For Americans living in both cities and the suburbs, the options for working close to home are getting slimmer.
The Brookings Institution, looking at U.S. Census Bureau data from 2000 to 2012 for the country’s largest 96 metropolitan areas, found that the number of jobs within a typical commuting distance for suburban residents dropped by 7 percent. For city residents, the drop was only 3 percent.
The distance between work and home can be more than just a matter of convenience. It can also affect people’s job prospects, wrote Brookings researchers Elizabeth Kneebone and Natalie Holmes. “People who live closer to jobs are more likely to work. They also face shorter job searches and spells of joblessness.”
Overall, the number of jobs in cities decreased by 1.8 percent from 2000 to 2012, while the number of jobs in the suburbs increased by 4.2 percent.
Closeness to workplaces affects people differently. While higher earning workers can afford to drive long distances to work, not everyone can. Being close to jobs affects how long black, female and older workers are unemployed more than other groups. For poor residents, having jobs nearby also increases their chances of working and leaving welfare.
“Proximity matters for lower-income, lower-skill workers in particular because they tend to be more constrained by the cost of housing and commuting. They are more likely to face spatial barriers to employment, thus their job search areas tend to be smaller and commute distances shorter,” the Brookings researchers wrote.
But the number of jobs close to poor neighborhoods and minority communities has dropped significantly faster than in other parts of metropolitan areas.
Poor residents, on average, saw a drop of 17 percent in the number of nearby jobs, compared to 6 percent for people who aren’t poor. While typical white residents in metropolitan areas also saw a 6 percent drop, the decrease for black residents was 14 percent. For Hispanics, the drop was 17 percent.
There is significant overlap between poor neighborhoods and majority-minority neighborhoods. In nearly three-quarters of high-poverty neighborhoods, a majority of residents were members of minorities. More than half of majority-minority neighborhoods had high rates of poverty.
That continues to be true as those groups increasingly move to the suburbs. There are many reasons, other than jobs, that people may relocate there, including affordable housing, better schools or nearby family and friends. The Great Recession also left many suburbanites poor with nowhere else to go.
As a result, a majority of all racial and ethnic groups, as well as the poor, in metropolitan areas now live in the suburbs, rather than the city.
In cities, areas that started off with high poverty or majority-minority populations saw fewer job losses than neighborhoods that became high-poverty or majority minority in the study period. In the suburbs, the opposite was true: Suburban neighborhoods that started the study period with either high poverty or a majority minority population had bigger drops in local jobs than newly established ones.
But even within the suburbs, the story could be more complicated, the Brookings authors said. They pointed to the Chicago and Seattle areas, where inner-ring suburbs fared worse than newer, farther-flung neighborhoods.
For metropolitan areas in general, the availability of nearby jobs varied greatly within regions. In the Atlanta region, for example, the far northeast suburbs gained local jobs, while inner-ring suburbs, most of the city and its far southern suburbs lost nearby places to work.
The Brookings researchers said regional leaders needed to pay more attention to the variation within metropolitan regions on where new jobs were going.
“Simply attracting more jobs or adding population is not enough to guarantee positive outcomes for metropolitan residents or even equal access to economic opportunity,” they wrote. Regional leaders, they said, should focus not just on bringing jobs to the region, but also to where in their region the jobs are going.
“Understanding the shifting map … can help illuminate geographic barriers to employment that may require tailored housing or transportation strategies to overcome,” they wrote.
Metro Area Data
The following table shows Brookings calculations of commutes, defined as the median within-metro-area commute distance.
|Metro name||Typical commute (miles)|
|Atlanta-Sandy Springs-Roswell, GA||12.8|
|Augusta-Richmond County, GA-SC||7.0|
|Austin-Round Rock, TX||8.6|
|Baton Rouge, LA||8.0|
|Boise City, ID||6.0|
|Buffalo-Cheektowaga-Niagara Falls, NY||6.5|
|Cape Coral-Fort Myers, FL||7.3|
|Charleston-North Charleston, SC||8.0|
|Colorado Springs, CO||5.9|
|Dallas-Fort Worth-Arlington, TX||12.2|
|Deltona-Daytona Beach-Ormond Beach, FL||5.9|
|Des Moines-West Des Moines, IA||6.4|
|El Paso, TX||7.0|
|Grand Rapids-Wyoming, MI||7.2|
|Greensboro-High Point, NC||6.9|
|Hartford-West Hartford-East Hartford, CT||7.3|
|Houston-The Woodlands-Sugar Land, TX||12.2|
|Kansas City, MO-KS||8.9|
|Lakeland-Winter Haven, FL||6.9|
|Las Vegas-Henderson-Paradise, NV||7.2|
|Little Rock-North Little Rock-Conway, AR||8.2|
|Los Angeles-Long Beach-Anaheim, CA||8.8|
|Louisville/Jefferson County, KY-IN||7.6|
|Miami-Fort Lauderdale-West Palm Beach, FL||8.6|
|Milwaukee-Waukesha-West Allis, WI||7.4|
|Minneapolis-St. Paul-Bloomington, MN-WI||9.5|
|New Haven-Milford, CT||5.0|
|New Orleans-Metairie, LA||6.2|
|New York-Newark-Jersey City, NY-NJ-PA||7.7|
|North Port-Sarasota-Bradenton, FL||5.9|
|Oklahoma City, OK||8.6|
|Omaha-Council Bluffs, NE-IA||6.0|
|Oxnard-Thousand Oaks-Ventura, CA||5.3|
|Palm Bay-Melbourne-Titusville, FL||6.6|
|Riverside-San Bernardino-Ontario, CA||9.1|
|St. Louis, MO-IL||10.0|
|Salt Lake City, UT||6.5|
|San Antonio-New Braunfels, TX||8.8|
|San Diego-Carlsbad, CA||8.5|
|San Francisco-Oakland-Hayward, CA||8.0|
|San Jose-Sunnyvale-Santa Clara, CA||6.4|
|Spokane-Spokane Valley, WA||5.6|
|Tampa-St. Petersburg-Clearwater, FL||8.5|
|Urban Honolulu, HI||6.6|
|Virginia Beach-Norfolk-Newport News, VA-NC||7.6|
Source: Brookings Institution analysis of 2011 Longitudinal Employer-Household Dynamics data