masseros, Village of LaGrange María Choca Urban, Cook County Bureau of Economic Jason Osborn, McHenry County Development Kurtis Pozsgay, Berwyn Development Corporation Steve Friedman, S.B. Friedman George Ranney, Prairie Crossing Karie Friling, Village of Oak Park Craig Sklenar, City of Evanston Leslie Palmer Garcia, Chicago Housing Authority Jack Swenson, Jack Swenson & Associates Reggie Greenwood, Chicago Southland Economic David Waden, City of Elgin Development Corporation (CSEDC) Nathan Werner, City of Elmhurst Anthony Griffin, Berwyn Development Corporation Christopher Yake, Reconnecting America Benet Haller, City of Chicago Department of Housing and Economic Development Transit-Oriented Development in the Chicago Region Efficient and Resilient Communities for the 21st Century

PREPARED BY THE CENTER FOR NEIGHBORHOOD TECHNOLOGY

APRIL 2013

FUNDED BY GAYLORD AND DOROTHY DONNELLEY FOUNDATION GRAND VICTORIA FOUNDATION SEARLE FUNDS AT THE CHICAGO COMMUNITY TRUST

COVER: METRA HEADING NORTHWEST FROM CHICAGO Photo Credit: Jim Watkins (Flickr user phototravel1/Jim Watkins)

Transit-Oriented Development in the Chicago Region, 2000–2010

Mixed-use centers anchored by public transit are essential Between 2000 and 2010, four of the nation’s five to the triple bottom line, or the economic, environmental, metropolitan regions with extensive rail transit and social sustainability of the Chicago Region. With systems (those with 325 or more stations)—New York, the publication of GO TO 2040 in 2010, the Chicago Philadelphia, Boston, and San Francisco—achieved Metropolitan Agency for Planning (CMAP) put forth a growth and development within their transit zone, or the vision to grow the transit-oriented development (TOD) land area within one half-mile of their fixed passenger rail areas of the Region and make them communities of stations. Only Chicago, the fifth region in this extensive choice. In 2012 the Center for Neighborhood Technology system cohort, saw a decline in development around (CNT) built on this vision with the publication of transit relative to growth in the broader region. During Prospering In Place, which honored GO TO 2040 for its the last decade in the Chicago Region, a household’s commitment to reconnect land use, transportation, and typical transportation costs, one of a household’s two the economy, and recommended the locations in the largest expenses, rose at a faster rate than median Chicago Region that had the best prospects for growth— household incomes. As a result, Chicago Region residents and hence warranted priority access to public and private are paying higher transportation costs and experiencing resources. Prospering in Place was also a cautionary story of reduced access to jobs. This report compares development how a blueprint alone, without a place-based framework in the areas around the Chicago Region’s passenger rail for development, will not reverse the Region’s undesirable transit stations to that of the Chicago Region as a whole, trend toward sprawl and disinvestment. This report as well as to its four peer regions with extensive rail builds on that story, melding those lessons learned with systems on several TOD performance metrics, including our new understanding of Regional trends to yield a set of household growth, vehicle miles traveled (VMT), and recommendations to optimize the promise of Chicago’s jobs. We are conducting this comparison to illustrate how historically magnetic transit zones. Chicago compares with national trends and then delving

CHICAGO SKYLINE Photo Credit: Flickr User mike appel, CC License

2 REGIONAL TOD ANALYSIS Chicago Region transportation costs rose faster than incomes into the causes of any shortcomings in order to make Our examination recommended that the Chicago Region policy recommendations. These recommendations seek needs to make these fundamental commitments: to get the Region on track towards maximizing the return 1. Create TOD zones. A transit zone is an area defined by a on public investment in transit and creating a ripple of half-mile radius around a fixed rail station. Many of the barriers benefits for the communities that it serves. to TOD are embedded in the land use policies of local governments, and are further complicated by regional, state, Changes in TOD demographics and development patterns and federal policies. Creating TOD zones helps eliminate from 2000 to 2010 were not the same throughout the barriers to development. Chicago Region. The differences are often explained by 2. Preserve affordable housing. To realize the full regional the characteristics of each transit station area. Using the benefits of quality transit and TOD, mixed-income housing National TOD Database,1 Transit-Oriented Development must be preserved and expanded in TOD zones. This may be accomplished through a combination of policies that prioritize in the Chicago Region: Efficient and Resilient Communities housing assistance to TOD communities and enforce existing for the 21st Century evaluates the dynamics of each of the state requirements for affordable housing in all communities. Region’s 367 CTA and Metra stations and identifies those 3. Match jobs and transit. Many limitations of metropolitan transit zones that are performing well: anchoring vital, Chicago’s transit system—as well as high transportation costs, walkable communities that possess an affordable, high traffic congestion, and air pollution—stem from job centers quality of life with minimal impact on the environment. moving away from mixed-income neighborhoods. A more efficient and healthier pattern may be established through systematic efforts Transit zones that have performed well are the first to expand transit services to job centers, site new employers in step in pointing us in the right direction. They teach existing transit-served communities, and promote incentives to commute through transit, biking, or walking. us the importance of setting policies and priorities that will grow our economy by connecting people to jobs 4. Provide alternatives to car ownership. Even dedicated transit users often are forced to buy cars to meet transportation and strengthening our communities through spatial needs that transit cannot efficiently fill. To provide alternatives efficiency. Understanding the challenges of transit zones to car ownership, the Region should support the growth of car- with flawed development patterns is yet another step. This sharing services, build more extensive bicycle infrastructure, report quantifies and qualifies the performance of TOD and establish more pedestrian-friendly streetscapes. in the Chicago Region in order to establish our strengths 5. Prioritize TOD across agencies. While public agencies can and weaknesses in optimizing the tremendous transit set favorable conditions for TOD, public investments of more assets that we have. than $1 billion are needed through 2040 to remove impediments to redevelopment and attract the much larger private investments that will build the mixed-income housing, mixed-use buildings, and functioning businesses that constitute TODs.2 Coordinated priorities and investments among a range of public agencies are needed to generate these effective public investments.

By taking these actions, transit and transit-oriented development can become the pillars of the Chicago Region’s economic development strategy over the next decade, improving the Region’s competitiveness and making it a better place to live and work.

The benefits of TOD are many. Individuals, communities, local governments, and businesses in the Chicago Region all receive value from TOD. The Center for Transit-Oriented Development (CTOD) describes some of the benefits of well- designed TOD as follows:

1. Reduced household driving and thus lowered regional congestion, air pollution, and greenhouse gas emissions

2. Walkable communities that accommodate more healthy and active lifestyles

3. Increased transit ridership for trips to work and fare revenue

4. Potential for added value created through increased and/ or sustained property values where transit investments have occurred

5. Improved access to jobs and economic opportunity for low-income people and working families

6. Expanded mobility choices that reduce dependence on the automobile, reduce transportation costs, and free up household income for other purposes3

These benefits convey the potential of TOD. Transit-Oriented Development in the Chicago Region: Efficient and Resilient Communities for the 21st Century compares this potential with the reality of TOD development in the Region. It tracks the performance of the Region’s 3674 fixed Metra and Chicago Transit Authority (CTA) rail stations and station areas that were operating from 2000 to 2010. It asks whether these zones are attracting households more successfully than the Region as a whole and whether residents near transit take full advantage of this transportation asset.

4 REGIONAL TOD ANALYSIS Introduction

What is Transit-Oriented TOD In The Region

Development? The Chicago Region has been concentrating its development around transportation since the 1850s; first there were The concept of TOD was defined by planners in the 1980s horse-drawn trolleys, then street cars and then rapid transit who sought to develop communities with mixed land uses, and buses. Chicago’s development has always been oriented dense residential development, and high-quality pedestrian around transit. One of Chicago’s first elevated rail lines, connections. According to the Center for Transit-Oriented the Lake Street “L,” was constructed in 1894 by developers Development (CTOD), “Transit-oriented development, or intent on drawing residents to their Garfield Park develop- TOD, is a type of community development that includes a ment. “L” stations became the anchors of neighborhood mixture of housing, office, retail and/or other commercial shopping districts, providing a predictable, steady stream of development and amenities integrated into a walkable customers. Developers located multi-family buildings near neighborhood and located within a half-mile of quality public “L” stops, giving their tenants ready access to jobs. The “L” transportation.”5 TOD’s mix of residential, retail, office, was the mobility backbone of Chicago. open space, and public land uses in a walkable environment make it convenient for residents and employees to travel With the end of World War II, the United States embarked on by transit, bicycle, foot, or car. This dense mix of uses is a prolonged love affair with the car, constructing an interstate designed to attract residents, workers, and visitors. highway system to speed up the commute between the city and the suburbs. Auto ownership skyrocketed—and transit TOD is not only about proximity to transit; the Regional systems were allowed to deteriorate. By 1958, Chicago’s Transportation Authority (RTA) defines TOD as “Moderate extensive streetcar system had been dismantled in favor of to high density, mixed use communities generally located buses, but the rail system, fortunately, continued to move within a half-mile radius (10 minute walk) of a rail or bus tens of thousands of Chicagoans every day. station designed to maximize walkability and transit access.” Thirty years ago, the City of Chicago announced its CNT estimates that in 2012 typical annual car ownership per intention to tear down the Lake Street elevated “L” train 6 vehicle in the Chicago Region cost $8,946, as compared with line. The response to this plan was a watershed for transit transit costs of $1,032, a difference of $7,914. The benefits of in the Chicago Region. Residents of Chicago’s West Side 7 transit use also include an increased quality of life, enhanced and Oak Park came together to fight for the preservation of social capital, and a healthier environment, to name a few. the “L.” Bethel New Life and the Center for Neighborhood TOD is the product of intelligent urban design and growth; Technology created Chicago’s first Transit-Oriented it is an antidote to traffic congestion, a reversal of suburban Development Plan for the Pulaski “L” Stop to demonstrate sprawl, and a tool to reverse inner city blight. what the transit-centered revitalization of that neighborhood TOD is characterized, in part, by its dense and compact could accomplish. nature. TOD includes a mix of housing, retail, and institu- Transit is valued throughout the Chicago Region. A recent tional and other land uses that are near each other so that study conducted by the real estate agency RE/MAX found people can walk, bike, or easily reach them by transit. TOD that Chicago suburbs with Metra train service saw home locates destinations within easy and affordable access at a prices rebound by 2012 at greater rates than the suburbs fraction of the cost of using an automobile. as a whole.8 The study also found that the decline in home sales for suburbs with Metra service was smaller than in the suburbs as a whole. TOD in the Region has thrived even in the housing market downturn. Suburban developers have

reported that suburban infill development near Metra TOD Value Capture. The RTA created Tools and Techniques for stations has been a successful building pattern because Facilitating Effective TOD Value Capture – A White Paper, which identifies best practices of transit agencies from around the people want to live near transit. While transit has been an country that have sought to capture enhanced land values asset, the expansion of the Chicago Region has disconnected resulting from transit service and leverage it for investment in transportation, land use and economy from one another. the transit system. Suburban sprawl has complicated the role that transit service Policies. The RTA Board of Directors adopted a Housing and plays in our daily routines. The RTA understands this Jobs Policy as an amendment to the RTA’s Strategic Plan in complexity and believes that TOD is an effective strategy September 2009, and a Transit-Oriented Development to address the growing divide in population, employment, (TOD) Policy in November 2010. These policies address improving the spatial disconnect between job centers and recreation and home. housing in the Region by advancing TOD to provide mixed-use The RTA is committed to providing a public transportation development and mixed-income housing near transit centers. The goals of the policies have been incorporated into the system that protects the environment and supports the Community Planning Program’s evaluation criteria. livability and economic vitality of the Region. The RTA has demonstrated that commitment, in part, by its extensive Streamlining the Entitlement Process for TOD. The RTA created a best practices report that outlines ways to streamline TOD initiatives throughout the Region, including: the entitlement (or approval process) for TOD projects. This The Regional TOD Working Group was formed by the RTA in document can be used by communities as a guide to explore June 2008 to provide a forum for regional government and ways to adjust and reduce the submittal and review requirements nonprofit agencies to discuss and coordinate numerous TOD for development proposals. initiatives underway in the Region. The Working Group meets quarterly, with its primary focus on TOD implementation TOD Funding Sources. The RTA provides a list of available strategies and efforts, and a secondary focus on planning efforts. funding sources to help implement TOD, the Municipal Funding Strategies and initiatives developed by the Working Group guide Opportunities for Transit-Oriented Development, which includes the RTA’s work plan related to TOD. local, regional, state, federal, and private foundation sources which is updated twice a year. Setting the Stage for Transit Guide. Local communities can be proactive in creating an environment conducive to transit TOD Parking and Access Report. The RTA created Access and through transit supportive planning and by channeling Parking Strategies for Transit-Oriented Development as a resource local financial investments into transit service. To be more for municipal officials looking for innovative strategies to competitive for increased transit service, communities are support multi-modal access to their transit station and the encouraged to plan for transit by supporting development that surrounding TOD area. While providing parking options in has sufficient densities, mix of land uses, and available land for these areas is important, this guide focuses first on assessing transit facilities. The RTA created the Setting the Stage for Transit multi-modal access strategies as a whole and placing a priority guide as a resource for municipal officials looking to make their on pedestrian, bicycle and transit access. The RTA has also communities more transit-friendly. produced an associated PowerPoint for municipal staff to utilize in explaining the principles of the Access and Parking Strategies

6 REGIONAL TOD ANALYSIS Performance Measures

Report. The PowerPoint concisely summarizes the main points Development in the Chicago transit shed (the half-mile of the report and provides talking points for the presenter. radius around all of the Region’s train stations) has not TOD: The Future of Development. The RTA created a performed as well over the last ten years as transit sheds in brochure promoting the importance of transit-oriented develop- peer regions. If the Chicago Region had robust regional ment. The brochure describes TOD’s target demographics and transit-oriented development, we would see the transit shed positive effect on housing, retail, office and restaurant markets, and developer testimonials on the increased interest in TOD. compared with the Region as a whole characterized by:

Zoning and TOD. The RTA created Zoning and Transit-Oriented Increased number of households living in transit zones; Development: A Best Practices Report outlining the most common Lower transportation costs and Vehicle Miles Traveled types of zoning ordinances and the best practices of each as (VMT); and related to TOD. This document can be used as a guide for communities to help further implement TOD by incorporating Increased employment opportunities. transit-supportive zoning regulations and standards in their transit area. The reality, however, has been very different:

RTAMS Transit-Oriented Development Map Viewer, an The Chicago transit shed lost households from 2000 to 2010; interactive online tool that maps the development of ongoing and completed RTA TOD Studies. The Chicago transit shed did indeed have lower household VMT than the regional average, but over the past decade TOD helps to maximize the use of the existing transit household VMT rose in all parts of the Region, including near system and increase ridership for trips to work. TOD should transit; and encourage growth in corridors that connect vibrant and Though all areas lost jobs in the past decade due to the interconnected centers, discourage sprawl, and reduce the nationwide economic decline, the Chicago transit shed lost jobs at a rate almost three times faster than regional losses. cost of new infrastructure. The Region’s rich TOD legacy can be the basis for future development. In order to evaluate the performance of the Metra and CTA stations in the Chicago Region and find ways to improve their performance going forward, this study analyzes these trends and others to determine how well Chicago’s TODs provide economic vitality, sustainability, and equity, as well as location efficiency. Compact neighborhoods with walkable streets, access to transit, and a wide variety of stores and services have high location efficiency. These features represent TOD best practices because they require less time, money, and greenhouse gas emissions for residents to meet their everyday travel requirements.

METRA UNION STATION ENTRANCE Photo Credit: Flickr User Mike Miley, CC license

Evaluating TOD Performance in the Chicago Regions

This report uses data from three different geographies: allows for more consistency when aggregating data with different geographical bases (e.g. TIGER 2000, TIGER 2009, Transit Zone is the half-mile buffer around each transit TIGER 2010, etc.). For the purposes of this report, the Chicago station. One half-mile (radius) is widely considered a walkable Transit Region has been defined as the six Northeastern distance to a fixed guideway (rail) transit station. The TOD Illinois counties (Cook, DuPage, Kane, Lake, McHenry, and Database allows the user to query transit zones for existing Will) that encompass the RTA service area. These six counties stations, potential stations, and both in tandem. contain all of the fixed guideway stations in the Metra and Transit Shed is a group of transit zones. It can be made up CTA system. When data is represented for comparison across of selected stations, an entire line, an entire agency, or all regions, the Chicago Region is defined by a larger region that stations in the transit region. An important feature of transit also includes DeKalb, Grundy and Kendall counties. These shed statistics is that when two transit zones overlap, the additional three counties are not included in Chicago’s transit transit shed does not double count the data. Transit shed shed for this study and are excluded from Region to transit shed data are available for both existing and potential stations comparisons. This yields a slight variation in the Chicago data and a combination of the two. For the purpose of this report, when looking at it on a regional level (Region versus transit the transit shed has been defined as 367 Metra and Chicago shed) as compared to national peers (Chicago Region and Transit Authority (CTA) stations, the number of stations that transit shed versus that of other regions). were in operation in 2010 that were also in operation in the year 2000. Comparisons of 2000 data with 2010 data in this report are based on these 367 stations. Transit Regions (hereafter referred to as regions) are comprised of a number of counties, typically those that contain the majority of the region’s transit system. Using counties

THE CHICAGO REGION TRANSIT SHED IS COMPOSED OF 367 STATIONS THAT SPAN ACROSS SIX ILLINOIS COUNTIES.

8 REGIONAL TOD ANALYSIS This report also compares the Chicago Region with the four National TOD Database and the US Census Data peer US regions with extensive transit systems—New York The Center for Transit-Oriented Development’s (CTOD) 9 City, Philadelphia, Boston, and San Francisco. CNT defines TOD Database provides data on every existing and proposed transit systems by the number of stations as follows: fixed guideway transit station area in the United States (as Extensive: 325 – 951 stations of October 2011). It has nearly 70,000 data characteristics Large: 72 – 151 stations for 4,416 existing stations and 1,583 proposed stations in Medium: 25 – 67 stations 54 metros, for the households and housing units within a Small: fewer than 25 stations walkable one half-mile and one quarter-mile radius transit Chicago and its peer regions all have more than 325 zone of each station. Data in this report from the National stations and are referred to as “extensive systems” TOD Database are derived the following US Census data throughout this report. sources: US Decennial Census 2000 Percentage Change versus Change in Percentage Points Summary File 1 In this report, change is presented in three ways: as absolute Summary File 3 change, percentage change, and change in percentage points. US Decennial Census 2010 Percentage should be thought of as the size of a slice of the Summary File 1 pie. It is appropriate to use percentage points when the data American Community Survey (ACS), 2005-09 compared between 2000 and 2010 is already a percentage. Five-Year Estimates (a proxy for 2010 data) This is the case for Housing and Transportation (H+T®) ACS is an ongoing survey that gathers detailed population and housing data every year. It replaced the long form of the Affordability Index data and for transit mode share (i.e. Census. The 5-Year Estimates are rolling averages of data percentage of population who use public transportation for collected between 2005 and 2009. ACS data is aggregated trips to work). from block groups and tracts. This data serves as a proxy for the 2010 decennial Census data until it becomes available.

Local Employment Dynamics, 2002- 2009 LED is a voluntary partnership between the Federal Census Bureau and state labor market information agencies. The employment (jobs) data comes from this source.

More information on these data sources and how they inform the National TOD database can be found at http://toddata.cnt.org.

NORTHSIDE CHICAGO NEIGHBORHOOD Photo Credit: Clint Bautz

Household Growth Not Keeping Up in Transit Zones

Household Changes

The rate of growth in the number of households was greater in the entire Chicago Region than in Chicago’s transit shed. This contrasts with our peer regions where household growth occurred disproportionately around transit stations.

Change in Number of Households by Percentage 2000-2010

20% 18% 16% 14% 12% 10%

Percentage Change 8% 6% 4% Region 2% Shed 0% Boston Chicago New York Philadelphia San Francisco

CHICAGO REGION AND CHICAGO TRANSIT SHEDS ARE DEFINED BY A LARGER SET OF COUNTIES WHEN DATA IS COMPARED WITH OTHER REGIONS. Source: National TOD Database: http://toddata.cnt.org

Urban sprawl has continued to be the dominant development Part of the lower rate of household growth can be attributed pattern in the Chicago Region, with households increasingly to the Chicago Housing Authority’s Plan for Transformation dispersed around the Region and a growing proportion of that eliminated 18,366 units in the City of Chicago. Fifteen the Region’s households living more than a half-mile from thousand and forty-nine of these eliminated housing units a transit station. Between 2000 and 2010, the number of were located within a half-mile of a CTA or Metra station. households in the Chicago Region increased 5.8 percent, More than one-third of these housing units (5,703) were while households in the transit shed increased just 2.1 occupied. Considering that the transit shed added just over percent. Though households increased in number, Chicago’s 9,000 households over the study period, this loss of nearly Transit shed lost population—an effect explained in part by 6,000 households significantly affected the housing stock shrinking average household sizes. growth rate.

A greater proportion of people in the Chicago Region are living more than a half-mile from transit stations, making urban sprawl the dominant development pattern in the Region.

10 REGIONAL TOD ANALYSIS October 1999 December 2010

Total Occupied Total Occupied Total CHA Units* CHA Units CHA Units* CHA Units CHA Residents (individuals) CHA units located within one half- 26,611 15,552 11,562 9,849 16,194 mile of a CTA or Metra station

CHA units NOT located within one 13,566 10,011 10,249 6,135 13,757 half-mile of a CTA or Metra station

GRAND TOTAL 40,177 25,563 21,811 15,984 29,951

*INCLUDES OFFLINE UNITS THAT ARE OFFLINE LONG-TERM OR SLATED FOR DEMOLITION Source: Chicago Housing Authority 2012

Downtown Chicago gained population, but on a county-wide is occurring beyond the reach of the rail transit system. basis the highest population growth rates in the Region The reality is that today our transit system can no longer occurred in the collar counties: Will, Lake, Kane, and directly serve much of its population. This challenge is McHenry. By 2012, the Chicago Region’s transit assets, addressed by RTA initiatives; their report Setting the Stage however, are concentrated elsewhere: 306 of 384 (80 percent) for Transit encourages the development of transit supportive of the Region’s CTA and Metra train stations are located in communities that make strategic land use investments and Cook County. The Region’s strongest population growth set planning goals that connect people with transit.

CABRINI GREEN, 2008 Photo Credit: Flickr User TheeErin, CC License

©2013 CENTER FOR NEIGHBORHOOD TECHNOLOGY 11 POPULATION GROWTH OUTSIDE OF COOK COUNTY While Chicago’s Loop—a portion of Cook County—saw significant growth in population, Cook County as a whole saw a loss of 3.4%. With much of the population and household growth happening in counties that hold only 20% of the Region’s rail stations, expanded TOD in these collar counties offers opportunities to increase transit connectivity to the rest of the Region.

Average household size (average population per household) developments have featured small one- and two-bedroom between 2000 and 2010 decreased throughout the Chicago condos marketed to empty nesters and young professionals. Region by about two percent while average household size in Going forward, it is important to ensure the Chicago Region the transit shed decreased over five percent. This indicates is enabling a wide range of household types to access the that the households near transit are increasingly single benefits of living near transit for reasons of both economic individuals, couples without children living at home, and equity and Regional competitiveness. other small family types. This may be because many TOD

12 REGIONAL TOD ANALYSIS Change in Average Household Size 2000-2010

0.04 0.02 0.00 -0.02 -0.04 -0.06 -0.08 -0.10 -0.12 Region Shed -0.14 Channge in Number of of People in Number HH per Channge Boston Chicago New York Philadelphia San Francisco

CHICAGO REGION AND CHICAGO TRANSIT SHEDS ARE DEFINED BY A LARGER SET OF COUNTIES WHEN DATA IS COMPARED WITH OTHER REGIONS. Source: National TOD Database: http://toddata.cnt.org

Percent Change in Family and Non-Family Households 2000-2010

10.0% 8.0% 6.0% 4.0% 2.0% 0.0% Percent Change -2.0% -4.0% Region Shed -6.0% % Change of Family Household % Change Non-Family Household

CHICAGO REGION AND CHICAGO TRANSIT SHEDS ARE DEFINED BY A LARGER SET OF COUNTIES WHEN DATA IS COMPARED WITH OTHER REGIONS. Source: National TOD Database: http://toddata.cnt.org

Chicago’s decrease in average household size far surpassed people to live alone at rates that were not possible in earlier that of all of its peer regions. Throughout the nation, there times. Those small households are choosing to live near has been a significant rise in single-person households, transit. It is important to the Region’s future that families of particularly in transit zones, which lowers the average all sizes be able to access the benefits of living near transit, household size. In 1950, nine percent of Americans lived so future TOD planning and incentives should continue to alone; today that figure is 14 percent. Changing social promote development of larger homes and affordable housing structures and financial prosperity have made it possible for to balance out the trends of the past decade.10

Over the decade, Chicago’s Regional annual housing costs the location efficiency of those places by the housing market, increased by $3,579 (28 percent) from $12,741 to $16,338 per and it can result in increased property tax revenue. However, year. In the transit shed, housing costs increased by $2,751 this needs to be balanced with the inclusion of affordable (19 percent) from $14,744 to $17,495.11 Communities that housing around transit stations to ensure that the Region’s saw additional TOD growth typically added units at the high low- and moderate-income households can benefit from the end of the market, such as luxury condominiums marketed to Region’s investment in public transit, as well. affluent empty nesters. Transit access is a valuable amenity. It makes the land However, even as housing costs rose, incomes also rose. The surrounding transit stations more valuable than land outside cost of housing as a percentage of household income housing of the transit shed. Affordable housing is threatened by decreased by 1.1 percentage points in the Region and rose replacement by more expensive housing options, displacing by just 1.4 percentage points (based on national data, which those who cannot afford to pay premium rates to live is defined by a larger geography) in the transit shed. In three near transit and the amenities that transit zones offer. of the five extensive systems (Boston, Chicago, and New Preservation of affordable housing contributes to job access York), housing costs in the transit shed increased as a share of for many households. The increase in the cost for housing median incomes at rates significantly higher than that of their in the transit shed constitutes an urgent call for the Chicago respective regions. An increase in the cost of housing can Region to focus affordable housing development around benefit communities as it represents the capture of value of transit stations.

Change in Percentage Points for Housing Costs as a Percentage of Income 2000-2010 2.5% 2.0% 1.5% 1.0% 0.5% 0.0% Percentage Change -0.5% -1.0% Region -1.5% Shed -2.0% Boston Chicago New York Philadelphia San Francisco

CHICAGO REGION AND CHICAGO TRANSIT SHEDS ARE DEFINED BY A LARGER SET OF COUNTIES WHEN DATA IS COMPARED WITH OTHER REGIONS. Source: National TOD Database: http://toddata.cnt.org

14 REGIONAL TOD ANALYSIS Benefits of Transit Are Not Equitably Distributed

Optimally, the transit shed population should be representative of the Region, including young people, seniors, families, singles, and households of all backgrounds. The data shows, however, that over the last decade Chicago’s transit shed has become less diverse. Income

The average household income in transit zones in the project added units near transit over the last decade at price Chicago Region increased by 27 percent or $12,348 over the points from $250,000 to $500,000 and up, often marketed past decade. The Chicago Region as a whole experienced a towards young professionals and wealthy empty nesters smaller 18 percent increase in median income of $9,312. The looking to downsize, but continue to build equity through divergence in median income between the transit shed and real estate investment. the Region may indicate that the transit shed is gentrifying, potentially displacing low- and moderate-income households.

Transit should be an economic benefit accessible to all The transit shed may be of the Region’s residents, but low- and moderate-income gentrifying, potentially households, already with the fewest options, need transit displacing low- and moderate- access the most. Yet over the past decade, development around transit stations has skewed toward middle and upper- income households. income households. Suburban towns interviewed for this

Median Incomes for 2000 vs. 2010 with Constant 2010 Dollars

2000 2010 Year 2000 Median Income Adjusted for 2010 Inflation

$70,000 $60,000 $50,000 $40,000 $30,000 2010 2010

Median Income $20,000 2000 2000 ear 2000 ear 2000 Income Median Adjusted for 2010 Inflation 2010 for Adjusted $10,000 Y Adjusted for 2010 Inflation 2010 for Adjusted Year 2000 Median Income Income Median 2000 Year $0 Chicago Region Transit Shed data source : Census 2000 SF3 / ACS 2009

CHICAGO REGION AND CHICAGO TRANSIT SHEDS ARE DEFINED BY A LARGER SET OF COUNTIES WHEN DATA IS COMPARED WITH OTHER REGIONS. Source: National TOD Database: http://toddata.cnt.org

In three of four of Chicago’s peer regions, median household disparity between the increase of Chicago’s Regional median incomes within a half-mile of train stations increased more income and that of its transit shed was larger than any of its than the regional median. The trend of increased household peers. Chicago’s transit shed median income grew nearly income near transit is not just an issue in Chicago, but the nine percent more than the Region’s.

Change in Median Incomes 2000-2010

$18,000 $16,000 $14,000 $12,000 Region $10,000 Shed $8,000 $6,000

Change in Median Income $4,000 $2,000 $0 Boston Chicago New York Philadelphia San Francisco

CHICAGO REGION AND CHICAGO TRANSIT SHEDS ARE DEFINED BY A LARGER SET OF COUNTIES WHEN DATA IS COMPARED WITH OTHER REGIONS. Source: National TOD Database: http://toddata.cnt.org

16 REGIONAL TOD ANALYSIS Families

The percentage of American households with children under decreased by nearly 22,000 (five percent), while the Region 18 living at home hit a half-century low of 46 percent in 2008. saw a small increase of 0.2 percent in the same time period. During the study period, the Chicago Region lost 1.5 percent This means that family households likely saw an increase in of its households with children; by 2010, only 33 percent transportation costs. Family households with children are of households had children under 18. The transit shed lost not thought by developers to be the optimal TOD residents; 2.3 percent of its households with children during this same singles, millennials, and seniors are often thought to be the period; by 2010, 26 percent of its households were homes more ideal occupants for transit-adjacent living. Based on to children. The greatest loss came in transit shed rental our interviews, we found that this is because developers have households with children, which decreased by 2.8 percent. found that it is expensive to build 2-3 bedroom multi-family This loss is more than double the 1.3 percent regional loss housing units large enough to house these families. Family rate for households with children. For owner occupied households are among the primary beneficiaries of public households with children, the Region saw a loss of 0.3 percent transit when it is accessible, because they can use it for trips to but the transit shed gained 0.5 percent. work, school, and/or other local destinations at a fraction of the cost of automobile transport. Family access to affordable Another troubling trend is that families were represented housing needs to become a regional priority. in fewer TOD households in 2010 than in 2000. Over the last decade within the transit shed, family households

Change in Percentage Points for Family Household with Children by Tenure 1.00 0.50 0.00 -0.50 -1.00 -1.50

Percentage Points Percentage -2.00 -2.50 -3.00 Change in % Points for Household Owners with Change in % Points for Household Renters with Children Children

datasource : Census 2000 SF3 / ACS 2009 Region Shed

CHICAGO REGION AND CHICAGO TRANSIT SHEDS ARE DEFINED BY A LARGER SET OF COUNTIES WHEN DATA IS COMPARED WITH OTHER REGIONS. Source: National TOD Database: http://toddata.cnt.org

Between 2000 and 2010 there was a decrease of 15,095 rental households (–3.4 percent) within the transit shed compared with an increase of 28,768 (2.8 percent) in the Region as a whole. Towns experiencing TOD development have often been more supportive of new condominiums and townhomes than new rental apartments, even when the new units rent at market rate or higher. This, combined with conversion of existing apartments to condominiums, may have led to a decrease in the total number of rental households.

The data shows a trend of fewer rental units near train stations which may mean a restriction of opportunities for less-affluent families to locate in TODs. Despite the condo boom in the 2000s, which tapered off by 2010, we have seen a resurgence of rental units in TOD since then. Rental units have been more successful than condo units in communities including Berwyn, Orland Park, and Tinley Park.

Since existing condos are not succeeding in the current METRA DOWNTOWN Photo Credit: Flickr User Anarchosyn, CC License housing market, communities in the Region have become more open to approving the development of buildings planned for rental living.

Change in Renter and Owner Occupied Units 2000-2010

140,000 120,000 100,000 80,000 60,000 40,000 20,000 Number of Units 0 -20,000 -40,000 Owner Occupied Units Renter Occupied Units Region Shed data source : Census SF1 2000 & 2010

CHICAGO REGION AND CHICAGO TRANSIT SHEDS ARE DEFINED BY A LARGER SET OF COUNTIES WHEN DATA IS COMPARED WITH OTHER REGIONS. Source: National TOD Database: http://toddata.cnt.org

18 REGIONAL TOD ANALYSIS Changes in Transportation Patterns

Transit Ridership for Trips to Work Not Keeping Up

Ridership for trips to work in the Region’s transit shed rose region-wide. This indicates that Chicago’s transit ridership only slightly between 2000 and 2010, rather than becoming for trips to work could be growing much faster than it has, an ever more robust mobility option for the Region’s both among TOD households and throughout the Region. residents. Over the past 10 years, there has been a 0.30 Chicago is the only Region among its peers that saw a loss in percentage point increase in transit ridership for trips to transit ridership for trips to work on a Regional level. This work among residents within a half-mile of a train station, suggests an opportunity to promote transit to current TOD compared to a Chicago Regional decrease in transit ridership residents, and implement policies and programs to ensure for trips to work of 0.03 percentage points. that residents that move to the Region’s TODs in the coming decade make full use of the Chicago Region’s substantial In Chicago’s peer regions, transit ridership for trips to transit investments. work increased an average of 0.60 percentage points within the Transit shed and, on average, 0.62 percentage points

Chicago is the only Region that saw a loss in transit ridership for trips to work.

Change in Percentage Points for Transit Ridership Trips to Work 2000-2010 2.5 Region Shed 2.0

1.5

1.0

0.5

0.0 Change in Percentage Points -0.5 Boston Chicago New York Philadelphia San Francisco -1.0

CHICAGO REGION AND CHICAGO TRANSIT SHEDS ARE DEFINED BY A LARGER SET OF COUNTIES WHEN DATA IS COMPARED WITH OTHER REGIONS. Source: National TOD Database: http://toddata.cnt.org

16% 14% 12% 10% 8% 6% 4% 2% 0% Percent Change Miles Traveled Change in Vehicle Percent Boston Chicago New York Philadelphia San Francisco Region Shed

CHICAGO REGION AND CHICAGO TRANSIT SHEDS ARE DEFINED BY A LARGER SET OF COUNTIES WHEN DATA IS COMPARED WITH OTHER REGIONS. VEHICLE MILES TRAVELLED (VMT) IS MODELED BASED ON A REGIONAL TYPICAL HOUSEHOLD AND IS A PRODUCT OF THE H+T INDEX, A PRODUCT OF THE CENTER FOR NEIGHBORHOOD TECHNOLOGY. Source: National TOD Database: http://toddata.cnt.org

VMT is Lower, but Increasing Faster in the Transit Shed as Compared to the Region

In the Chicago transit shed, average household annual that over the past decade the population with the greatest vehicle miles travelled (VMT) is lower than average, but access to transit still drive less per year than other Regional increased 14.6 percent, compared to 13.3 percent for the residents, but driving has increased at a faster rate among this Region as a whole. People who live within a half-mile of group. This was the case in all four of the other regions with a rail station increased their annual driving mileage by a extensive systems as well. larger proportion of the overall Region. We do not know In recent years the nation has seen resurgence in transit with certainty why this trend is occurring, but we do know ridership for trips to work. After decades of decline, public that the transit shed of Chicago, as well as that of the other transportation ridership for trips to work grew 36 percent extensive Regions, have higher median household incomes. from 1995 through 2008, almost three times the growth This could mean higher car ownership and miles travelled, rate of the US population (14 percent) and substantially but further research is needed to fully understand the trend. more than the growth for VMT on our nation’s streets and This is troubling, as proximity to transit, as we have seen, is highways (21 percent) over the same period.12 a valuable amenity. People who live nearby should be taking advantage of it more and driving less. These data show

20 REGIONAL TOD ANALYSIS Change in Annual Transportation Costs as a Percentage of Median Income 2000-2010 25

5 Percent of National Median Income 0 2000 2010

datasource : Housing + Transportation Affordability Index Model. Based on Regional Typical Household Region Shed

CHANGE IN ANNUAL TRANSPORTATION COSTS AS A PERCENTAGE OF MEDIAN INCOME 2000-2010. Source: Housing + Transportation Affordability Index Model. Based on Regional Typical Household

Transportation Costs Are Not Increasing as Quickly Within the Transit Shed

Transportation costs in the transit shed were significantly the option to use public transit, walk, and bicycle, and they lower than transportation costs in the Region as a whole. typically have access to destinations that are closer together. Within the transit shed, they also increased at a slower rate. Altogether, this results in the need for fewer cars, fewer miles of driving, and less impact on household budgets Between 2000 and 2010, average annual household transpor- from increases in gas prices and other transportation tation costs for residents of the Chicago Region increased by costs. Between 2000 and 2010, the cost of transportation $3,282 (38 percent) from $8,730 per year to $12,012 per year. as a proportion of regional household income increased In the transit shed, transportation costs increased $2,324 (31 by 2.6 percentage points in the Region as compared to 1.3 percent) from $7,416 per year to $9,740 per year.13 percentage points in the transit shed. This speaks to the Both the Chicago Region and the Chicago transit shed significant impact on transportation costs of transit ridership saw transportation costs rise as a percentage of incomes. for trips to work. While VMT rose faster in the transit shed, Transportation costs in the transit shed continued to the transportation costs rose more slowly in the shed as represent a smaller percentage of median incomes and rose compared to the Region. This suggests that even though the at a slower rate, showing the transportation cost savings for VMT rose in the shed more rapidly than in the Region, the residents of the transit shed. overall cost of transportation rose more slowly within the transit shed, likely due to transit ridership for trips to work, In 2010, residents living in a transit zone spent $2,272 less which is a more affordable transportation option. In other on household transportation expenses as compared to the regions, the same was true: transportation costs increased at Region. Households living within the transit shed typically a slower rate in the transit shed than they did in the transit enjoy lower transportation costs because residents have Region. This is what TOD strives to achieve.

Combining the costs of housing and transportation and understanding the proportion of incomes required to pay for them reveals the true costs to households of living in a particular place. In the Chicago Region, households living in transit zones saw the combined cost of housing and transportation increase more as a proportion of household income than in the whole Region (three percentage points versus one percentage point, respectively). Despite its higher rate of increase over the decade, these major costs of living remained significantly lower in the transit shed as compared to the Region as a whole. This is yet another demonstration of the cost savings and benefits of living within a transit shed.

For three of Chicago’s four peer regions, housing and transportation costs also increased more rapidly in the transit shed than in the Region. In three of the five extensive systems (Boston, Chicago, and New York), the housing costs in the transit shed increased as a share of median incomes at rates significantly greater than that of the Region. Chicago’s

Change in Combined Housing and Transportation Costs as a Percentage of Median Income 2000-2010 58 56 54 52 50 48 46 44 Percent of National Median Income 42 2000 2010

datasource : Housing + Transportation Affordability Index Model Region Shed

CHICAGO REGION AND CHICAGO TRANSIT SHEDS ARE DEFINED BY A LARGER SET OF COUNTIES WHEN DATA IS COMPARED WITH OTHER REGIONS. Source: National TOD Database: http://toddata.cnt.org

22 REGIONAL TOD ANALYSIS Chicago saw the largest growth BNSF AMTRAK YARDS SOUTHSIDE CHICAGO Photo Credit: Flickr User Mike Miley, CC License in the H+T cost disparity between its transit shed and Region

10-year change in H+T costs as a percentage of income was unique among its peers. Chicago saw the largest growth in the H+T cost disparity between its transit shed and Region: the Chicago transit shed saw an increase of 2.8 percentage points while the Region saw an increase of 1.6 percentage points. Chicagoland’s transit shed experienced a trend of a combined housing and transportation costs rising faster than the Region over the past decade. If this trend continues it means moderate- and lower-income households (i.e. young singles, families, renters, affordable housing beneficiaries) will increasingly have difficulty living in the transit shed. Policies should be enacted to ensure that affordability issues do not financially exclude those who want to live near transit and contribute to ridership for trips to work. Overall the data shows that transit creates value for communities by making them desirable and competitive places to own a home, increasing property values and benefitting the larger community through tax revenues near transit.

Percentage Point Change for Housing and Transportation Costs as a Percentage of Income 2000-2010 4.5 Region Shed 4.0 3.5 3.0 2.5 2.0 1.5 1.0 Change in Percentage Points 0.5 0.0 Boston Chicago New York Philadelphia San Francisco

CHICAGO REGION AND CHICAGO TRANSIT SHEDS ARE DEFINED BY A LARGER SET OF COUNTIES WHEN DATA IS COMPARED WITH OTHER REGIONS. Source: National TOD Database: http://toddata.cnt.org

The Center for Neighborhood Technology’s Housing and Transportation (H+T®) Affordability Index provides a more comprehensive way of thinking about the cost of housing and transportation true affordability. The Index is the only tool of its kind that examines transportation costs at a neighborhood level. It allows users to view housing and transportation data as maps, charts, and statistics for nearly 900 metropolitan and micropolitan areas—covering 89 percent of the US population. The H+T Index shows that transportation costs vary between and within regions, depending on neighborhood characteristics. People who live in location-efficient neighborhoods—compact, mixed-use areas with convenient access to jobs, services, transit, and amenities—tend to have lower transportation costs. People who live in location-inefficient places that require automobiles for most trips are more likely to have high transportation costs. The traditional measure of affordability recommends that housing cost no more than 30 percent of income. Under this view, 76 percent of US neighborhoods are considered “affordable” to the national typical household. That benchmark, however, ignores transportation costs, which are typically a household’s second- largest expenditure. The H+T Index offers an expanded view of affordability, one that combines housing and transportation costs and sets the benchmark at no more than 45 percent of household income. Under this view, the number of affordable neighborhoods drops to 28 percent, resulting in a net loss of 86,000 neighborhoods that Americans can truly afford. The H+T Index data have implications for consumers, planners, and policy makers. The Applications page of the website has more information about how the data can and have been used across the country. Throughout the evolution of the H+T Index model, the key finding remains the same: household transportation costs are highly correlated with urban environment characteristics when controlling for household characteristics. For more information or to use the H+T Index please visit our website http://htaindex.cnt.org/. Using a National Typical Household allows results to be directly compared with other metropolitan regions by holding income, average household size, and commuters constant.

24 REGIONAL TOD ANALYSIS Based on the 2005–2009 H+T Model, the characteristics of the National Typical Household in this report are: • Income = $51,425 • Average household size = 2.6 • Commuters = 1.15 To put this in a local perspective, the Chicago-Naperville-Joliet metropolitan area Regional Typical Household characteristics are: • Income = $60,289 • Average household size = 2.73 • Commuter = 1.23

Using H+T Affordability Index Data to Compare Datasets Over Time

The recent release of the 2009 H+T Index (using 2005-2009 American Community Survey five-year estimates) represents the first time that the full Index has been expanded and updated to cover a new time period. With this release, there has been great interest in comparing the two Index datasets to assess how housing and transportation costs have changed over the time period. However, due to differences in the data reported in the 2000 Census and the 2005- 2009 American Community Survey (ACS), the 2000 H+T Index and the 2009 H+T Index are not immediately comparable. To enable comparisons to be made between the 2000 H+T Index and the 2009 H+T Index, this dataset compiles Index values from the two time periods in a comparable format. Because the Index is constructed for a fixed, typical household, it is important that the characteristics defining this household are derived from the same geographic area for the two time periods. Because statistical areas are constantly changing and being redefined, regional statistics do not provide a consistent source on which to fix household characteristics. Therefore, for the H+T Index comparison dataset, national values (national median income, national average household size, and national average commuters per household) are used to define the typical household for each time period.

Transit Shed Loses Jobs Faster Than Region

The Chicago Region’s job market saw a loss rate (-1.3 their impact on transit is much greater. Almost 60 percent of percent) nearly three times higher in the transit shed than all transit trips are for work.14 In September 2012, 12 million in the Region as a whole (-0.5 percent), an alarming trend. of the CTA’s 20 million boardings were work-related. Rush Ideally, the development pattern in transit zones should hour travel behaviors shape peak travel demand. Historically, result in an increase in the number of mixed-use spaces and Chicago had one major job center, Chicago’s Loop; travelers employment opportunities. would leave from their low-density residential communities and travel to the highly dense downtown for work. This The Chicago Region kept pace with other extensive systems development pattern has diminished with the development in terms of transit shed job capture rate. In 2009, the Chicago of multiple, if smaller, job centers outside of the downtown, transit shed was home to 33 percent of the Region’s jobs however in many cases new satellite job centers have been compared with Philadelphia’s transit shed that held 32 developed in locations underserved by transit, which is percent of its jobs and New York’s transit shed that held 45 restricting employment to those who own cars and are willing percent of its Region’s jobs. Understanding the connection to drive to work. between transit and jobs is essential to maximize the economic potential of the transit shed. While work-related Job sprawl exacerbates household unaffordability. Low- and trips make up only 18 percent of all trip types nationwide, moderate-income households15 often move to areas far

Percentage Change in Number of Jobs 2002-2009 0.0% -0.2% -0.4% -0.6% -0.8% -1.0% Percentage Change -1.2% -1.4% Chicago Region Transit Shed

CHICAGO REGION AND CHICAGO TRANSIT SHED S ARE DEFINED BY A LARGER SET OF COUNTIES WHEN DATA IS COMPARED WITH PEER REGIONS. Source: National TOD Database: http://toddata.cnt.org

26 REGIONAL TOD ANALYSIS removed from jobs and public transportation in search jobs have scattered throughout regions, decentralizing from of lower-cost housing. What results is an increase in central business districts and succumbing to sprawl. The dependency on car ownership, longer driving distances proportion of jobs located at the core of metropolitan areas to work, and higher transportation costs. Lower income has decreased as these jobs have moved out to employment households are better served by homes in transit zones and by centers along highways in suburban locations.17 Nationally, employment centers well connected by public transportation. most of the jobs that were added to the transit shed were due to transit zone transit expansion, rather than the creation of One of the key trends in job centers in recent decades is new jobs near pre-existing train stations. that they are often located in auto-oriented, suburban communities that are on the edge or just outside of The Brookings report also found that when the metropolitan metropolitan regions. According to a Brookings Institution area has high rates of job sprawl, low- and moderate-income report, between 1998 and 2006 jobs shifted away from major populations are more suburbanized; in other words, poor metropolitan cores and out to the suburbs.16 The same has people follow jobs. This report also found that employment been true of population: the largest growth (outside of the decentralization is highest for manufacturing (77.4 percent) central business district) has been captured in collar counties and lowest for skill-intensive service industries (66.9 percent). of large metropolitan regions. Over the last half-century,

LEVELS OF SUBURBANIZATION BY POVERTY STATUS AND JOB SPRAWL INDEX, 2006-2007. Source: Raphael, Steven, and Michael A. Stoll. Job Sprawl and the Suburbanization of Poverty (Washington D.C.: Brookings, 2010).

©2013 CENTER FOR NEIGHBORHOOD TECHNOLOGY 27 Employment Sprawl Yields the Sprawl of Lower Income Residents Away from Metropolitan Cores Within metropolitan regions, 72 percent of all jobs are more Successful TODs are typically characterized by strong local than five miles away from the central business district. economies, providing retail services and jobs for residents, Metropolitan regions with high rates of job sprawl see higher as well as by the economic diversity of transit zone residents. rates of suburbanization in general.18 Only 20 percent of For city-dwellers whose incomes limit their housing and the Chicago Region’s transit shed extends beyond Cook transportation options, sprawl poses a complex barrier to County, which is home to Chicago’s central business district. finding and maintaining employment. These counties beyond Cook are experiencing the greatest The data above summarizes the general trends of the transit population growth and job creation. This disconnect shed and the region for Chicago and its peers. The following creates a challenge for municipalities that want to provide section of this report uses a typology to break up the transit employment for people who may not be able to afford the zones for a closer look at some key trends at a station level. transportation costs associated with suburban employment. The typology drives some further analysis and case studies on TOD in the Region.

Growing municipalities outside of the Cook County transit shed struggle to provide employment for residents unable to afford the transportation costs associated with suburban employment.

SUBURBAN HOUSING Photo Credit: Flickr User nrtphotos, CC License

28 REGIONAL TOD ANALYSIS Comparing Transit Zones in Chicago

An analysis of population change from the US Census This extraordinary downtown growth pattern shows up Bureau found that the Chicago Region had the strongest when looking at the Chicago Region’s transit zones, as well. population growth within two miles of its downtown City Transit zones in downtown Chicago were not the only ones Hall of any major metro area in the country. Chicago’s down- that saw significant household growth. Household growth of town core saw a population growth of 48,288 (36.2 percent) 10 percent or more occurred in some suburban transit zones new residents in the past decade. Comparatively, downtown along every CTA and Metra line in the Region. New York—the area with the next largest growth—added 37,422 (9.3 percent) people in that time.19

ESRI WEST COOK STATION AREA MARKET SEGMENTS

©2013 CENTER FOR NEIGHBORHOOD TECHNOLOGY 29 Chicago Region Place Type Transit Zones by Type (Employment as share of employees + residents) Residential Mixed Use Employment Total The neighborhoods around transit in the Chicago Region vary a great deal by design, history, and use, and their 16 20 8 44 performance as TODs varies as well. To examine this variation, the performance of TODs within the Chicago Region is measured based on the transit zone, or the half- 19 10 2 31 mile radius around each transit station. The 367 transit zones in the Chicago Region that existed in 2000 (and thus 60 28 1 89 can show trends to 2010) are divided into 15 types based on their land-use mix and performance in terms of residential Household VMT vehicle miles traveled (VMT).20 This typology provides a 31 10 2 43 framework to understand the changes that occurred in each neighborhood around transit in the Chicago Region between 97 26 36 159 2000 and 2010. HighestLowest Total Tables 1 and 2 show how the Chicago Region’s transit zones 223 94 49 366 shifted within the typology from 2000 to 2010. Most transit Table 1 Chicago Region Transit Zones by Type 2000 zones are primarily residential places and became slightly more residential from 2000 to 2010. Household VMT is lower in transit zones than other areas, but grew in transit Place Type (Employment as share of employees + residents) zones throughout the Region, shifting many transit zones from being lower VMT types to higher VMT types, although Residential Mixed Use Employment Total the lowest VMT places continue to be among the densest. 35 34 5 74 Transit zones in the Chicago Region show some distinct geographical patterns by type, with lower VMT places largely situated near the city center and higher VMT places in the 42 29 2 73 less dense suburban and exurban areas. On average, the Low VMT transit zones are one to four miles from Chicago’s 58 13 2 73 City Hall, while the High VMT transit zones are 27–31 miles away. The Employment transit zones are clustered in downtown Chicago and a few outlying places, while the Household VMT 67 4 2 73 Residential transit zones are more suburban in nature. 28 15 30 73 Lowest HighestLowest

Total 230 95 41 366 Table 2 Chicago Region Transit Zones by Type 2010

30 REGIONAL TOD ANALYSIS TRANSIT ZONE TYPOLOGY FOR THE CHICAGO REGION Based on year 2000 to year 2010 changes in VMT and employees as a share of total residential population

As a performance metric, household growth shows positive Low-Moderate Mixed Use and Employment places—a performance, in that it means new households are choosing troubling trend for households seeking more location to live in transit zones and that new and existing housing efficient housing opportunities, but the overall trend was that units are accommodating growth. The transit zones that saw residential density showed stronger increases than household the highest percentage of household growth in the Chicago growth in many parts of the Region. Region were the Low VMT, High Employment places. This Household VMT is a performance metric, in that lower VMT is supported by the downtown growth trends in the map of indicates that a place is location efficient—that residents household growth patterns. Table 3 shows that these transit and workers can access jobs, school, shopping, and other zones had 62 percent household growth or an average of activities through walking, biking, or transit or without 2,700 additional households between 2000 and 2010. High driving long distances. Household VMT is lower in transit VMT places also saw household gains, but at a much smaller zones than it is in other parts of the Region, but VMT grew scale, as these neighborhoods tend to be exurban transit in most transit zones in the Chicago Region between 2000 stations with low residential density. and 2010, and growth was proportionally greatest in the Low In line with the household growth trends, residential density VMT transit zones (Table 3). Even with increased household (in terms of housing units per residential acre) increased most driving, however, the Low VMT transit zones saw very in the lowest VMT transit zones in the Chicago Region from limited transportation cost increases, as these households 2000 to 2010 (Table 4). The largest increase in density was own few cars, use less gasoline, and therefore are much less in the Low VMT, High Employment places that saw a near impacted by the fuel price increases that occurred over the doubling of density from 46 to 90 units per residential acre. past decade (Table 6). Two transit zone types lost density in the past decade,—the

CTA ANDERSONVILLE RED LINE STATION Photo Credit: Flickr User Andrew Ciscel, CC License

32 REGIONAL TOD ANALYSIS Place Type Place Type (Employment as share of employees + residents) (Employment as share of employees + residents) Residential Mixed Use Employment Residential Mixed Use Employment 5% (41) 3% (23) 7% (26) 2% 1% 22%

-4% (-76) 1% (18) -16% (-107) 4% 5% 18%

-6% (-187) 7% (234) 22% (231) 5% 14% 51% Household VMT -5% (-259) -2% (-87) -19% (-585) Household VMT 4% -9% -22%

2% (204) 25% (1,640) 62% (2,760) 10% 28% 107% Lowest HighestLowest Lowest HighestLowest

Table 3 Household Change, 2000–2010, by Transit Zone Type, Table 4 Percentage Residential Density Change, 2000–2010, by Chicago Region Transit Zone Type, Chicago Region (Units per Residential Acre)

Place Type Place Type (Employment as share of employees + residents) (Employment as share of employees + residents) Residential Mixed Use Employment Residential Mixed Use Employment 7% 7% 0% $4,038 $3,984 $3,933

13% 17% 13% $3,706 $3,752 $4,027

13% 19% 27% $3,061 $3,237 $3,171 Household VMT 17% 24% 24% Household VMT $2,486 $2,296 $2,318

17% 27% 32% $1,436 $1,132 $234 Lowest HighestLowest Lowest HighestLowest

Table 5 Percent Household VMT Change 2000–2010 by Transit Zone Table 6 Transportation Cost Change 2000–2010 by Transit Zone Type, Chicago Region Type, Chicago Region

©2013 CENTER FOR NEIGHBORHOOD TECHNOLOGY 33 Place Type Place Type (Employment as share of employees + residents) (Employment as share of employees + residents) Residential Mixed Use Employment Residential Mixed Use Employment -1% 0% -1% 1% 0% -1%

1% 0% -8% 0% 0% -1%

2% 0% -1% 1% 1% 1% Household VMT 5% 3% 3% Household VMT 0% -1% 9%

4% 5% -2% 1% -2% -3% Lowest HighestLowest Lowest HighestLowest

Table 7 Change in Housing and Transportation Costs as a Share of Table 8 Transit/Walk/Bike Commute Change, 2000–2010, by Transit Income, 2000–2010, by Transit Zone Type Chicago, Region Zone Type, Chicago Region

18% 19% 22% -13% -10% -29%

17% 25% 8% -10% 16% 8%

Household VMT 25% 19% 89% Household VMT -17% -5% -2%

41% 49% 28% 4% 1% 4% Lowest HighestLowest HighestLowest

Table 9 Percentage Household Median Income Change, 2000–2010, Table 10 Employment Change, 2000-2010, by Transit Zone type, by Transit Zone type, Chicago Region Chicago Region

34 REGIONAL TOD ANALYSIS Housing and transportation costs as a share of income Further analysis could build on this report to explore are an important metric of the affordability of a place to changes in the ways that people arrive to transit stations residents. The combined cost of housing and transportation (walking, biking, driving, other transit modes, etc.). represent the true cost of living in one neighborhood over Median household income grew in every transit zone type another, as this metric depends not just on housing prices, from 2000 to 2010. While transit zones of the Low-Moderate but the number of cars an average household will need VMT, High Employment type saw an 89 percent average to own and how much driving will be needed to live in increase in income, there are only two transit zones of this that place. Housing and transportation costs as a share of type in the Region. More significant was the income increase income changed inconsistently across transit zone types in the Low VMT transit zones. These three types saw in the Chicago Region between 2000 and 2010. In many household income increases from 28 percent to 49 percent. places, housing and transportation costs both increased Job growth in the Chicago Region transit zones from 2000 significantly, but incomes increased significantly as to 2010 was mixed (Table 10). As with household growth, the well. In other areas, such as the Low VMT, residential lowest VMT places performed well with one to four percent neighborhoods, income increases were not large enough growth across all three Low VMT types. Most impactful was to overcome increased housing and transportation costs, the growth in the Low VMT, High Employment transit zone resulting in an overall loss of affordability from 2000 to 2010. type where employment is densely located. The Moderate The share of commuters that walked, bicycled, or took VMT, Mixed Use and Employment places also performed transit to work did not significantly change in most transit well, with 16 percent and eight percent increases in jobs Table 8 zone types from 2000 to 2010 ( ). These alternative respectively. However, these areas are less dense, so the total commute modes continued to be far more prevalent in Low number of jobs added in these neighborhoods is limited. VMT communities than in higher VMT communities.

CTA ROSCO AVE. BROWN LINE STATION Photo Credit: Flickr User Andrew Ciscel, CC License

One of the advantages of the TOD typology is that it allows begin to see the demographics and indicators of a “typical” the development of average metrics by transit zone type. By neighborhood of that type. Table 11 provides several key averaging values across all transit zones in a type, one can metrics for the Chicago Region transit zones in this study.

2010 Average Metrics by Transit Zone Type Chicago Region Residential Places Mixed-Use Places Employment Places Low- High- Low- High- Low- High- Low Mod High Low Mod High Low Mod High Mod Mod Mod Mod Mod Mod VMT VMT VMT VMT VMT VMT VMT VMT VMT VMT VMT VMT VMT VMT VMT

Households 10,522 4,898 2,989 1,674 909 8,113 4,751 3,365 1,559 902 7,240 2,444 1,299 542 380

VMT per 10,647 12,301 14,329 16,722 19,501 9,900 12,038 14,519 16,798 19,507 8,464 11,680 14,260 17,74 4 19,979 Household

Household Transportation $7,894 $9,533 $11,051 $12,709 $13,905 $7,0 08 $9,272 $11,257 $12,783 $13,881 $5,693 $9,079 $10,972 $13,466 $14,071 Costs

H+T as Percent of 49% 45% 49% 58% 69% 55% 47% 56% 58% 69% 53% 34% 47% 86% 64% Income

Household $62,867 $39,822 $50,045 $67,252 $87,433 $80,894 $49,714 $63,263 $67,777 $88,787 $84,602 $33,173 $50,266 $127,914 $77,236 Income

Jobs 5,735 2,192 1,390 918 595 12,299 5,531 9,442 3,475 2,016 222,611 23,267 10,337 6,279 2,640

Residential Density (Units/ 30.2 16.0 9.7 5.2 3.5 34.9 19.9 10.6 5.3 3.6 89.8 16.1 12.0 2.6 5.8 Res. Acre)

Transit/ Walk/Bike 47% 36% 26% 19% 13% 47% 34% 31% 16% 12% 59% 50% 19% 21% 11% Commuters

Table 11 2010 Average Metrics by Transit Zone Type Chicago Region

36 REGIONAL TOD ANALYSIS TOD Typology Methodology

Defining Place Types Ranking Performance

Land use is an important neighborhood characteristic, Annual residential VMT is used as the key indicator for the as different policies and planning solutions are applicable types of transit zones, as lower household VMT is strongly to places that are primarily job centers as compared to correlated with the other benefits of successful TOD, residential neighborhoods. The Chicago Region’s transit including lower household transportation costs, lower zones are divided into three land use categories based on pollution, increased transit ridership for trips to work, and the share that employment makes up of the total of job and increased walking and biking. VMT values from CNT’s residents in the neighborhood. In other words, if you met Housing and Transportation Affordability Index (H+T® someone on the sidewalk in that neighborhood, are they more Index) were calculated for each transit zone based on a likely to live there or work there? national typical household. More information about the H+T Index and its methodology can be found at htaindex.cnt.org. Place Types: The 367 transit zones in study were divided into five sets by Residential places—0 to 33.3 percent employment Mixed-use places—33.4 to 66.7 percent employment their 2010 VMT values. Employment places—66.8 to 100 percent employment Performance Characteristics (VMT per household in 2010): High VMT—17,851 to 22,850 High-Moderate VMT—15,701 to 17,850 Moderate VMT—13,201 to 15,700 Low-Moderate VMT—11,351 to 13,200 Low VMT— 9,100 to 11,350

BERWYN METRA Photo Credit: Flickr User David Wilson, CC License

CASE STUDIES Six station areas were chosen to demonstrate the usefulness of the TOD typology for understanding development in the Chicago Region and explore the variety of development patterns within the transit zone. The following stations were chosen because they all have a demonstrated commitment to TOD and the communities have diverse characteristics representative of the Region: Berwyn BNSF Metra Station Elmhurst Metra Union Pacific West Line Grand Red Line Station Highland Park Metra Station UPN Metra Orland Park (143rd Street) SWS Line Metra 18th Street Pink Line CTA Station

38 REGIONAL TOD ANALYSIS

BERWYN METRA STATION Photo Credit: Flickr User reallyboring, CC License

Berwyn BNSF Metra Station Berwyn, Illinois Moderate VMT, Mixed-Use A community hard-hit by the recession turns to TOD planning as a revival tool

Berwyn is a well-established community just 10 miles west of 2010, but a four percent increase in residential density (residential units Chicago’s downtown. Known for its bungalow-style houses, Berwyn is per acre) causing the household vacancy rate to go from 4.7 percent in home to many first-time homebuyers who are attracted to its affordability, 2000 to 7.6 percent in 2010. variety of amenities, and close proximity to Chicago via car or public Moderate VMT, Mixed-Use transit zones like Berwyn experienced a transit. Although it was hard-hit by the recession, Berwyn has turned, in modest increase in residential density of 14 percent while the Region part, to TOD planning as a tool to reinvigorate its local economy. saw an increase of 34 percent. In the face of the challenge posed by this Many of the Metra train boardings at Berwyn’s three train relatively low increase of density around its transit station, the city turned, stations are by individuals who live outside of the community. in part, to planning and policies to help rebuild its local economy. The Berwyn train station is at the edge of a commuter payment zone; In 2008, the City of Berwyn released its TOD Study for the commuters who board at stations west of Berwyn and travel east toward Berwyn Metra station. In 2006, the RTA funded Berwyn’s Transit- downtown Chicago are charged more for their tickets, encouraging Oriented Master Plan entitled Berwyn: Transit-Oriented Development commuters from outside of Berwyn to drive to this Metra station. A Study for the three Berwyn Metra station areas along the Metra BNSF 2002 study by Metra found that 41 percent of the boardings at the three rail corridor between Harlem Avenue and Ridgeland Avenue: LaVergne, Berwyn stations are made by passengers from neighboring communities Berwyn, and Harlem Avenue. outside of the station’s transit zone. This high rate of riders from outside of the zone helps to explain why the Berwyn station zone saw no change in The plan proposed that the Berwyn stop, perceived to be the center non-auto commutes to work by local residents. Berwyn’s transit zone has of the city, would be transformed into the new hub for restaurants, an inner core of transportation facilities, mixed-use buildings, residential entertainment and shopping outlets. In response to the large numbers multifamily buildings, and medical institutions. The remainder of the zone of automobiles that are used to reach the station, commuter parking and is primarily single family residential housing with some multifamily housing its availability have been contentious issues. That same year, Berwyn clustered along the Metra line. built a 39,000 square foot parking structure with 15,000 square feet

Berwyn’s TOD planning was an exercise in resilience during of ground floor retail and 1,114 parking spaces—with 300 dedicated the height of the recession. Berwyn was hit particularly hard by the to commuters. The rest of the spaces would be shared for other retail housing crisis that started in 2007. The Berwyn Metra station transit uses. The structure has since been built and parking spaces dedicated zone saw a two percent decrease in households between 2000 and to commuters are 80 percent occupied on a regular basis. The ground

©2013 CENTER FOR NEIGHBORHOOD TECHNOLOGY 39 floor space was initially intended for retail, but it was ultimately developed actually grew. Berwyn continues to build on its successful development as an indoor sports and training facility that will serve residents of Berwyn of multifamily rental units near transit. In 2012 Berwyn put out a request and surrounding communities. for proposals for a multifamily residential development targeted to seniors across the street from the Berwyn train station. Berwyn’s 2008 plan sought to focus development around all three of its train stations with priority given to the Berwyn station. The plan promoted Berwyn continues its TOD planning efforts. In 2011, Berwyn pedestrian development around the stations, including bike paths and was the recipient of a Model Communities Grant, allowing the city to streetscaping along new connections to the parks. pursue new planning efforts to encourage healthy and non-auto transit options such as biking and walking. That same year the West Cook Rental units and recreational amenities in Berwyn have been County Housing Collaborative announced its plans to update the TOD in high demand. In 2009, a 53-unit condo building was developed development strategy for five communities including Berwyn. Also in the Berwyn station transit zone. It was not successful and went into in 2011, in an effort to renew its housing market, residents of Berwyn foreclosure and now has been converted to rental units, all of which started a Berwyn Bungalow Preservation Initiative that offers incentives are now occupied. The ground floor of this building is still struggling; of to people who buy or renovate a bungalow. In October 2012, Berwyn the 15,000 square feet available for retail, 11,000 remain unoccupied. released its Comprehensive Plan, which builds on its plans from the Elsewhere in Berwyn, in contrast, local economic development planners recent past as well as CMAP’s GO TO 2040 Plan. report that the retail not only withstood the economic downturn, but

Average for Average for All Chicago Berwyn Metra Transit Zone Transit Zone Type Transit Zones Change Change Change Metric 2000 2010 2000-2010 2000-2010 2000-2010 Households 1,636 1,703 4% 1% 7% VMT per Household 13,120 16,578 26% 17% 14% Household Transportation Costs $9,008 $12,969 44% 42% 36% H+T Cost as a Percent of Income* 67% 62% -5% 0% 2% Household Income $75,016 $96,268 28% 19% 23% Jobs 4,101 4,233 3% -10% 3% Residential Density (Units/Residential Acre) 4.2 4.5 8% 5% 34% Transit/Walk/Bike Commuters* 24% 23% -1% 0% 0% * H+T cost shows change as % of Income; Transit/Walk/Bike Commuters show change as the difference between 2010 and 2000 values. All other metrics use percentage change. 2010 Proxy Data: The data in this table used for H+T cost, Transportation costs, vehicle miles travelled (VMT) and transit/walk/bike commuters are from ACS 2005-2009 Data. Jobs data comes from The US Census’ 2002 and 2009 Local Employment Dynamics and have been used as proxies to represent year 2000 and 2010 data, respectively.

40 REGIONAL TOD ANALYSIS

ELMHURST METRA STATION Photo Credit: Flickr User mac steve, CC License

Elmhurst Metra Union Pacific West Line Elmhurst, Illinois High-Moderate VMT, Mixed-Use High change in VMT, mix of employees (commercial land uses) and residents (residential land uses) Prioritizing density near Metra station

Elmhurst is a suburb 18 miles west of Chicago. Located near major station. The plan was later updated by the city, in 2006, to include TOD- expressways and a short drive to both airports, Elmhurst is a desirable oriented principles in order to encourage and facilitate access to the location for both businesses and residents. It is home to Elmhurst downtown Metra station by all modes of transportation. College, as well as three fine art museums. The Elmhurst Metra station In implementing the plan, Elmhurst put land use regulations in is in the center of the downtown, a mixed-use residential, retail, and place that allow greater density and mixed-use development entertainment district. This transit zone is distinguished by its wide variety around the station. Developers, for example, can now apply for a of retail and amenities, while maintaining a small town feeling. conditional-use permit for buildings up to eight stories. Between 2000 In 1999, the City of Elmhurst completed its Downtown Plan, and 2010, Elmhurst developed almost 400 new units of housing, largely funded in part by the RTA. This plan found that pedestrian and upscale and owner occupied, and one office building with 30,000 new vehicular access to the Metra station was a deterrent to use of the train square feet of space. The majority (55.2 percent) of residential growth in the transit zone came from buildings with ten or more units, a nod Percentage Change for Number to the TOD principles guiding the city’s plan. Elmhurst also financed a of Structures in Elmhurst Transit structured parking lot that allowed underutilized surface parking lots to Zone by Site 2000-2010 be redeveloped. The 2006 TOD plan called for a 253-space parking structure to accommodate commuters and downtown visitors, which was 60% built in 2010. 50% 40% Interviews with developers informed us that despite this flurry 30% of TOD construction, the Elmhurst station area only saw a net 20% growth of 158 housing units, only 67 of which were occupied 10% 0% in 2010. This low increase in housing units was due to the demolition -10% of existing units and an increase in vacant homes. Residential density -20% increased by only eight percent. -30% -40% Elmhurst’s transit zone saw a 26 percent increase in household 10+ Units Single Units 2-9 Units VMT over the study period. This far surpassed typical High- data source : National TOD Database Moderate VMT, Mixed-Use transit station areas, and the Chicago

©2013 CENTER FOR NEIGHBORHOOD TECHNOLOGY 41 Region as a whole. This transit zone saw a one percent decrease in non- Elmhurst made efforts to boost its transit value by developing auto commuting for trips to work, while typical High VMT, Mixed type within its transit zone, but it didn’t see the benefits. Instead, transit zones and the Region saw no change in non-auto travel behavior. Elmhurst saw a significant increase in VMT and transportation costs, low Transportation costs as a percentage of median income increased 44 increases in residential density, and a loss in non-auto commuters for percent for the Elmhurst transit zone, as compared to 42 percent for the trips to work. We can’t be certain about why Elmhurst’s efforts yielded typical High-Moderate VMT. this effect, but we might assume that Elmhurst’s housing market was responding to the increase of incomes by building upscale housing just Household income increased 28 percent, significantly higher than before the economy went into recession. The increase in household the 15 percent increase of average High-Moderate VMT, Mixed-Use income and VMT may be indicators of the lack of mixed-income station type and the Region. This higher household income helped to developments. Elmhurst may have consolidated smaller, rental units into lower the proportional cost of housing and transportation for residents larger condo units in response to its plans to build for higher-income living within the Elmhurst transit zone by five percentage points from 67 households. The increase in vacancies could also have been related to percent to 62 percent. the building boom in the 2000s that led to the development of units that were never occupied.

Average for Average for All Chicago Elmhurst Metra Transit Zone Transit Zone Type Transit Zones Change Change Change Metric 2000 2010 2000-2010 2000-2010 2000-2010 Households 3,106 3,032 -2% 7% 7% VMT per Household 11,955 14,747 23% 19% 14% Household Transportation Costs $8,420 $11,709 39% 40% 36% H+T Cost as a Percent of Income* 50% 51% 2% 0% 2% Household Income $46,518 $56,440 21% 25% 23% Jobs 4,514 4,724 5% 16% 3% Residential Density (Units/Residential Acre) 7. 3 7.6 4% 14% 34% Transit/Walk/Bike Commuters* 19% 18% 0% 1% 0% * H+T cost shows change as % of Income; Transit/Walk/Bike Commuters show change as the difference between 2010 and 2000 values. All other metrics use percentage change. 2010 Proxy Data: The data in this table used for H+T cost, Transportation costs, vehicle miles travelled (VMT) and transit/walk/bike commuters are from ACS 2005-2009 Data. Jobs data comes from The US Census’ 2002 and 2009 Local Employment Dynamics and have been used as proxies to represent year 2000 and 2010 data, respectively.

42 REGIONAL TOD ANALYSIS

CTA RED LINE STATION GRAND AT AND STATE Photo Credit: Flickr User Zol87, CC License

Grand Red Line Station River North neighborhood, Chicago Low VMT, High Employment High employment share with low vehicle miles traveled Mixed-use, high density central business district station with a diversity of economic strengths

In 2012, after nearly 70 years of operation, the Grand Avenue Red Line risen by 29 percent to $1,471 since 2000, compared with the median subway station received a $73.6 million renovation that modernized rent for the Region of $898. Also, the median monthly homeowner and expanded the station to better serve the high volume of transit costs had dropped by nine percent to $2,642; the same median figure riders who pass through to access jobs, shopping, and entertainment. increased by 40 percent to $2,188 for the Region. According to the The Red Line provides 24-hour service and takes passengers to the Chicago Loop Alliance’s 2010 Annual Report,21 the median rent for a northern limits of the city at Howard and to 95th Street and the Dan Ryan condo in Chicago’s Loop rose 25 percent between 2005 and 2010. Expressway on the city’s South Side. Nearby destinations include Navy These significant changes in household costs are the result of a rising Pier, the Merchandise Mart, Michigan Avenue (the Magnificent Mile), demand for rental residences since the housing market crash that started 26 institutions of higher learning, and many dining and entertainment in 2007. While Chicago’s transit shed saw a loss in rental households options. The train station connects with three CTA bus lines (Routes 29, (15,095, or 3.4 percent), the Grand Red Line transit zone bucked 36, and 65), as well as a seasonal Navy Pier Trolley. the trend and saw a 37-percent increase. The rental market has become increasingly competitive throughout the Chicago Region, This transit zone, like much of the rest of Chicago’s downtown, especially within the transit zone, where renters are increasingly has developed characteristics resembling a residential unable to afford to live. neighborhood. With increases in population and households, and businesses to support them, the Grand Red Line subway station National trends for metropolitan areas saw larger population growth zone has diversified its economy over the last decade. Additions to concentrated near their cores. Chicago led the way as the metropolitan Chicago’s downtown—including Millennium Park (2004), college area with the largest population growth increase within two miles of its campus expansions, revitalization projects, and a wealth of dining and city hall. (Chicago saw a 36-percent increase in this population.) The entertainment—have made this part of the city a more desirable place to Grand Red Line transit zone saw a population increase of 48 percent live. These new elements and the populations they attract help to keep the and a housing stock increase of 46 percent. Based on the transit zone downtown area lively after the work crowd has gone home. typology in this report, the station is a high employment, low VMT zone. This suggests that the zone’s jobs and non-auto patterns are indicators of The area is defined by high density buildings that contain higher-cost offices and residences, as well as high pedestrian sustainability.

and auto traffic. In 2010, the zone’s population density was 12 people Transit ridership for trips to work for the Grand station saw a generally and four households per acre. The median rent for the transit zone had steady increase with the exception of two separate periods between

©2013 CENTER FOR NEIGHBORHOOD TECHNOLOGY 43 2003 and 2007. Similar dips in the upward trend line for jobs can Between 2000 and 2010, the zone saw an increase in households, be seen between 2002 and 2009. This may have been due to the household density, household income, jobs, and savings in expenditures recession or other economic factors that affected the workforce and their of housing and transportation costs as a percentage of income. These travel patterns to work. Gas prices were on a similar upward trend with factors are promising for continued TOD success. the exception of one period between 2007 and 2009.

Grand Transit Shed Total Jobs 2002-2009

155,000 150,000 145,000 140,000 135,000 130,000 125,000 120,000 2002 2003 2004 2005 2006 2007 2008 2009 data source : National TOD Database

Average for Average for All Chicago Grand Red Line Transit Zone Transit Zone Type Transit Zones Change Change Change Metric 2000 2010 2000-2010 2000-2010 2000-2010 Households 11,573 16,866 46% 62% 7% VMT per Household 6,260 7,752 24% 32% 14% Household Transportation Costs $5,199 $4,896 -6% 4% 36% H+T Cost as a Percent of Income* 54% 52% -2% -2% 2% Household Income $61,850 $81,604 32% 28% 23% Jobs 136,188 148,355 9% 4% 3% Residential Density (Units/Residential Acre) 67.6 112.3 66% 107% 34% Transit/Walk/Bike Commuters* 64% 58% -6% -3% 0% * H+T cost shows change as % of Income; Transit/Walk/Bike Commuters show change as the difference between 2010 and 2000 values. All other metrics use percentage change. 2010 Proxy Data: The data in this table used for H+T cost, Transportation costs, vehicle miles travelled (VMT) and transit/walk/bike commuters are from ACS 2005-2009 Data. Jobs data comes from The US Census’ 2002 and 2009 Local Employment Dynamics and have been used as proxies to represent year 2000 and 2010 data, respectively.

44 REGIONAL TOD ANALYSIS

HIGHLAND PARK METRA STATION Photo Credit: Flickr User Zol87, CC License

Highland Park Metra Station UPN Metra Highland Park, Illinois High-Moderate VMT, Mixed-Use Moderately high VMT and mixed (employment and residential) population and land uses An affluent North Shore community strengthens quality of life through TOD

The Highland Park transit zone is a High-Moderate VMT, mixed- but incomes also increased significantly, so that transportation costs employment residential station with shopping, including groceries, dining, as a percent of income increased by only two percent. H+T cost as a and entertainment. It is predominantly residential, low- to moderate- percent of income decreased almost four percent, mainly due to stagnant density with an affordable housing policy that promotes housing for a mix housing costs. of incomes. In 2001, The Plan Commission for the City of Highland Park partnered The Highland Park Metra stop is in downtown Highland Park, an affluent with Camiros to develop a plan for the city’s central district. This plan suburb 23 miles north of downtown Chicago. The station is in the heart of sought to revive the community, which had traditionally served as a hub of Highland Park’s downtown area, a mix of upscale shopping and housing. activity for surrounding North Shore communities. The 2001 plan has led The area is one of the most vibrant and thriving commercial areas on the to the following public and private improvements in the Metra transit zone: North Shore, offering a wide range of retail to meet every day needs. There has been substantial growth in dense, multifamily housing in the Public: downtown area over the last decade. Redeveloped art center The station itself is bracketed by parking lots. PACE buses connect the Purchase of the Highland Park Theater and adjacent parking lot station locally. The Robert McClory Bike Path runs parallel to the train tracks, connecting Highland Park to other suburbs. This is mostly a New parking structures recreational bike path. There are no car-share locations in Highland Park. Improved pocket parks for pedestrians

Households in the Highland Park transit zone are upper-income Private: homeowners living in low-density housing. The number of households in this transit zone declined by two percent between 2000 and 2010. 80,000 square foot Renaissance Place: an upscale, mixed use retail, Incomes rose 25 percent over the study period. Transit ridership for trips office, and residential structure to work and the use of alternative transportation modes declined in the Banks and retail Highland Park transit zone between 2000 and 2010. Household VMT 430 Park Avenue: mixed use retail, office, and residential rose over the last decade by 11 percent, less than in other transit zones. Transportation costs rose 42 percent, more than in other transit zones, Laurel Terrace: mixed use, 85,000 square foot building

©2013 CENTER FOR NEIGHBORHOOD TECHNOLOGY 45 In 2009, Highland Park updated its 2001 downtown planning strategy in $20,000, and the Grand-Red Line zone’s costs rose 26 percent to order to remain a competitive player in the North Shore commercial real nearly $22,000. This is in part attributable to the weak market, but estate market. Highland Park’s commitment to providing affordable housing cannot go unrecognized. Organizations such as Community Partners for One of the striking facts about Highland Park is that H+T costs as a Affordable Housing are working with local, state, and federal agencies to percentage of income declined seven percent, compared to the modest ensure that there are affordable options for working families in the area. rises that were seen in other transit zones. While transportation costs grew sharply and incomes rose just above the Regional average, housing The City of Highland Park has long been committed to creating a costs rose just two percent to just over $23,000 a year, well below compact, diverse neighborhood around the downtown transit zone. The the Regional average of 21 percent. Highland Park has the highest city has a strong vision for creating and maintaining a competitive edge household costs of the case study areas presented in this report, but for its downtown development, and has adopted a Sustainability Plan and the slight increase is still remarkable, considering the Orland Park 143rd Non-motorized Transportation Plan. Highland Park has positioned itself Street Metra zone’s housing costs rose nearly 25 percent to just over on a long-term path toward sustainability.

Average for Average for All Chicago Highland Park Metra Transit Zone Transit Zone Type Transit Zones Change Change Change Metric 2000 2010 2000-2010 2000-2010 2000-2010 Households 1,658 1,622 -2% 1% 7% VMT per Household 16,075 17, 824 11% 17% 14% Household Transportation Costs $9,171 $13,062 42% 42% 36% H+T Cost as a Percent of Income* 76% 70% -5% 0% 2% Household Income $76,587 $95,469 25% 19% 23% Jobs 3,835 3,877 1% -10% 3% Residential Density (Units/Residential Acre) 4.1 4.3 5% 5% 34% Transit/Walk/Bike Commuters* 20% 18% -1% 0% 0% * H+T cost shows change as % of Income; Transit/Walk/Bike Commuters show change as the difference between 2010 and 2000 values. All other metrics use percentage change. 2010 Proxy Data: The data in this table used for H+T cost, Transportation costs, vehicle miles travelled (VMT) and transit/walk/bike commuters are from ACS 2005-2009 Data. Jobs data comes from The US Census’ 2002 and 2009 Local Employment Dynamics and have been used as proxies to represent year 2000 and 2010 data, respectively.

46 REGIONAL TOD ANALYSIS

ORLAND PARK METRA STATION Photo Credit: Flickr User amtrak_russ, CC License

Orland Park (143rd Street) SWS Line Metra Orland Park, Illinois High VMT, Mixed-Use High change in annual VMT, mixed (employment and residential) population and land use Major push for public improvements

The Village of Orland Park is a well-connected suburb 25 miles south The Village has moved aggressively to promote TOD, which may of Chicago. The Orland Park 143rd Street stop is one of three Metra reverse these trends in the coming decade. The Orland Park station was stops in Orland Park. Situated on the South West Service Line, this stop conceived as part of an RTA funded study what was completed in 2000. offers service to downtown Chicago. Due to freight congestion, Metra Orland Park constructed and opened a new Metra station at 143rd Street historically operated only a handful of trains to the Chicago Loop during in April, 2007. rush period. That number has expanded, and riders can now even take The Main Street Triangle, built around the train station, will be a the South West Service to the Loop on Saturdays. pedestrian-friendly mixed-use development. It will include over 155,000 Owing in part to this modest commuter service, 143rd Street originally square feet of commercial space and 240 housing units. The Village of developed as a car-oriented commercial and residential center for the Orland Park implemented a Tax Increment Financing (TIF) zone for the community. Much of the land around the station is strip center retail or area, using the funds to assemble the land, conduct environmental reviews parking for shoppers. There is some housing from which many errands and remediation, and create infrastructure improvements. To date, Orland can be accomplished on foot. There are restaurants, groceries, retail Park has invested over $30 million in public improvements. The Triangle stores, parks, schools, and entertainment less than a mile from the station. will be connected via pedestrian bridge to Orland Park Crossing, an Orland Square is a major regional mall for southwest Cook and northern upscale, walkable shopping complex across La Grange Road. Will Counties; its stores may provide competition for additional retail One of Orland Park’s more recent TOD projects is Ninety 7 Fifty on the around the transit stop. Park, a six story mixed-use transit-oriented development that represents Households, employment, and transit use all declined around the station the first phase of the village’s new downtown district. The development over the last decade. Households in the transit zone declined four will provide a mix of upscale residences and retail as well as a pedestrian percent over the study period. Both transit ridership for trips to work and friendly space near the 143rd street Metra station. The development will alternative transportation modes declined in the Orland Park transit zone consist of 295 residences, 4,000 square feet of first floor commercial between 2000 and 2010. However, household VMT rose only five space, 8,666 square feet of residential amenity space and 365 parking percent, well below the average for Chicago’s transit shed. Transportation spaces. These residences will serve a wide range of residents from costs rose over 40 percent, and increased from 12 percent to 17 percent young professionals to empty nesters. This kind of development is new of median incomes. Employment in the Orland Park 143rd Street transit to Orland Park and is filling a gap that was identified by the Village of zone declined 18 percent, from 2,653 to 2,165 jobs. Orland Park. The development anticipates housing 401 residents.

©2013 CENTER FOR NEIGHBORHOOD TECHNOLOGY 47 Construction began in early 2011 and is planned to be completed by the This commitment to TOD should help boost job growth along the end of 2013. South West Service line and create more destinations for transit riders. Few transit-served employment centers exist near Orland Park’s 143rd Since the station has opened the SWS line has doubled its service and Street transit zone in Southwest Cook and Northern Will Counties, so seen an increase of 20 percent in ridership for trips to work. The Village households may still have to drive to work and amenities, even when they has also recently updated their zoning ordinance to include transit- live in a TOD. supportive regulations.

Average for Average for rd All Chicago Orland Park 143 Metra Transit Zone Transit Zone Type Transit Zones Change Change Change Metric 2000 2010 2000-2010 2000-2010 2000-2010 Households 496 475 -4% 3% 7% VMT per Household 18,896 19,863 5% 7% 14% Household Transportation Costs $9,936 $14,101 42% 40% 36% H+T Cost as a Percent of Income* 62% 67% 4% 0% 2% Household Income $77,665 $80,696 4% 19% 23% Jobs 2,653 2,165 -18% -4% 3% Residential Density (Units/Residential Acre) 3.8 3.5 -6% 1% 34% Transit/Walk/Bike Commuters* 11% 7% -4% 0% 0% * H+T cost shows change as % of Income; Transit/Walk/Bike Commuters show change as the difference between 2010 and 2000 values. All other metrics use percentage change. 2010 Proxy Data: The data in this table used for H+T cost, Transportation costs, vehicle miles travelled (VMT) and transit/walk/bike commuters are from ACS 2005-2009 Data. Jobs data comes from The US Census’ 2002 and 2009 Local Employment Dynamics and have been used as proxies to represent year 2000 and 2010 data, respectively.

48 REGIONAL TOD ANALYSIS

CTA PINK LINE STATION 18TH AT AND PAULINA Photo Credit: Flickr User reallyboring, CC License

18th Street Pink Line CTA Station Pilsen neighborhood, Chicago Low VMT, Residential Primarily residential community with low change in annual vehicle miles travelled Historically dense community with declining population and changing demographics

The Pilsen neighborhood is an enclave of Mexican Culture. nurture the culture that has made Pilsen what it is.” This plan is supported Located on Chicago’s southwest side, just four miles southwest of by Alderman Danny Solis and 23 local community groups who have downtown, the 18th Street Pink Line station is in the middle of the Pilsen pledged to participate in the implementation. neighborhood. Since the 1960s, Pilsen has been home primarily Changing demographics have created the perception of a threat to Mexican-American families. In 2010, 84 percent of the zone’s to the community’s strong cultural identity. Between 2000 and population was Latino or Hispanic. Sixty-five percent of the households in 2010, the area lost population and households, largely Hispanic, and the 18th Street transit shed were families. gained smaller populations of other races including whites and Asians. Just five stops from Chicago’s Loop, the 18th Street Pink Line Other than Mexican-American families, the community is populated by transit zone provides access to a wealth of attractions. The students and young singles, who are perceived to be responsible for the train station is located on 18th, a two-lane street with parking on either gentrification of the area. side, and older three- to four-story buildings with commercial space The primary land use patterns of the transit zone are residential, on the ground floor and rental apartments on the upper levels. The industrial and urban mixed use. The 18th Street transit zone’s industrial area is also characterized by iconic Mayan sidewalk medallions and land uses include part of the Pilsen Industrial Corridor Tax Incremental large, bright murals that represent images of Mexican cultural heritage. Financing (TIF) District and the container shipping carrier APL It is home to many mom and pop Mexican restaurants, the National intermodal yard on Western Avenue. This zone has potential for infill Museum of Mexican Art and a burgeoning art gallery district. Residents development on the large amount of vacant land in the northern end can catch a short train ride to major job centers such as the Loop, adjacent to industrial and other land uses. A 2004 study by the New University of Illinois at Chicago (UIC), and the UIC Medical District. The Communities Program showed that, in large parts of Pilsen, the value Pilsen neighborhood, with its strong Mexican identity, is now a tourist of the land was greater than the structures or physical improvements. destination. Local stakeholders have worked to preserve the character of Census data shows that 1940 was the average year that a structure was the neighborhood while continuing to attract developments for residents built the 18th Street transit zone; many of these structures, particularly the and visitors. An example came in 2006 when the Local Initiatives residential apartments, are quite old. Support Corporation (LISC) released Pilsen: A Center of Mexican Life, a plan that cautioned, “As others discover the beauty of our housing Development in the PiIsen neighborhood over the last decade has stock and the vitality of our local economy, it is up to us to protect and led to some demographic changes in the community. Race, age,

-1,000

-2,000

-3,000

-4,000

-5,000 Change in Total Number of White Number of Black or Number of Asian Number of Hispanic or Population African American Latino data source : National TOD Database

DEMOGRAPHIC SHIFT. The 18th Street transit zone saw large losses in its Hispanic and black population, and gains in its white and Asian population.

Average for Average for th All Chicago 18 Street Pink Line Transit Zone Transit Zone Type Transit Zones Change Change Change Metric 2000 2010 2000-2010 2000-2010 2000-2010 Households 5,107 4,741 -7% 2% 7% VMT per Household 9,040 10,993 22% 17% 14% Household Transportation Costs $6,442 $8,357 30% 22% 36% H+T Cost as a Percent of Income* 31% 35% 4% 4% 2% Household Income $25,766 $27, 520 7% 41% 23% Jobs 3,171 5,067 60% 4% 3% Residential Density (Units/Residential Acre) 19.3 21.2 10% 10% 34% Transit/Walk/Bike Commuters* 35% 40% 5% 1% 0% * H+T cost shows change as % of Income; Transit/Walk/Bike Commuters show change as the difference between 2010 and 2000 values. All other metrics use percentage change. 2010 Proxy Data: The data in this table used for H+T cost, Transportation costs, vehicle miles travelled (VMT) and transit/walk/bike commuters are from ACS 2005-2009 Data. Jobs data comes from The US Census’ 2002 and 2009 Local Employment Dynamics and have been used as proxies to represent year 2000 and 2010 data, respectively.

50 REGIONAL TOD ANALYSIS and incomes have played a role in the demographic shift of the 18th Between 2000 and 2010, the 18th Street transit zone lost Street transit zone. The Chicago Region’s Hispanic or Latino population 4,317 people, 23 percent of its population. In comparison, typical increased by 28.5 percent over the last decade, while the 18th Street Residential, Low VMT transit zones showed a 2000 to 2010 population transit zone, with its strong Mexican identity, saw a decline (4,385 or 27 loss of only 412 people. The 1990s and early 2000s saw an influx of percent) of its Hispanic or Latino population. This transit zone has seen immigration to Chicago’s ethnic enclaves, which offset the otherwise an increase in whites (663 people) and Asians (99 people) over the past declining population of these areas. As this immigration influx tapered off, decade—many of them students and young singles who flock to the area families aged, and poverty rates rose, immigrant populations represented for its low rents in and proximity to transit. While the Chicago Region smaller proportions of the total population in communities like Pilsen.* saw a gain of 36 percent in the Latino/Hispanic population, the Chicago This population loss can be linked to the loss of 366 households (seven transit shed saw a Latino population loss of 0.54 percent. This suggests percent). Most of this loss was in rental households. that new and existing Hispanic populations are living in Pilsen at the rates The 18th Street transit zone saw an increase of four percent in transit lower than they did in recent decades. This change in racial makeup has ridership for trips to work and a five percent increase in its share of non- led to accusations of the community being gentrified by the new non- auto commuters for trips to work. This increase in non-auto commuters Hispanic population. was five times greater than typical for this type of transit zone. Another demographic change has been the return of young professional The 18th Street transit zone gained 1,896 jobs, far more than the average Mexican-Americans who grew up in the neighborhood’s working 221 jobs that the typical Residential, Low VMT transit zone type gained class families. Many, now with higher incomes, have moved back to the for that period of time. The zone has a thriving local economy with neighborhood to raise their own families in Pilsen’s affordable homes outstanding job growth and high transit use, with the potential for growth or to become landlords in the community’s popular rental market. The in both areas. The zone also has significant potential to develop its vacant community is said to be shifting from a blue collar community to one that and underutilized land which can address the challenges of population is a mix of both blue and white collar households. and household losses, while reinforcing the community’s unique Mexican-American identity.

*Hispanics of Mexican Origin in the United States, 2010. Pew Hispanic Center RSS. N.p., n.d. Web. 07 Dec. 2012.

GO TO 2040 took an important step in establishing transit-supportive priorities for the Region. Alone, it will not overcome the barriers to local governments, developers, and citizens making location-efficient transit choices in the Region. To implement GO TO 2040, all levels of government will need to adopt new priorities that target resources to the right locations across the Region. To do this, the Center for Neighborhood Technology advocates for actions which will do the following:

Recommendation 1: Create TOD Zones

Optimizing the level of TOD around transit stations is a proven means of increasing transit use and achieving many of the economic, environmental, and quality of life goals that align with sustainability. TOD has also proven to be a secure and profitable form of development for investors in many situations. In most cases in this Region, however, TOD involves the reuse of previously developed properties. Such redevelopment poses problems in terms of modifying existing zoning, assembling land, and establishing more intensive land use. The Chicago Region needs to adopt an integrated program of zoning reforms and financial incentives to overcome the impediments to TOD.

Implementers: a. Establish Mixed Use Zoning Municipalities, along with Council Many local land-use regulations do not explicitly allow TOD, so new developments must go through a of Governments organizations, with lengthy and contentious community process that greenfield projects typically avoid. Communities can assistance from CMAP and RTA address both of these obstacles by building upfront community support for a mixed-use zoning code that Priority: HIGH allows TOD as a matter of right. Feasibility: MEDIUM

Implementers: b. Incentivize Higher Density Development Municipalities along with Council Developers and landowners should be engaged through incentives that encourage them to build of Governments organizations, with structures that support higher density near transit stations. For example under favorable market conditions, assistance from CMAP and RTA zoning that permits higher floor area ratios (FAR) will raise investors’ potential return on investment Priority: MEDIUM per acre of land and stimulate higher density development. The City of Evanston has led the way with a proposed zoning code that allows for public benefit bonuses on FAR for developments that provide Feasibility: MEDIUM affordable units, shared structured parking, and/or quality public space.

Implementers: c. Offer Expedited Building Permits Municipalities along with Council For developers, time is money: they need fast action by municipalities to minimize the carrying cost of Governments organizations, with of property awaiting development. The City of Chicago, for example, incentivizes green buildings by assistance from CMAP and RTA guaranteeing a building permit decision within 30 business days to projects that meet certain standards, Priority: HIGH compared with the usual 90 days. Municipalities throughout the Region should offer a similar building permit incentive to TODs as part of a new zoning package. Feasibility: HIGH

Implementers: d. Decrease Parking Requirements Municipalities along with Council of The City of Chicago has cut parking requirements by half for buildings within 600 feet of transit stops. A Governments organizations, CMAP, rental apartment building close to a Chicago transit stop, for example, needs only one parking space for and RTA as providers of technical every two apartments, compared with one space per unit for buildings located farther away from stations. assistance to municipalities Communities could also follow the example of Fayetteville, Arkansas, which allowed developments to Priority: HIGH fulfill their requirement by providing parking for bicycles rather than automobiles. Both options reduce construction costs devoted to parking, thereby creating more affordable units and more viable projects. Feasibility: HIGH

52 REGIONAL TOD ANALYSIS Implementers: e. Facilitate Structured and Shared Parking Transit agencies, CMAP, IDOT, Acres of surface parking lots sit adjacent to Metra and CTA stations. Structured parking facilities, though Municipalities highly expensive, would consolidate these spaces into smaller parcels and free up additional land for TOD. Priority: HIGH Structured parking should be a possible use of all of the TOD funding and financing mechanisms proposed in these recommendations. In communities where demand is not sufficient to support structured parking, Feasibility: LOW alternatives such as shared parking with nearby businesses and institutions should be considered as means of reducing the parking footprint in TOD areas.

Implementers: f. Use Value Capture Municipalities along with Council The high cost and complex timeline of infill redevelopment has led many municipalities to rely on Tax of Governments organizations, with Increment Financing (TIF) to see projects through from predevelopment to completion. Mechanisms like assistance from CMAP and RTA; TIF enable municipalities to capture the extra property and sales taxes generated by the development and Illinois Legislators adjacent properties and use those revenues to help finance TOD. In some jurisdictions, the revenues are Priority: MEDIUM pledged to operating needs of the transit service. Special Service Areas (SSAs) can also help by financing beautification efforts that increase rents or business health within a TOD. Municipalities should make Feasibility: MEDIUM TOD the explicit focus of TIF, SSA, and other special financing mechanisms. TIF financing often imposes an extraordinary burden on smaller and lower-income municipalities that must defer tax revenue for a generation to incentivize present development. In recognition of the Regional benefits generated through TOD, an act of the Illinois Legislature should allow state funds to replace a portion of local tax revenues obligated by TIFs that finance TODs in lower-income municipalities.

Implementers: g. Practice Joint Development Transit agencies, CMAP, FTA The most recent federal transportation bill, MAP-21, has made it easier than ever for transit agencies to Priority: MEDIUM use residual transit property or redevelop stations for transit-supportive development. The law also makes it easier to flex any Federal Transportation Agency (FTA) planning or capital grants towards mixed-use Feasibility: HIGH projects that boost ridership and increase revenue. Joint development projects must be included in the long range transportation plan developed by local jurisdictions and transit operators through CMAP. Metra and CTA should hire real estate consultants to shape the financing of these projects as well as economic development experts to communicate the expected benefits to the FTA.

The realization of extensive joint development in TOD Zones will require substantial and integrated public investments from a spectrum of agencies, which will stimulate much larger private investments.

Implementers: h. Plan TOD Around Future Expansions CMAP, Municipalities GO TO 2040 identifies over twenty future rail projects throughout our region. Planning for a few fiscally Priority: MEDIUM constrained projects is already underway. These projects will preserve future right-of-way for express bus or transit service. These alignments will create new TODs, many of which developed during the age of the Feasibility: HIGH automobile and may need substantial technical assistance for retrofits.

Access to good transit service reduces residents’ costs of housing and transportation and makes neighborhoods genuinely affordable. However, when the market realizes these benefits in communities, property values rise, and lower income residents may be displaced. A region that optimizes the value of its transit system will replicate model programs and use available funding sources to protect and create affordable housing in its transit zones.

Implementers: a. Implement Municipal Programs for Affordable Housing Municipalities, Housing agencies, Municipalities should develop inventories of vulnerable affordable housing and potential development sites Philanthropic organizations located near transit and then act to expand these affordable housing assets. The City of Highland Park, for Priority: HIGH example, has established an independent, non-profit entity to preserve land and units. It then conveys land to developers, who can use it in tandem with the state Affordable Housing Donation Tax Credit to raise Feasibility: HIGH more equity than would otherwise be possible.

Implementers: b. Establish and Support Affordable Housing Trusts Municipalities, Housing agencies, Housing Trust organizations acquire properties on which they build or maintain affordable housing, Philanthropic organizations sometimes by continuing to own the properties and sometimes by selling them with covenants that limit Priority: HIGH the appreciated value for which they may be sold. Such organizations are especially helpful in successful TOD areas where property values rise rapidly. The work of these organizations in TOD zones should be Feasibility: HIGH supported by public and private contributions similar to the community development funds established for affordable housing in San Francisco and Denver. Parking for shared vehicles rather than private autos can be another efficient use of resources.

Implementers: c. Increase Preferences for Low Income Housing Tax Credit in TOD Areas IHDA The Illinois Housing Development Authority (IHDA) has taken great strides in recent years in adding Priority: MEDIUM location-efficient criteria to its Qualified Action Plan for Low Income Housing Tax Credits, the single biggest source of equity for affordable projects. IHDA should increase the points available to a project Feasibility: HIGH within a TOD and add additional scoring criteria based on that project’s average transportation costs.

Implementers: d. Channel CDBG and HOME Funding Municipalities and Counties The US Department of Housing and Urban Development (HUD) provides these block grants to Priority: MEDIUM Participating Jurisdictions (PJs) to invest in economic development and affordable housing. Those PJs, which include large municipalities and county governments, should pledge to invest them in priority TOD areas. Feasibility: MEDIUM

Implementers: e. Site Housing and Social Services Near Transit Affordable housing services Affordable housing advocacy agencies and supportive social services should locate in vibrant, mixed-use Priority: LOW neighborhoods near transit. This allows better access to these services. Feasibility: HIGH

Implementers: f. Implement Inclusionary Zoning Municipalities In those TOD areas with affordable housing needs, as measured by Illinois’ Affordable Housing Planning Priority: HIGH and Appeal Act, communities should adopt an inclusionary zoning ordinance. Highland Park’s ordinance requires a 20% set aside. These units must be dispersed throughout the development and visually Feasibility: MEDIUM compatible with market rate units.

Implementers: g. Exceed Accessibility Standards Municipalities For people with disabilities and the senior population, public transit may be the only transportation option. Priority: MEDIUM Accessibility policies in TOD should adhere to the spirit and letter of ADA requirements to ensure that portions of development are accessible for those with disabilities. Feasibility: HIGH

54 REGIONAL TOD ANALYSIS Recommendation 3: Match Jobs and Transit

Many limitations of the Chicago Region’s transit system, as well as high transportation costs, traffic congestion, and air pollution, stem from a pattern of removing job centers from transit and mixed-income neighborhoods. A more efficient and healthy pattern may be achieved through systematic and integrated efforts to expand transit services to job centers, site new employment centers in existing, transit-served communities, and promote incentives to commute through transit, biking, or walking.

Implementers: a. Expand Transit Services to Regional Job Centers CMAP, RTA, Transit Agencies, The rail and enhanced bus service expansions recommended in this report should focus on connecting Council of Governments communities to employment centers. Specific examples of this policy include enhancing rail access to the organizations, Municipalities Chicago Loop from the far south side and southern suburbs; expanding transit services to the job centers Priority: HIGH of Oakbrook and the northern suburbs west of O’Hare Airport; and improving rail, bus, or van access to industrial parks throughout the Region. Feasibility: HIGH

Implementers: b. Focus Job Creation Investments in Transit Served Locations CMAP – in its capacity as the region’s Investments to stimulate office-based and industrial employment should prioritize areas that now possess land use as well as transportation extensive transit service such as the city of Chicago’s industrial corridors, Chicago’s south side and inner planning agency – Illinois agencies ring suburbs of Chicago. including DCEO, IFA, and IEPA; Counties, Council of Governments organizations, and Municipalities Priority: MEDIUM Feasibility: MEDIUM

Implementers: c. Direct Businesses to TOD Locations Municipalities, Counties. CDCs, Chicago area local governments should guide prospective companies to transit-served sites. The Neighborhood organizations economic development staffs of local government should quantify and communicate the benefits of Priority: MEDIUM transit service to employers, as these benefits relate to employees’ well-being, increased morale, and reduced absenteeism. Civic and neighborhood groups that support business development should also Feasibility: HIGH communicate the benefits of TOD locations to businesses to help them make informed decisions in the best interest of their companies and the Region’s transportation system.

Implementers: d. Promote Transit Incentives to Employees and Employers Employers and employees Programs that encourage employees to commute by transit, biking, or walking should be promoted organizations, Advocacy groups, more aggressively. For example, the RTA/CTA Transit Benefit Fare Program provides fiscal incentives to Transit agencies employees and employers for transit ridership, but a low number of employers take advantage of it. Priority: MEDIUM Feasibility: HIGH

Implementers: e. Target Workforce Development Workforce development Job training and workforce development groups should focus their efforts on firms and industries that are organizations accessible by transit so that new employees are not forced to commute by car. Priority: MEDIUM Feasibility: MEDIUM

Even dedicated users of an excellent transit system need other transportation choices to complete all of their routine trips. Options for active personal transportation and convenient access to cars must be in place to avoid the financial and environmental costs of individual car ownership and frequent single occupant driving.

Implementers: a. Support Car-Sharing CMAP, Municipalities, IDOT; Metropolitan Chicago is served by for-profit and nonprofit car sharing programs through which tens of Employers and employees thousands of members schedule the use of a car when it is needed. Car-sharing should grow through: organizations; Advocacy groups • The mandated provision of at least one free car sharing parking space at transit stations and at Priority: HIGH apartment buildings with off-street parking; • f Decisions o corporations, institutions, and public agencies to provide car fleets through car sharing Feasibility: MEDIUM agencies; • Temporary public support for car sharing expansion into new community areas until break-even levels of membership are reached in these markets; and • f Decisions o individual citizens to replace personal car ownership with transit, active transportation, and car sharing.

Implementers: b. Facilitate Carpooling CMAP, Municipalities, IDOT; Municipalities should work with employers and advocacy groups to create incentive programs for Employers and employees employees to join carpooling arrangements. organizations; Advocacy groups Priority: HIGH Feasibility: HIGH

Implementers: c. Build Bicycle Infrastructure and Facilities CMAP, IDOT, Municipalities, Transit Local governments should expand the network of dedicated bike trails and separated bike lanes on public agencies streets. In addition, local municipalities and the transit providers should work together to locate secured Priority: MEDIUM indoor bicycle parking in transit stations and in shared parking facilities. Feasibility: HIGH

56 REGIONAL TOD ANALYSIS Recommendation 5: Prioritize TOD Across Agencies

While a list of public policies can set favorable conditions for TOD, substantial public investments are needed to remove impediments to redevelopment and attract the much larger private investments that will build significant amounts of mixed-income housing, mixed-use buildings, and functioning businesses in TODs, especially in moderate and weak markets. Collaboration among a range of agencies is required to make these effective public investments.

Implementers: a. Establish and Direct Resources to Priority Development Areas (PDAs) CMAP, Municipalities, COGs, State The Chicago Metropolitan Agency for Planning (CMAP) should establish a mechanism for communities and regional agencies with transit assets and TOD planning to volunteer to become PDAs. State and Regional agencies as well Priority: HIGH as Councils of Governments (COGs) should pledge to invest in PDAs, using existing resources such as MAP-21, CMAQ, and CDBG. The San Francisco Bay Area pioneered this “bottom up” strategy, and it has Feasibility: MEDIUM inspired transit rich communities to plan for more TOD with the knowledge that Regional resources are available for implementation.

Implementers: b. Support Sub-Regional TOD Funds State agencies, County and In Chicago’s south and near west suburbs, inter-municipal coalitions have secured federal Sustainable municipal governments, Private Communities Challenge grants for the purpose of seeding TOD revolving loan funds. Following examples foundations, Financial institutions of comparable TOD funds in San Francisco, Denver, and Minneapolis-St. Paul, these are structured funds Priority: HIGH that integrate public and philanthropic investments with conventional bank capital to finance mixed-income housing and mixed-use development in TODs. These funds are now in the process of attracting additional Feasibility: HIGH investments and planning their first transactions. These ventures should be supported with investments and technical assistance; they should also be viewed as pilots for a broader Regional TOD initiative.

Implementers: c. Support Sub-Regional Land Banks State agencies, Illinois legislators, Following the successful examples of dozens of Regions across the country, communities in Chicago’s County and municipal governments, southern suburbs have formed a nonprofit land bank to take title to vacant, foreclosed, and tax-delinquent Private foundations, Financial properties; remove impediments to the reuse of these properties (such as title imperfections, back institutions taxes, and environmental contamination); and return the improved properties to the private market. The Priority: HIGH Cook County Board is also considering the establishment of a county-wide land bank. Land banks can be powerful tools for facilitating the redevelopment of properties in potential TOD areas. While these Feasibility: HIGH emerging land banks can act effectively as nonprofit organizations or as agencies of county government, their capacities could be enhanced by state legislation. The efforts of the south suburban and Cook County land banks should be supported through intergovernmental cooperation and public and private investment. These programs should also be viewed as pilots for a potential Regional land bank or a land bank coalition that would advance TOD throughout metropolitan Chicago.

Implementers: d. Establish a Sustainable Communities Fund CMAP, COGs CMAP and COGs should pledge $1 billion dollars in federal transportation dollars to a competitive Priority: HIGH fund that can finance joint development projects and infrastructure improvements that set the stage for TOD, including structured parking, bicycle facilities, and streetscapes. Because COGs have traditionally Feasibility: LOW controlled transportation investment decisions among their member municipalities, they should retain the same discretion and control over the TODs that win awards in the same boundaries. The Sustainable Communities Fund should function in collaboration with sub-Regional and Regional TOD Loan Funds and Land Banks to provide the scale of public investment needed to remove impediments to TOD and allow private investment to flow into TOD across the Region.

1 The TOD database is a product of the Center for Transit- 9 Extensive Regions counties are defined by counties. Oriented Development developed and hosted by the Boston: Bristol County, MA, Essex County, MA, Center for Neighborhood Technology with support from Middlesex County, MA, Norfolk County, MA, Plymouth the FTA. The database is available at http://toddata.cnt. County, MA, Suffolk County, MA, Bristol County, org/ RI, Kent County, RI, Newport County, RI, Providence County, RI, Washington County, RI. New York: Fairfield 2 Center for Neighborhood Technology. Prospering In Place: County, CT, New Haven County, CT, Bergen County, Linking Jobs, Development and Transit to Spur Chicago’s NJ, Bronx County, NY, Dutchess County, NY, Essex Economy. Rep. Chicago: Center for Neighborhood County, NJ, Hudson County, NJ, Hunterdon County, Technology, 2012. Print. NJ, Kings County, NY, Mercer County, NJ, Middlesex 3 Center for Transit-Oriented Development, Frequently County, NJ, Monmouth County, NJ, Morris County, Asked Questions, 2012 http://www.ctod.org/faqs.php NJ, Nassau County, NY, New York County, NY, Ocean County, NJ, Orange County, NY, Passaic County, NJ, 4 367 is the number of Metra and CTA stations that were Putnam County, NY, Queens County, NY, Richmond operating in the year 2000. In order to most accurately County, NY, Rockland County, NY, Somerset County, capture change over the 10-year study period, none of the NJ, Suffolk County, NY, Sussex County, NJ, Union stations opened after the year 2000 were used in this study. County, NJ, Warren County, NJ, Westchester County, 5 Center for Transit-Oriented Development, Frequently NY, Pike County, PA: . Philadelphia: Burlington County, Asked Questions, 2012 http://www.ctod.org/faqs.php NJ, Camden County, NJ, Gloucester County, NJ Salem County, NJ, Berks County, PA, Bucks County, PA, 6 AAA. Your Driving Costs: How Much Are You Really Paying Chester County, PA, Delaware County, PA, Montgomery to Drive? Heathrow: AAA, 2012. Print. County, PA, Philadelphia County, PA. San Francisco: 7 American Public Transportation Association. 2012 Public Alameda County, CA, Contra Costa County, CA, Marin Transportation Fact Book. Rep. 63rd ed. Washington, DC: County, CA, Napa County, CA, San Francisco County, American Public Transportation Association, 2012. Print. CA, San Mateo County, CA, Santa Clara County, CA, Solano County, CA. 8 Center for Neighborhood Technology. Prospering In Place: Linking Jobs, Development and Transit to Spur Chicago’s Economy. Rep. Chicago: Center for Neighborhood Technology, 2012. Print.

58 REGIONAL TOD ANALYSIS 10 Klinenberg, Eric. Going Solo: The Extraordinary Rise and 16 Raphael, Steven, and Michael A. Stoll. Job Sprawl and Surprising Appeal of Living Alone. New York: Penguin, the Suburbanization of Poverty. Rep. Washington D.C.: 2012. Print. Brookings, 2010. Print.

11 Housing cost values are from the H+T Affordability Index 17 Kneebone, Elizabeth. Job Sprawl Revisited: The Changing and are based on the American Community Survey’s Geography of Metropolitan Employment. Rep. Washington values for gross rent and selected owner costs. For more D.C.: Brookings, 2009. Print. information see htaindex.cnt.org. 18 Raphael, Steven, and Michael A. Stoll. Job Sprawl and 12 2010 Public Transportation Fact Book, American Public the Suburbanization of Poverty. Rep. Washington D.C.: Transportation Association, 61st Edition, April 2010 Brookings, 2010. Print.

13 Based on H+T Affordability Index data for typical regional 19 US Census Bureau, Patterns of Metropolitan and household. Micropolitan Population Change: 2000 to 2010, September 2012 14 Reconnecting America, and Center for Transit-Oriented Development. Transit + Employment: Increasing Transit’s 20 The neighborhood around the O’Hare airport CTA stop Share of the Commute Trip. Tech. no. TOD202. N.p.: was excluded as there are no households there and thus no Federal Transit Administration, 2008. Print. household VMT values.

15 The US Department of Housing and Urban Development 21 Chicago Loop Alliance. Chicago Loop Alliance: 2010 defines income groups as follows: Households earning: Annual Report. Rep. Chicago: Chicago Loop Alliance, between 120 and 80 percent Area Median Income (AMI) 2010. Print are considered “moderate-income” have incomes below 80 percent AMI, “low-income” is below 50 percent AMI, “very low-income” and below 30 percent AMI, “extremely low-income.”

The Center for Neighborhood Technology (CNT) is an award-winning innovations laboratory for urban sustainability. Since 1978, CNT has been working to show urban communities in Chicago and across the country how to develop more sustainably. CNT promotes the better and more efficient use of the undervalued resources and inherent advantages of the built and natural systems that comprise the urban environment.

As a creative think-and-do tank, we research, promote, and implement innovative solutions to improve the economy and the environment; make good use of existing resources and community assets; restore the health of natural systems and increase the wealth and well-being of people—now and in the future. CNT’s unique approach combines cutting edge research and analysis, public policy advocacy, the creation of web-based information tools for transparency and accountability, and the advancement of economic development social ventures to address those problems in innovative ways.

CNT works in four areas: transportation and community development, water, energy and climate. CNT has two affiliates, IGOTM CarSharing and CNT Energy.

CNT is a recipient of the 2009 MacArthur Award for Creative and Effective Institutions.

More information about CNT is available at www.cnt.org

For more information, contact CNT: [email protected] | 773.278.4800

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URBAN WONK

EMILY BADGER MAR 11, 2013 134 COMMENTS

This prediction sounds bold primarily for the fact that most of us donʹt think about technology – or the history of technology – in century‐long increments: “We’re probably closer to the end of the automobility era than we are to its beginning,” says Maurie Cohen, an associate professor in the Department of Chemistry and Environmental Science at the New Jersey Institute of Te c h n o lo gy. “If we’re 100 years into the automobile era, it seems pretty inconceivable that the car as we know it is going to be around for another 100 years.”

Cohen ﬁgures that we’re unlikely to maintain the deteriorating Interstate Highway System for the next century, or to perpetuate for generations to come the public policies and subsidies that have supported the car up until now. Sitting in the present, automobiles are so embedded in society that it’s hard to envision any future without them. But no technology – no matter how essential it seems in its own era – is ever permanent. Consider, just to borrow some examples from transportation history, the sailboat, the steamship, the canal system, the carriage, and the streetcar.

All of those technologies rose, became ubiquitous, and were eventually replaced. And that process followed a pattern that can tell us much about the future of the automobile – that is, if we’re willing to think about it not in the language of todayʹs ʺwar on cars,ʺ but in the broad arc of time.

“There’s not going to be a cataclysmic moment,” Cohen says of what’s coming for the car. “Like any other technology that outlives its usefulness, it just sort of disappears into the background and we slowly forget about it.” The landline telephone is undergoing that process right now. Your grandmother probably still has one. But did you even bother to call the phone company the last time you moved into a new home? “It’s not as if we all wake up one morning and decide we’re going to get rid of our landlines,” Cohen says, “but they just kind of decay away.

“I think cars will kind of disappear in much the same way.”

They may still exist at the periphery (there are still canal boats out there). But, for the most part, in all likelihood we’ll move on. History is full of these ʺsocio‐technical transitions,ʺ as academics like Cohen call them. The history of the steamship has particularly inﬂuenced this line of thinking. Society spent a good

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hundred years transitioning from the sailing ship to the steamship. “It wasn’t as if steamships instantly demonstrated their superiority,” Cohen says. There were problems with the technology. Kinks had to be worked out. Sometimes they blew up.

We often think of the car as having arrived with a ﬂourish from Henry Ford around the turn of the last century. But the history of the automobile actually dates back more than a hundred years earlier to steam‐powered vehicles and the ﬁrst internal combustion engine. Early prototypes of the car used to blow up, too. People were afraid of them. You had to acquire a special skill set just to operate them. And then there were all the networks we needed to develop – roads, gas stations, repair shops – to make cars feasible.

“We tend to focus on the car itself as the central element,” Cohen says, “and we fail to recognize that it’s not just the car.” Like any ubiquitous technology, the car is embedded in a whole social system. In this case, that system includes fuel supply lines, mechanisms for educating and licensing new drivers, companies to insure them, laws to govern how cars are used on common roads and police oﬃcers to enforce them. In the academic language of socio‐technical transitions theory, all of that stuﬀ is the regime around the car.

“People who are part of that regime get up in the morning, put their shoes on and reproduce that system on a daily basis,” Cohen says. “So that system also has a profound ability to beat back any challenges to it.”

But we can already start to see cracks in the regime. New automobile registrations have plateaued in the U.S, even as the population has continued to grow. Rising gas prices have made some housing patterns predicated on the car unsustainable. Twentysomethings are now less likely to own cars and say they’re less enamored of them. The 1973 classic car ﬂick American Graﬃti, Cohen points out, would never be made today.

Within any social system, there also exist what Cohen calls “insurgent niches” challenging the regime. Niches are fragile, they’re underfunded, they’re stigmatized. The car was once an insurgent niche in the age of streetcars. Now in the age of the automobile, we might think of those niches as car‐sharing companies or bike advocacy groups.

Some niches eventually grow to replace the prevailing regime, as cars themselves once did. But that process is equally dependent on so much more than technological invention. Look at how the cell phone has evolved to replace the landline. Our need for cell phones didn’t arise in a vacuum. Work practices changed. Commuting times got longer, creating the need for communication inside cars. Batteries got smaller. Cell phone towers proliferated.

These are the unnoticed events that happen in the slow course of technological transition. We didn’t even recognize that the car was a fundamentally new thing until around World War I, Cohen says. Until then, many people viewed the car as just a carriage without a horse.

“The replacement of the car is probably out there,” Cohen adds. “We just don’t fully recognize it yet.”

In fact, he predicts, it will probably come from China, which would make for an ironic comeuppance by history. The car was largely developed in America to ﬁt the American landscape, with our wide‐open spaces and brand‐new communities. And then the car was awkwardly grafted onto other places, like dense, old European cities and developing countries. If the car’s replacement comes out of China, it will be designed to ﬁt the particular needs and conditions of China, and then it will spread from there. The result probably won’t work as well in the U.S., Cohen says, in the same way that the car never worked as well in Florence as it did in Detroit.

We’re not terribly well positioned right now to think about what this future will look like. Part of the challenge is that, culturally, we’re much more accustomed to celebrating new gadgets than thinking about how old technology decays.

“An d people don’t have the perspective that extends beyond their own lives,” Cohen says. “They were born into a society and culture where cars were everywhere, and they can’t envision – with good reason – living their lives without a car.”

He worries that in the U.S., we’ve lost our “cultural capacity to envision alternative futures,” to envision the Futurama of the next century. More often, when we do picture the future, it looks either like a reproduced version of the present or like some apocalyptic landscape. But this exercise

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requires a lot more imagination: What will be the next carriage without a horse? The next car without an engine?

The above public‐domain 1736 English Patent Drawing of a Steamboat is courtesy of Wikimedia Commons.

Keywords: Future, Streetcars, history, steamships, Cars

Emily Badger is a staﬀ writer at The Atlantic Cities. Her work has previously appeared in Paciﬁc Standard, GOOD, The Christian Science Monitor, and The New York Tim es. She lives in the Washington, D.C. area. All posts »

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