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          Mega Commuters in the U.S.

    Time and Distance in Defining the Long Commute using the 

                  American Community Survey



                                  Melanie A. Rapino, Ph.D. 

                                   Alison K. Fields, Ph.D. 


                      Journey to Work and Migration Statistics Branch

                      Social, Economic, and Housing Statistics Division

                                United States Census Bureau 




                                   Working Paper 2013-03 


                                        Presented at the 

         Association for Public Policy Analysis and Management Fall 2013 Conference 





Disclaimer: This paper is released to inform interested parties of ongoing research and to
encourage discussion of work in progress. The views expressed on statistical or methodological
issues are those of the authors and not necessarily those of the U.S. Census Bureau.


 
 


Mega Commuters in the U.S.: Time and Distance in Defining the Long Commute using
the American Community Survey

Melanie A. Rapino, Ph.D.
Alison K. Fields, Ph.D.
Journey to Work and Migration Statistics Branch
Social, Economic, and Housing Statistics Branch
United States Census Bureau


Introduction

With a changing employment landscape, some U.S. commuters are travelling long times and
distances to get to work. One study by Moss and Qing (2012) noted that “super” commuters are
on the rise in the U.S. In their analysis, a super commuter is defined as working in the central
county of a metropolitan area, but lives beyond the boundaries of that metropolitan area,
commuting long distances by air, rail, car, bus, or some combination. This is a definition based
on distance. Extreme commuting has been increasing since at least 1990 (see Figure 1).
Extreme commuters are defined as workers who travel 90 minutes or more to work, one-way –
a definition based on time (U.S. Census Bureau, 2005). Additionally, this research defines long-
distance commuters as workers who travel 50 miles or more to work, one-way. And mega
commuters as those who combine these two definitions and travel 90 minutes or more and 50
miles or more to work, one-way.

    Definitions
    Extreme Commuting: Traveling 90 or more minutes to work.
    Long-distance Commuting: Traveling 50 or more miles to work.
    Mega Commuting: Traveling 90 or more minutes and 50 or more miles to work.


This analysis evaluates the national, county-level, and metropolitan area patterns of “mega”
commuting, examining time and distance, first, independently, and then jointly. We analyze
commutes determining the county-to-county flow pairs with the highest average distance and
time; noting counties with the highest distance traveled, and extremes in inflow and outflow. We
mapped the mega commutes by counties and metropolitan areas and examine these measures
in relationship to travel mode choice, in the presence of demographic characteristics such as,
age, marital status, presence of children, wages, gender, and occupation. Additionally, using the
study area of Washington, D.C., we compare mega commuters to other commuters and their
national counterparts. Washingtonian commuters report some of the longest commute times in
the U.S. and have a variety of transportation modes from which to choose. These results will
better inform how to define these commutes with respect to both time and distance.




                                                                                                1 
 
 


Figure1: Percent of Workers with Commute Times of 90 Minutes or More, 1990-2011


                          Percent of Workers with Commute Times of                     
                                      90 Minutes or More
               3.0%
               2.5%
               2.0%
               1.5%
               1.0%
               0.5%
               0.0%
                       1990        2000        2006 2007 2008 2009 2010 2011
                      Census      Census       ACS ACS ACS ACS ACS ACS


Source: U.S. Census Bureau, 1990 Census, Census 2000, 2006 ACS, 2007, 2008 ACS, 2009 ACS, 2010
ACS, 2011 ACS.


Research Questions
    What are the geographic patterns and distribution of mega commuters?
    What are the transportation and socio-economic characteristics of mega commuters in
      comparison to other commuters?
    How do commuters into the District of Columbia compare to commuters across the
      U.S.?


Data and Methodology

The American Community Survey (ACS) is a nationwide survey designed to provide
communities with reliable and timely demographic, social, economic, and housing data for the
nation, states, congressional districts, counties, places, and other localities every year. It had a
2011 sample size of about 3.3 million addresses across the United States and Puerto Rico and
includes both housing units and group quarters (e.g.,nursing facilities and prisons). The ACS is
conducted in every county throughout the nation and every municipio in Puerto Rico, where it is
called the Puerto Rico Community Survey. Beginning in 2006, ACS data for 2005 were released
for geographic areas with populations of 65,000 and greater. For information on the ACS
sample design and other topics, visit <www.census.gov/acs/www>.

This research utilizes the 2006-2010 5-year ACS. The 5-year ACS estimates contain 60
months of collected data, which allows for a larger sample size and more reliable, precise, but
less current, estimates than the 1-year and 3-year datasets. For this research, the 5-year
dataset was advantageous to examine such a small sect of the population at geographies below
the national or state level.

The ACS questions related to daily travel patterns focus solely on commuting and do not ask
about leisure travel or other non-work trips. Respondents answer questions about where they
live, where they work, what time they leave home for work, the means of transportation used to


                                                                                                   2 
 
 


get there, the number of workers riding in a car, truck, or van, and how long, in minutes, it takes
to travel to work (see ACS transportation-related questions on associated poster). The full
addresses of a worker’s residence and workplace are collected in the survey. They are each
geocoded to the place-level, and the block-level where possible.

We use both travel time and distance to analyze commuting patterns for full-time workers in the
U.S., where full-time workers have been defined as those who reported working 50 or more
weeks a year and 35 or more hours per week. We obtain travel time from reported values on
the ACS (see Question #33). The ACS does not ask about travel distance to work. To estimate
travel distance, we utilize geocoded residence and place of work information from the 2006-
2010 5-year ACS to calculate the Census block centroid -to-Census block centroid distance
variable for each individual home-to-work flow pair based on Euclidean distance (i.e., “as the
crow flies”) (see Equation 1). In order to account for the transportation network effect, the travel
distance obtained from Equation 1 is multiplied by a constant of 1.25 (see Equation 2).

From here, we delineate workers who commute 90 minutes or more and 50 miles or more as
“mega” commuters, workers who commute 90 minutes or more as “extreme,” and workers who
commute 50 miles or more as “long-distance” (see Definitions box above).


    Equation 1
    Straight Line Distance = 3949.99 * arcos(sin(LAT_res) * sin(LAT_pow) + cos(LAT_res) *
    cos(LAT_pow) * cos(LONG_pow - LONG_res))

    where, LAT_res is the latitude of the centroid of the residential block of each commuter, LAT_pow is
    the latitude of the centroid of the place of work census block of each commuter, LONG_res is the
    longitude of the centroid of the place of residence of each commuter, and LONG_pow is the longitude
    of the centroid of the place of work of each commuter.


    Equation 2
    Inflated Distance = Straight Line Distance * 1.25

    where, Straight Line Distance is defined in Equation 1 and 1.25 is a constant (Sparks et al., 2011).



Findings and Discussion

Of all reported commutes in the U.S. for full-time workers, approximately 5% are considered to
be “long”, while 95% make up other commutes. Of the long commutes, about 2.41% or
1,713,931 can be categorized as extreme, 3.15% or 2,241,915 as long-distance, and 0.82% or
586,805 as mega.

This research has shown that in the U.S.:

       o	 Mega commuters are more likely to depart for work before 6 am, be male, older,
          married, make a higher salary, and have a spouse that does not work (see Appendix
          Table 1).1
                                                            
1
  Statistically significant at the 90 percent confidence level for full-time working U.S. commuters versus
their mega counterparts.

                                                                                                             3 
 
 


       o	 Mega commuters are more likely to travel to another metro or micro area for work, as
          opposed to the one in which they reside.2
       o	 Mega receiving flows are geographically concentrated in populous cities, while sending
          flows are more geographically dispersed (see ‘Mega Commuting Flows: Top Sending
          and Receiving Counties’ map).


Table 1: Percent Mega Commutes for Metro Areas with the Highest Mean Travel Time for Full-
time Working Commuters3
                                                                                   Percent Mega
                                   Metro Areas with the Highest Mean Travel Time
                                                                                    Commutes
                            San Francisco-Oakland-Fremont, CA                          2.06
                            New York-Northern New Jersey-Long Island, NY-NJ-PA         1.90
                            Washington-Arlington-Alexandria, DC-VA-MD-WV               1.89
                            Trenton-Ewing NJ Metropolitan Statistical Area             1.40
                            Los Angeles-Long Beach-Santa Ana, CA                       1.25
                            Boston-Cambridge-Quincy, MA-NH                             1.17
                            Atlanta-Sandy Springs-Marietta, GA                         0.90
                            Chicago-Joliet-Naperville, IL-IN-WI                        0.81
                            Philadelphia-Camden-Wilmington, PA-NJ-DE-MD                0.80
                            Seattle-Tacoma-Bellevue, WA                                0.57


Table 2: Percent Mega Commutes for Metro Areas with the Highest Mean Distance for Full-time
Working Commuters4
                                                                                   Percent Mega
                                         Metro Areas with Highest Mean Distance
                                                                                    Commutes
                            San Francisco-Oakland-Fremont, CA                          2.06
                            San Jose-Sunnyvale-Santa Clara, CA                         1.90
                            Salinas, CA	                                               1.23
                            Gulfport-Biloxi, MS                                        0.94
                            Hinesville-Fort Stewart, GA                                0.93
                            Lawton, OK 	                                               0.82
                            Fayetteville, NC                                           0.73
                            Brunswick, GA                                              0.64
                            Anchorage, AK                                              0.25
                            Honolulu, HI                                               0.08
                                                            
2
  Statistically significant at the 90 percent confidence level for full-time working U.S. commuters versus
their mega counterparts.
3
 Not all metro areas on this list have statistically different mean travel times from those ranked lower.
San Francisco, CA, Boston, MA. and, Seattle, WA metro areas have percent mega commuters that are
statistically different from all other metro areas on the list at the 90 percent confidence level but not
necessarily from metro areas excluded from the list.
4
  Anchorage, AK and Honolulu, HI have statistically different mean distances from other metro areas at
the 90 percent confidence level, but not from each other. None of the metro areas on the list have percent
mega commuters that is statistically different from all other metro areas on the list.
 

                                                                                                             4 
 
 


Geographic Dispersions

The map of the percent of mega commuters by metro area shows a dispersion across the U.S.
with the biggest clusters located in major metro areas on the east and west coasts such as New
York, NY, Washington, D.C., San Francisco, CA, and Los Angeles, CA. Interestingly, there are
two additional clusters in the New Orleans, LA and Houma, LA areas as well as the Santa Fe,
NM and Farmington, NM. Included in the Appendix is a tabulation of place of work metropolitan
statistical areas with the estimated number of mega commuters, estimated margin of error,
percent of mega commuters, and percent margin of error (see Appendix Table 2).

Of note,
    o	 San Bernadino Co., CA to Los Angeles Co., CA and Fairfield Co., CT to New York Co.,
       NY flows have flow counts that are statistically larger than other mega commuter flows at
       the 90 percent confidence level (see Table 3).

    o	 The flow from San Bernadino Co., CA to Los Angeles Co., CA has a mean travel time
       and mean distance that is statistically larger than other mega commuter flows at the 90
       percent confidence level (see Table 3).


Table 3: Mean Travel Time and Mean Distance for the Most Frequent Mega Commuter Flows
Top 10 Mega County Commuter Flows by Frequency
                                                                         Mean Travel    Mean
State          County                  POW State POW County
                                                                            Time       Distance
California     San Bernardino County   California   Los Angeles County      104.2        68.0
California     Riverside County        California   Los Angeles County      109.3        77.4
New York       Suffolk County          New York     New York County         114.2        64.5
Connecticut    Fairfield County        New York     New York County         104.2        60.4
New York       Orange County           New York     New York County         110.7        62.3
New Jersey     Mercer County           New York     New York County         104.6        59.3
California     Riverside County        California   San Diego County        102.3        75.5
New York       Dutchess County         New York     New York County         116.8        76.3
California     San Joaquin County      California   Alameda County          104.1        61.5
Pennsylvania   Monroe County           New York     New York County         120.5        91.1




                                                                                                  5 
 
 


Focus: Washington, D.C.

Washington, D.C. is located in the Mid-Atlantic region of the U.S. It is an ideal area to further
examine long commuting patterns because respondents have consistently reported long
commutes in terms of time and it has a variety of transportation modes. According to a U.S.
Census Bureau report, more than a quarter (27.4 percent) of District of Columbia workers
traveled 60 minutes or longer to get to work, notably higher than that of any other state
(McKenzie 2013). Additionally, Washington, D.C. has a large geographic commuting shed due
to the consistent and stable job opportunities located in the metro area and its distinct role as
our nation’s capital.

This research has shown that in the District of Columbia:
   o	 D.C. mega commuters have different characteristics from D.C. commuters as a whole,
       as well as their U.S. counterparts.
   o	 In terms of place of work state, the highest percent of mega commuters work in D.C.5
       (2.15%)
   o	 In terms of place of work county, D.C. has the 4th highest number of receiving mega
       commuters.6
   o	 For place of residence state, D.C. mega commuters have among the highest average
       distance and time.7
   o	 Highest mean travel time for place of work CBSA (along with the NYC metro area) for all
       full-time working commuters.8

The map of the mega commuter flows into D.C. shows a ring around the District of Columbia
encompassing counties in Maryland, Pennsylvania, Virginia, West Virginia, and New Jersey.
These flows contain at least 3 unweighted cases. Counties among the top five county mega
commuter flows into the District of Columbia in terms of commuter frequency are: Spotsylvania
Co., VA, Frederick Co., MD, Baltimore Co., MD, Stafford Co, VA, and Berkeley Co., WV (see
Table 4).9 Each of these flows have relatively high proportions of carpooling and public
transportation usage but each county varies on the percent of mega commuters by means of
transportation.




                                                            
5
    Statistically different from other place of work states at the 90 percent confidence level. 

6
    Statistically different from other place of work counties at the 90 percent confidence level. 

7
    Not statistically different from all other place of residence states for mega commuters.

8
  Statistically different from other place of work CBSAs at the 90 percent confidence limit, except for the 

New York-New York-Northern New Jersey-Long Island, NY-NJ-PA metropolitan statistical area. 

 
9
  The number of mega commuters from Spotsylvania County, VA into Washington, DC is statistically 

different at the 90 percent confidence level from other county flows into Washington, DC.



                                                                                                                6 
 
 


Table 4: Percent Mega Commuters and Percent of Mode Share for the Most Frequent Mega
Commuter Flows into Washington, D.C. by County
Top 5 Mega Commuter County Flows into DC by Means of Transportation
                                                                    Percent   Percent of
       State             County            Mode of Transportation
                                                                     Mega     Mode Share
                                          Drove alone                  51.2      24.7
      Virginia      Spotsylvania County   Carpooled                    38.5      28.1
                                          Public Transportation        84.0      47.2
                                          Drove alone                  21.8      35.3
     Maryland        Frederick County     Carpooled                    30.3      14.7
                                          Public Transportation        49.3      50.0
                                          Drove alone                  18.5      43.1
     Maryland        Baltimore County     Carpooled                    15.8      5.9
                                          Public Transportation        27.1      51.0
                                          Drove alone                  14.0      32.7
      Virginia        Stafford County     Carpooled                    9.2       24.5
                                          Public Transportation        39.6      42.9
                                          Drove alone                  73.7      35.9
    West Virginia    Berkeley County      Carpooled                   100.0      10.3
                                          Public Transportation       100.0      53.8




Concluding Thoughts
Further research is needed to better understand whether mega commuting is a choice or a
necessity for workers. Mega commuters may choose to commute to an onsite location part of
the week and work from home other days (see Mateyka, Rapino, and Landivar 2012). Or, mega
commuters may be a result of the changing employment landscape, meaning workers have to
travel further and longer to existing job opportunities.




                                                                                           7 
 
 


References

Mateyka, P. J., Rapino, M. A., and L. C. Landivar, 2012. “Home-based Workers in the United
States: 2010,” Household Economic Studies, U.S. Census Bureau, P70-132, October.

McKenzie, B. 2013. “Out of State and Long Commutes: 2011,” American Community Survey
Reports, U.S. Census Bureau, ACS-20, February.

Moss, M. L. and C. Qing, 2012. “The Emergence of the Super-Commuter,” Rudin Center for
Rudin Center for Transportation, New York University Wagner School of Public Service,
February.

Sparks, A. L., Bania, N., and L. Leete, 2011. “Comparative Approaches to Measuring Food
Access in Urban Areas: The Case of Portland, Oregon,” Urban Studies 48: 1715-1737.

U.S. Census Bureau, 2005. “Extreme Commute Rankings,”
(http://www.census.gov/newsroom/releases/pdf/2005-03-30_Commute_extremes.pdf

U.S. Census Bureau. 2006-2010 5-year American Community Survey.




                                                                                             8 
 
Appendix Table 1: Selected Characteristics of Mega Commuters and all other Commuters in the U.S. and Washington, D.C., 2006-2010
                                             U.S. Commuters               U.S. Mega Commuters               D.C. Commuters                D.C. Mega Commuters
                                                  Margin of                      Margin of                       Margin of                       Margin of
Selected Characteristics                   Total Error (+/-) Percent       Total Error (+/-) Percent       Total Error (+/-) Percent       Total Error (+/-) Percent
Means of Transportation
Drove alone                           58,315,022    97,304      81.9    400,833     4,810       68.3     229221      3671       44.9      4,338        466      39.4
Carpooled                              6,750,149    32,414       9.5     83,796     2,231       14.3      58476      1744       11.5      2,176        354      19.8
Public Transportation                  3,552,815    13,564       5.0     66,278     1,648       11.3     190174      2665       37.3      3,971        463      36.1
Other means                            2,584,759    14,365       3.6     35,898     1,268        6.1      32529      1113        6.4        519        135       4.7
Occupation
Management, business science,
and arts occupations                  28,989,151   142,284      40.7    263,965     3,822       45.0     335692      4344       65.8      7,580        625      68.9
Service occupations                    8,919,159    41,131      12.5     42,353     1,333        7.2      56169      2092       11.0        898        196       8.2
Sales and office occupations          18,069,960    34,170      25.4     98,276     2,268       16.7      83388      2020       16.3      1,383        287      12.6
Production, transportation, and
material moving occupations            8,701,910    22,875      12.2     86,361     1,611       14.7      15801      1058        3.1        277        102       2.5
Natural resources, construction and
maintenance occupations                6,183,227    16,461       8.7     92,540     2,322       15.8      16204       899        3.2        805        184       7.3
Military specific occupations            339,338     5,874       0.5      3,310       446        0.6       3146       360        0.6         61         44       0.6
Wages/Salary Income
Less than $40,000                     34,347,772    67,963      48.2    145,402     2,824       24.8     109303      2236       21.4       1,045        213      9.5
$40,000 to $79,999                    25,610,475   101,434      36.0    251,488     3,605       42.9     189213      3262       37.1       3,887        455     35.3
$80,000 or more                       11,244,498    78,129      15.8    189,915     3,183       32.4     211884      3334       41.5       6,072        555     55.2
Mean ($)                               52,676.00    139.10         -   75,414.00   606.70          -   84,863.00   872.00          -   91,346.00   3,665.00        -
Age
Less than or equal to 29              12,859,005    25,391      18.1     61,968     2,176       10.6      82117      1834       16.1        996        266       9.1
30-64                                 56,509,820   107,185      79.4    510,966     5,511       87.1     413126      4816       80.9      9,627        844      87.5
65 and Over                            1,833,920     8,418       2.6     13,871       600        2.4      15157       745        3.0        381        136       3.5
Mean (years)                                42.5        0.0        -       44.5        0.1         -        42.9       0.1         -       45.3         0.7        -
Class of Worker
Government workers                    12,066,821    68,012      16.9     92,177     2,507       15.7     209027      3402       41.0      5,511        595      50.1
Private wage and salary workers       53,957,906    58,454      75.8    459,881     4,529       78.4     282703      3549       55.4      5,257        514      47.8
Self-employed workers                  5,119,985    18,034       7.2     34,530     1,296        5.9      18483       975        3.6        236         91       2.1
Appendix Table 1: Selected Characteristics of Mega Commuters and all other Commuters in the U.S. and Washington, D.C., 2006-2010
                                         U.S. Commuters               U.S. Mega Commuters               D.C. Commuters                D.C. Mega Commuters
                                              Margin of                      Margin of                       Margin of                       Margin of
Selected Characteristics               Total Error (+/-) Percent       Total Error (+/-) Percent       Total Error (+/-) Percent       Total Error (+/-) Percent
Unpaid family workers                58,033      1,802       0.1        217        111       0.0        187        118       0.0          0          -       0.0
Sex
Female                            31,024,200    33,915      43.6    144,375      2,696      24.6     246806       3653      48.4      3,767       478       34.2
Male                              40,178,545   102,588      56.4    442,430      5,182      75.4     263594       3229      51.6      7,237       556       65.8
Marital Status
Married                           42,923,445   287,624      60.3    420,181      5,194      71.6     270708       3980      53.0      8,190       653       74.4
Other                             28,279,300   177,399      39.7    166,624      3,117      28.4     239692       3552      47.0      2,814       382       25.6
Presence of Children
Children under 6 only              6,983,308    74,083       9.8     57,706      1,823       9.8      50009       1788       9.8      1,398       277       12.7
Children 6-17 only                17,522,961    95,370      24.7    162,837      3,210      27.8     102586       2524      20.1      2,836       398       25.8
Children under 6 and 6-17 years    6,099,072    23,549       8.6     60,446      1,888      10.3      33103       1404       6.5        892       220        8.1
No children present               40,382,670    70,855      56.9    305,445      3,974      52.1     323797       3673      63.6      5,878       522       53.4
Property Value
Mean ($)                          123,894.97    423.40         - 160,590.79    2,416.47        - 214,567.86    3,965.41        - 200,489.36 17,961.08          -
Number of Bedrooms
Mean                                     3.0       0.0         -         3.2        0.0        -         3.0        0.0        -         3.4       0.1         -
Property Value/Bedrooms ($)        41,298.32         -         -   50,184.62          -        -   71,522.62          -        -   58,967.46         -         -
Number of Vehicles Available
Mean                                     2.2       0.0         -         2.4        0.0        -         1.8        0.0        -         2.3       0.1         -
Time of Departure
12:00 to 5:59 am                   9,461,218    22,878      13.3    247,926      3,444      42.3      73681       1909      14.4      6,786       675       61.7
6:00 to 8:59 am                   49,149,190   145,045      69.0    260,230      4,114      44.3     361594       4205      70.8      3,751       375       34.1
9:00 to 11:59 am                   5,748,363    24,371       8.1     26,476      1,064       4.5      46404       1652       9.1        162        69        1.5
12:00 to 3:59 pm                   3,456,332    17,074       4.9     23,919        950       4.1      14844        897       2.9         76        47        0.7
4:00 to 11:59 pm                   3,387,642    13,545       4.8     28,254      1,173       4.8      13877        830       2.7        229        95        2.1
Travel Time
Mean (minutes)                          26.1       0.0         -      119.0         0.3        -        42.5        0.3        -      118.6        1.7         -
Distance to Work1
Appendix Table 1: Selected Characteristics of Mega Commuters and all other Commuters in the U.S. and Washington, D.C., 2006-2010
                                         U.S. Commuters                 U.S. Mega Commuters              D.C. Commuters            D.C. Mega Commuters
                                              Margin of                        Margin of                      Margin of                   Margin of
Selected Characteristics               Total Error (+/-) Percent         Total Error (+/-) Percent     Total Error (+/-) Percent    Total Error (+/-) Percent
Mean (miles)                               18.8         0.1         -    166.4      3.0          -     26.3        1.3         -   102.6        8.9         -
Work Status of Spouse in Family Households
Spouse works full-time              22,986,397    183,745       32.3  182,155     3,091       31.0   153259      3023       30.0   3,828       435       34.8
Spouse works part-time               6,274,525     76,275        8.8    72,935    1,950       12.4    36365      1321        7.1   1,485       262       13.5
Spouse does not work                 7,685,184     40,825       10.8  108,599     2,273       18.5    44790      1374        8.8   1,990       261       18.1
No spouse present                    8,516,945     53,733       12.0    48,602    1,653        8.3    62291      1878       12.2     842       203        7.7
Not Applicable                      25,739,694    134,976       36.1  174,514     2,942       29.7   213695      3666       41.9   2,859       379       26.0
Metro/Micro Status
Living in Metro/Micro Statistical
Area, working in Metro/Micro
Statistical Area of residence       64,206,838    102,010       90.2  182,123     3,187       31.0
Living in Metro/Micro Statistical
Area, working in different
Metro/Micro Statistical Area         4,342,853     18,673        6.1  338,985     4,349       57.8
Living in Metro/Micro Statistical
Area, working outside any
Metro/Micro Statistical Area           216,561       2,977       0.3     5,789      454        1.0
Living outside any Metro/Micro
Statistical Area, working in a
Metro/Micro Statistical Area           904,991       5,926       1.3    57,847    1,625        9.9
Living and working outside any
Metro/Micro Statistical Area         1,531,502     10,354        2.2     2,061      269        0.4
Source: U.S. Census Bureau, 2006-2010 5-year American Community Survey.
1/ Calculated by authors. See methodology in Working Paper 2013-13.
Appendix Table 2: Mega Commuters by Place of Work Metropolitan Statisical Area, 2006-
2010
                                                        Margin of             Margin of
Metropolitan Statistical Area                Estimate       Error   Percent       Error
Abilene, TX                                       202        118        0.5         0.3
Akron, OH                                       1,586        360        0.8         0.2
Albany, GA                                        506        235        1.5         0.7
Albany-Schenectady-Troy, NY                     2,954        426        1.2         0.2
Albuquerque, NM                                 1,508        455        0.7         0.2
Alexandria, LA                                    638        257        1.7         0.7
Allentown-Bethlehem-Easton, PA-NJ               2,516        528        1.4         0.3
Altoona, PA                                       194        101        0.7         0.3
Amarillo, TX                                      246        109        0.4         0.2
Ames, IA                                          342        125        1.5         0.5
Anchorage, AK                                     498        178        0.5         0.2
Anderson, IN                                      126         95        0.5         0.4
Anderson, SC                                      190        156        0.6         0.5
Ann Arbor, MI                                   1,174        262        1.1         0.2
Anniston-Oxford, AL                               362        185        1.3         0.6
Appleton, WI                                      648        229        1.1         0.4
Asheville, NC                                     562        209        0.6         0.2
Athens-Clarke County, GA                          602        272        1.5         0.7
Atlanta-Sandy Springs-Marietta, GA             22,770      1,302        1.8         0.1
Atlantic City-Hammonton, NJ                     1,958        372        2.8         0.5
Auburn-Opelika, AL                                416        257        1.8         1.1
Augusta-Richmond County, GA-SC                  1,178        458        1.0         0.4
Austin-Round Rock-San Marcos, TX                4,860        770        1.1         0.2
Bakersfield-Delano, CA                          2,758        574        1.9         0.4
Baltimore-Towson, MD                           13,774      1,284        1.8         0.2
Bangor, ME                                        650        199        1.8         0.6
Barnstable Town, MA                               448        193        1.0         0.4
Baton Rouge, LA                                 4,638        737        2.6         0.4
Battle Creek, MI                                  394        182        1.1         0.5
Bay City, MI                                      270        102        1.4         0.5
Beaumont-Port Arthur, TX                        1,834        518        2.4         0.7
Bellingham, WA                                    228        122        0.6         0.3
Bend, OR                                          140        107        0.6         0.5
Billings, MT                                      536        262        1.2         0.6
Binghamton, NY                                    340        155        0.6         0.3
Birmingham-Hoover, AL                           4,378        768        1.6         0.3
Bismarck, ND                                      174        107        0.5         0.3
Blacksburg-Christiansburg-Radford, VA             232        142        0.7         0.4
Bloomington, IN                                   622        294        1.6         0.8
Bloomington-Normal, IL                            898        221        1.8         0.4
Boise City-Nampa, ID                              746        281        0.5         0.2
Boston-Cambridge-Quincy, MA-NH                 30,042      1,751        2.2         0.1
Boulder, CO                                       416        212        0.5         0.3
Bowling Green, KY                                544
     268    1.6   0.8
Bremerton-Silverdale, WA                         394
     159    0.7   0.3
Bridgeport-Stamford-Norwalk, CT                6,718
     928    2.6   0.4
Brownsville-Harlingen, TX                        142
     125    0.2   0.2
Brunswick, GA                                    190
     150    1.3   1.0
Buffalo-Niagara Falls, NY                      1,360
     253    0.5   0.1
Burlington, NC                                   214
     150    0.7   0.5
Burlington-South Burlington, VT                  842
     249    1.3   0.4
Canton-Massillon, OH                             422
     168    0.5   0.2
Cape Coral-Fort Myers, FL                        558
     204    0.5   0.2
Cape Girardeau-Jackson, MO-IL                    416
     226    1.7   0.9
Carson City, NV                                   68
      73    0.3   0.4
Casper, WY                                       458
     239    2.0   1.0
Cedar Rapids, IA                               1,022
     257    1.3   0.3
Champaign-Urbana, IL                             614
     222    1.0   0.4
Charleston, WV                                 1,882
     439    2.9   0.7
Charleston-North Charleston-Summerville, SC    2,052
     479    1.2   0.3
Charlotte-Gastonia-Rock Hill, NC-SC            6,936
     925    1.4   0.2
Charlottesville, VA                              860
     264    1.8   0.5
Chattanooga, TN-GA                             1,926
     467    1.5   0.4
Cheyenne, WY                                     544
     281    1.9   1.0
Chicago-Joliet-Naperville, IL-IN-WI           40,096
   1,970	   1.6   0.1
Chico, CA                                        642
     280    1.7   0.7
Cincinnati-Middletown, OH-KY-IN                5,968
     676    1.0   0.1
Clarksville, TN-KY                               596
     248    0.9   0.4
Cleveland, TN                                     76
      74    0.4   0.4
Cleveland-Elyria-Mentor, OH                    5,180
     604    0.9   0.1
Coeur d'Alene, ID                                104
      68    0.4   0.2
College Station-Bryan, TX                      1,024
     334    2.3   0.7
Colorado Springs, CO                           1,544
     372    0.9   0.2
Columbia, MO                                     528
     180    1.1   0.4
Columbia, SC                                   3,126
     603    1.6   0.3
Columbus, GA-AL                                  930
     273    1.3   0.4
Columbus, IN                                     282
     177    1.2   0.7
Columbus, OH                                  10,620
     911    2.0   0.2
Corpus Christi, TX                             1,528
     451    1.6   0.5
Corvallis, OR                                    254
     156    1.4   0.9
Crestview-Fort Walton Beach-Destin, FL           704
     252    1.2   0.4
Cumberland, MD-WV                                182
     150    1.0   0.8
Dallas-Fort Worth-Arlington, TX               24,102
   1,390	   1.4   0.1
Dalton, GA                                       386
     213    0.9   0.5
Danville, IL                                     146
      78    0.8   0.4
Danville, VA                                     338
     348    1.9   2.0
Davenport-Moline-Rock Island, IA-IL              746
     267    0.7   0.3
Dayton, OH                                     1,694
     393    0.8   0.2
Decatur, AL                                      222
     172    0.7   0.5
Decatur, IL                                      202
     103    0.6   0.3
Deltona-Daytona Beach-Ormond Beach, FL    1,210
     394   1.2   0.4
Denver-Aurora-Broomfield, CO              6,370
     684   0.9   0.1
Des Moines-West Des Moines, IA            2,528
     421   1.4   0.2
Detroit-Warren-Livonia, MI               14,186
   1,116   1.4   0.1
Dothan, AL                                  206
     118   0.7   0.4
Dover, DE                                   346
     170   1.0   0.5
Dubuque, IA                                 426
     182   1.4   0.6
Duluth, MN-WI                             1,074
     204   1.6   0.3
Durham-Chapel Hill, NC                    1,644
     418   1.2   0.3
Eau Claire, WI                              560
     155   1.4   0.4
El Centro, CA                               756
     267   3.4   1.2
El Paso, TX                                 508
     212   0.3   0.1
Elizabethtown, KY                           336
     174   1.0   0.5
Elkhart-Goshen, IN                          594
     221   1.0   0.4
Elmira, NY                                  104
      60   0.5   0.3
Erie, PA                                    454
     183   0.6   0.3
Eugene-Springfield, OR                      574
     219   0.8   0.3
Evansville, IN-KY                           784
     216   0.8   0.2
Fairbanks, AK                                94
      90   0.4   0.4
Fargo, ND-MN                                648
     140   1.0   0.2
Farmington, NM                              616
     168   3.3   0.9
Fayetteville, NC                          1,398
     495   1.4   0.5
Fayetteville-Springdale-Rogers, AR-MO     1,288
     324   1.1   0.3
Flagstaff, AZ                               490
     235   2.0   0.9
Flint, MI                                   764
     198   1.0   0.2
Florence, SC                                774
     261   1.5   0.5
Florence-Muscle Shoals, AL                  134
      92   0.5   0.3
Fond du Lac, WI                             232
     112   1.0   0.5
Fort Collins-Loveland, CO                   292
     132   0.4   0.2
Fort Smith, AR-OK                           586
     223   1.0   0.4
Fort Wayne, IN                            1,210
     313   1.0   0.3
Fresno, CA                                1,984
     393   1.2   0.2
Gadsden, AL                                 142
      93   0.7   0.4
Gainesville, FL                           1,092
     413   1.9   0.7
Gainesville, GA                             602
     262   1.6   0.7
Glens Falls, NY                             220
     124   0.9   0.5
Goldsboro, NC                               218
     133   0.8   0.5
Grand Forks, ND-MN                          240
     123   0.9   0.5
Grand Junction, CO                          414
     248   1.2   0.7
Grand Rapids-Wyoming, MI                  2,768
     472   1.3   0.2
Great Falls, MT                             162
      85   0.7   0.4
Greeley, CO                                 668
     342   1.5   0.8
Green Bay, WI                               866
     204   0.9   0.2
Greensboro-High Point, NC                 2,690
     542   1.3   0.3
Greenville, NC                              266
     136   0.7   0.4
Greenville-Mauldin-Easley, SC             2,038
     498   1.3   0.3
Gulfport-Biloxi, MS                       1,270
     346   1.9   0.5
Hagerstown-Martinsburg, MD-WV                 916     273   1.9   0.6
Hanford-Corcoran, CA                          234     148   1.1   0.7
Harrisburg-Carlisle, PA                     3,932     570   2.1   0.3
Harrisonburg, VA                              416     238   1.4   0.8
Hartford-West Hartford-East Hartford, CT    3,306     526   0.9   0.1
Hattiesburg, MS                               826     321   2.5   1.0
Hickory-Lenoir-Morganton, NC                  750     234   0.9   0.3
Hinesville-Fort Stewart, GA                   140     166   1.9   2.1
Holland-Grand Haven, MI                       320     147   0.5   0.3
Honolulu, HI                                  440     179   0.2   0.1
Hot Springs, AR                               150     125   0.7   0.6
Houma-Bayou Cane-Thibodaux, LA              2,752     488   5.9   1.0
Houston-Sugar Land-Baytown, TX             22,328   1,531   1.5   0.1
Huntington-Ashland, WV-KY-OH                  558     267   0.9   0.4
Huntsville, AL                              1,174     242   1.0   0.2
Idaho Falls, ID                               252     114   0.9   0.4
Indianapolis-Carmel, IN                     8,442     844   1.7   0.2
Iowa City, IA                                 460     183   1.1   0.4
Ithaca, NY                                    260     120   1.0   0.5
Jackson, MI                                   258     151   0.8   0.4
Jackson, MS                                 3,060     566   2.2   0.4
Jackson, TN                                   476     200   1.3   0.5
Jacksonville, FL                            4,464     771   1.3   0.2
Jacksonville, NC                              360     164   0.7   0.3
Janesville, WI                                218     116   0.7   0.4
Jefferson City, MO                            854     298   2.0   0.7
Johnson City, TN                              288     173   0.9   0.5
Johnstown, PA                                 214     113   0.7   0.4
Jonesboro, AR                                 204     127   0.8   0.5
Joplin, MO                                    698     254   1.6   0.6
Kalamazoo-Portage, MI                         488     168   0.6   0.2
Kankakee-Bradley, IL                          310     167   1.3   0.7
Kansas City, MO-KS                          6,398     672   1.1   0.1
Kennewick-Pasco-Richland, WA                  792     341   1.5   0.6
Killeen-Temple-Fort Hood, TX                  788     245   0.7   0.2
Kingsport-Bristol-Bristol, TN-VA              364     208   0.6   0.3
Kingston, NY                                  358     151   1.3   0.5
Knoxville, TN                               2,042     485   1.1   0.3
Kokomo, IN                                    554     255   2.3   1.0
La Crosse, WI-MN                              378     130   1.0   0.3
Lafayette, IN                                 708     238   1.4   0.5
Lafayette, LA                               2,632     488   3.4   0.6
Lake Charles, LA                              810     314   1.8   0.7
Lake Havasu City-Kingman, AZ                  448     202   1.4   0.6
Lakeland-Winter Haven, FL                   1,728     408   1.5   0.4
Lancaster, PA                                 986     316   0.8   0.2
Lansing-East Lansing, MI                    1,882     272   1.7   0.2
Laredo, TX                                      724
     389    1.7   0.9
Las Cruces, NM                                  304
     138    0.8   0.4
Las Vegas-Paradise, NV                        4,376
     709    0.8   0.1
Lawrence, KS                                     74
     108    0.3   0.4
Lawton, OK                                      446
     149    1.5   0.5
Lebanon, PA                                     364
     136    1.4   0.5
Lewiston, ID-WA                                  94
      76    0.8   0.6
Lewiston-Auburn, ME                             298
     156    1.0   0.5
Lexington-Fayette, KY                         2,918
     554    2.0   0.4
Lima, OH                                        450
     219    1.5   0.7
Lincoln, NE                                     744
     167    0.8   0.2
Little Rock-North Little Rock-Conway, AR      3,230
     442    1.6   0.2
Logan, UT-ID                                    152
     146    0.7   0.7
Longview, TX                                    430
     148    0.9   0.3
Longview, WA                                    238
     134    1.5   0.8
Los Angeles-Long Beach-Santa Ana, CA         75,800
   2,693	   2.5   0.1
Louisville/Jefferson County, KY-IN            4,450
     644    1.3   0.2
Lubbock, TX                                     416
     236    0.6   0.3
Lynchburg, VA                                   636
     296    1.1   0.5
Macon, GA                                       522
     194    1.0   0.4
Madera-Chowchilla, CA                           220
     139    1.0   0.7
Madison, WI                                   3,106
     439    1.7   0.2
Manchester-Nashua, NH                         1,408
     351    1.3   0.3
Manhattan, KS                                   536
     191    1.6   0.6
Mankato-North Mankato, MN                       114
      84    0.6   0.4
Mansfield, OH                                   284
     157    0.9   0.5
McAllen-Edinburg-Mission, TX                    336
     223    0.3   0.2
Medford, OR                                     182
     131    0.4   0.3
Memphis, TN-MS-AR                             5,782
     648    1.7   0.2
Merced, CA                                      404
     194    1.1   0.5
Miami-Fort Lauderdale-Pompano Beach, FL      15,486
   1,464    1.1   0.1
Michigan City-La Porte, IN                      110
      86    0.5   0.4
Midland, TX                                     520
     192    1.2   0.5
Milwaukee-Waukesha-West Allis, WI             5,310
     657    1.2   0.1
Minneapolis-St. Paul-Bloomington, MN-WI      13,278
     832    1.3   0.1
Missoula, MT                                    614
     211    2.1   0.7
Mobile, AL                                    1,076
     327    1.2   0.3
Modesto, CA                                   1,246
     309    1.3   0.3
Monroe, LA                                      350
     182    0.8   0.4
Monroe, MI                                      318
     182    1.3   0.8
Montgomery, AL                                2,442
     441    2.4   0.4
Morgantown, WV                                  348
     204    1.5   0.9
Morristown, TN                                  154
     103    0.6   0.4
Mount Vernon-Anacortes, WA                      390
     197    1.5   0.8
Muncie, IN                                      266
     149    1.0   0.6
Muskegon-Norton Shores, MI                      338
     160    1.0   0.5
Myrtle Beach-North Myrtle Beach-Conway, SC      750
     301    1.3   0.5
Napa, CA                                             922
     302    2.7   0.9
Naples-Marco Island, FL                              410
     168    0.6   0.2
Nashville-Davidson--Murfreesboro--Franklin, TN     8,382
     915    2.0   0.2
New Haven-Milford, CT                              2,358
     428    1.1   0.2
New Orleans-Metairie-Kenner, LA                   10,726
   1,144    3.7   0.4
New York-Northern New Jersey-Long Island, NY-    183,278
   4,246    3.8   0.1
Niles-Benton Harbor, MI                              246
     134    0.7   0.4
North Port-Bradenton-Sarasota, FL                  1,226
     343    0.9   0.2
Norwich-New London, CT                             1,462
     344    1.8   0.4
Ocala, FL                                            686
     336    1.2   0.6
Ocean City, NJ                                       256
     118    1.3   0.6
Odessa, TX                                           372
     168    1.1   0.5
Ogden-Clearfield, UT                                 642
     221    0.6   0.2
Oklahoma City, OK                                  3,604
     524    1.1   0.2
Olympia, WA                                          706
     226    1.3   0.4
Omaha-Council Bluffs, NE-IA                        1,714
     358    0.7   0.1
Orlando-Kissimmee-Sanford, FL                      7,602
     793    1.4   0.1
Oshkosh-Neenah, WI                                   304
     107    0.5   0.2
Owensboro, KY                                        270
     144    1.1   0.6
Oxnard-Thousand Oaks-Ventura, CA                   4,502
     884    2.6   0.5
Palm Bay-Melbourne-Titusville, FL                  1,428
     369    1.1   0.3
Palm Coast, FL                                        20
      31    0.2   0.3
Panama City-Lynn Haven-Panama City Beach, F          386
     162    0.9   0.4
Parkersburg-Marietta-Vienna, WV-OH                   344
     172    1.1   0.6
Pascagoula, MS                                       382
     156    1.3   0.5
Pensacola-Ferry Pass-Brent, FL                       500
     199    0.5   0.2
Peoria, IL                                         1,324      314    1.4   0.3
Philadelphia-Camden-Wilmington, PA-NJ-DE-MD       23,992    1,435	   1.6   0.1
Phoenix-Mesa-Glendale, AZ                          7,350      936    0.7   0.1
Pine Bluff, AR                                       402
     173    2.0   0.9
Pittsburgh, PA                                     5,782
     710    1.0   0.1
Pittsfield, MA                                       316
     156    1.0   0.5
Pocatello, ID                                         76
      60    0.4   0.3
Port St. Lucie, FL                                   394
     166    0.6   0.2
Portland-South Portland-Biddeford, ME              2,334
     459    1.7   0.3
Portland-Vancouver-Hillsboro, OR-WA                3,810
     560    0.7   0.1
Poughkeepsie-Newburgh-Middletown, NY               2,842
     537    2.5   0.5
Prescott, AZ                                         592
     246    1.6   0.7
Providence-New Bedford-Fall River, RI-MA           2,116
     448    0.6   0.1
Provo-Orem, UT                                       626
     380    0.8   0.5
Pueblo, CO                                           238
     102    0.7   0.3
Punta Gorda, FL                                       68
      86    0.3   0.4
Racine, WI                                           338
     163    0.8   0.4
Raleigh-Cary, NC                                   4,144
     736    1.5   0.3
Rapid City, SD                                       254
     147    0.8   0.4
Reading, PA                                          612
     214    0.7   0.3
Redding, CA                                          216
     120    0.6   0.3
Reno-Sparks, NV                              484     207   0.4   0.2
Richmond, VA                               6,192     807   1.9   0.2
Riverside-San Bernardino-Ontario, CA      15,816   1,242   2.3   0.2
Roanoke, VA                                1,348     397   1.6   0.5
Rochester, MN                                596     157   1.1   0.3
Rochester, NY                              1,886     418   0.7   0.2
Rockford, IL                                 980     290   1.2   0.3
Rocky Mount, NC                              298     146   1.0   0.5
Rome, GA                                      98      65   0.4   0.3
Sacramento--Arden-Arcade--Roseville, CA    8,044     936   1.7   0.2
Saginaw-Saginaw Township North, MI           626     161   1.3   0.3
Salem, OR                                  1,072     314   1.3   0.4
Salinas, CA                                1,986     402   2.5   0.5
Salisbury, MD                                238     148   0.9   0.6
Salt Lake City, UT                         2,318     361   0.7   0.1
San Angelo, TX                               198     114   0.7   0.4
San Antonio-New Braunfels, TX              3,824     648   0.8   0.1
San Diego-Carlsbad-San Marcos, CA         14,036   1,101   1.8   0.1
San Francisco-Oakland-Fremont, CA         46,234   2,376   4.1   0.2
San Jose-Sunnyvale-Santa Clara, CA        19,820   1,402   3.8   0.3
San Luis Obispo-Paso Robles, CA              476     241   0.9   0.5
Sandusky, OH                                 268     180   1.3   0.9
Santa Barbara-Santa Maria-Goleta, CA       1,836     390   2.0   0.4
Santa Cruz-Watsonville, CA                   626     301   1.3   0.7
Santa Fe, NM                               1,594     538   4.4   1.5
Santa Rosa-Petaluma, CA                    2,000     429   2.1   0.5
Savannah, GA                               1,532     380   1.9   0.5
Scranton--Wilkes-Barre, PA                 1,044     281   0.8   0.2
Seattle-Tacoma-Bellevue, WA               11,256   1,222   1.1   0.1
Sebastian-Vero Beach, FL                     208     119   0.8   0.4
Sheboygan, WI                                288     167   0.9   0.5
Sherman-Denison, TX                          238     170   1.1   0.8
Shreveport-Bossier City, LA                1,456     403   1.4   0.4
Sioux City, IA-NE-SD                         314     133   0.8   0.3
Sioux Falls, SD                              506     131   0.7   0.2
South Bend-Mishawaka, IN-MI                  592     205   0.8   0.3
Spartanburg, SC                              682     272   0.9   0.4
Spokane, WA                                  544     171   0.5   0.1
Springfield, IL                              954     183   1.4   0.3
Springfield, MA                            1,768     462   1.1   0.3
Springfield, MO                            1,348     280   1.2   0.3
Springfield, OH                              210     130   0.8   0.5
St. Cloud, MN                                674     175   1.3   0.3
St. George, UT                               266     142   1.3   0.7
St. Joseph, MO-KS                            178     114   0.6   0.4
St. Louis, MO-IL                          10,628     922   1.4   0.1
State College, PA                            366     155   1.1   0.5
Steubenville-Weirton, OH-WV                           66
         58     0.3   0.3
Stockton, CA                                       2,360
        445     2.1   0.4
Sumter, SC                                           216
        139     0.8   0.5
Syracuse, NY                                       1,878
        440     1.1   0.3
Tallahassee, FL                                      648
        247     0.7   0.3
Tampa-St. Petersburg-Clearwater, FL                5,332
        757     0.8   0.1
Terre Haute, IN                                      586
        216     1.5   0.6
Texarkana, TX-Texarkana, AR                          236
        152     0.8   0.5
Toledo, OH                                         2,112
        401     1.3   0.2
Topeka, KS                                           652
        247     1.0   0.4
Trenton-Ewing, NJ                                  3,562
        562     2.8   0.5
Tucson, AZ                                         2,104
        497     0.9   0.2
Tulsa, OK                                          3,390
        495     1.3   0.2
Tuscaloosa, AL                                       862
        295     1.9   0.7
Tyler, TX                                            684
        295     1.3   0.6
Utica-Rome, NY                                       572
        213     0.9   0.3
Valdosta, GA                                         128
        110     0.4   0.4
Vallejo-Fairfield, CA                              2,238
        534     3.1   0.7
Victoria, TX                                         610
        252     2.5   1.0
Vineland-Millville-Bridgeton, NJ                     282
        117     0.8   0.4
Virginia Beach-Norfolk-Newport News, VA-NC         5,518
        797     1.1   0.2
Visalia-Porterville, CA                              890
        395     1.3   0.6
Waco, TX                                             944
        316     1.7   0.6
Warner Robins, GA                                    768
        303     2.0   0.8
Washington-Arlington-Alexandria, DC-VA-MD-WV      69,158
      2,689	    3.8   0.1
Waterloo-Cedar Falls, IA                             760
        313     1.6   0.6
Wausau, WI                                           304
        130     0.7   0.3
Wenatchee-East Wenatchee, WA                         224
        124     1.2   0.6
Wheeling, WV-OH                                      372
        183     1.2   0.6
Wichita Falls, TX                                    574
        250     1.5   0.6
Wichita, KS                                        1,542
        326     0.9   0.2
Williamsport, PA                                     382
        220     1.2   0.7
Wilmington, NC                                     1,202
        362     1.5   0.4
Winchester, VA-WV                                  1,156
        349     3.7   1.1
Winston-Salem, NC                                  1,328
        456     1.2   0.4
Worcester, MA                                      2,158
        466     1.2   0.3
Yakima, WA                                           550
        215     1.1   0.4
York-Hanover, PA                                   1,396
        328     1.4   0.3
Youngstown-Warren-Boardman, OH-PA                    966
        274     0.8   0.2
Yuba City, CA                                        204
        118     0.8   0.5
Yuma, AZ                                             200
        120     0.6   0.4
Source: U.S. Census Bureau, 2006-2010 5-year American Community Survey
Out-of-State and Long Commutes: 2011
American Community Survey Reports

By Brian McKenzie
Issued February 2013
ACS-20




  A complex set of factors influences variation in com-                   outside of their state of residence. These topics are
  muting patterns across the United States, and multiple                  subsets of a much broader, more complex set of travel
  indicators may be considered when assessing such pat-                   time and place indicators. The media occasionally dis-
  terns. Among other factors, the relationship between                    cuss such commuting patterns within several contexts,
  home and work is influenced by community develop-                       including health, interstate commuter taxes, and shifts
  ment patterns, labor market shifts, and technological                   in the housing and labor markets. This report may
  changes that expand workers’ options for where and                      serve as a baseline statistical reference point for such
  how to work. The American Community Survey (ACS)                        discussions. Unless otherwise noted, estimates refer to
  provides critical information about several aspects of                  the working population who did not work at home.
  commuting for U.S. workers. The ACS is an ongoing
  survey conducted annually by the U.S. Census Bureau                     HIGHLIGHTS
  that captures changes in the socioeconomic, housing,                    • Among U.S. workers who did not work at home,
  and demographic characteristics of communities across                     8.1 percent had commutes of 60 minutes or longer
  the United States and Puerto Rico.1                                       in 2011.
  The ACS questions related to travel focus solely on the                 • An estimated 61.1 percent of workers with “long
  work trip and do not ask about leisure travel or other                    commutes” drove to work alone, compared with
  nonwork trips. Among other commuting questions,                           79.9 percent for all workers who did not work
  the ACS asks respondents in the workforce about their                     at home.
  principal workplace location and the number of min-
                                                                          • New York shows the highest rate of “long commutes”
  utes it usually takes to get from home to work, one
                                                                            at 16.2 percent, followed by Maryland and New
  way. This report uses 2011 ACS data at the state level
                                                                            Jersey at 14.8 and 14.6 percent, respectively.
  to explore two commuting indicators related to travel
  time and work location: (1) the percentage of commut-                   • The District of Columbia has the highest rate of out-
  ers with long commutes (commutes of 60 minutes or                         of-state commuters among its resident workers at
  longer) and (2) the percentage of workers who work                        25.2 percent, followed by Maryland at 18.3 percent.
                                                                          • Among all people who work in the District of
     1
        The ACS uses a series of monthly samples to produce annual
  estimates. Detailed questions that previously appeared on the decen-      Columbia, 72.4 percent live outside the District
  nial census long form are now included in the ACS, and the decennial      of Columbia.
  census now produces a count of the nation’s population and a snapshot
  of its most basic demographic characteristics. Five years of ACS data
  collection are necessary to achieve a cumulative sample large enough
                                                                          COMMUTES OF 60 MINUTES OR LONGER
  to ensure respondent confidentiality for smaller communities and for
  small geographic units such as census tracts or block groups. For       As a relative concept, the definition of a long commute
  larger geographies, specifically those with populations of 65,000 or    varies across people and communities. For simplic-
  greater, estimates are available annually. For selected geographies
  with populations of 20,000 or greater, combined 3-year estimates
                                                                          ity, this report defines long commutes as those of 60
  are available.




  U.S. Department of Commerce
  Economics and Statistics Administration
  U.S. CENSUS BUREAU
  census.gov
                                                                                         minutes or longer (one way). This
     Figure 1.                                                                           threshold is well above the national
     Average One-Way Travel Time for U.S. Workers:                                       average travel time of 25.5 min-
     2000–2011                                                                           utes in 2011. Figure 1 shows that
     (Data based on sample. For information on confidentiality protection,               the national average travel time
     sampling error, nonsampling error, and definitions, see
                                                                                         fluctuated little between 2000 and
     www.census.gov/acs/www/)
                                                                                         2011. The 60-minute travel time
           Minutes                                                                       threshold is also roughly twice that
     26                                                                                  of metro areas with the longest
                                                                                         average travel times, which exceed
                                                                                         30 minutes. For example, in 2011,
                                                                                         workers in the New York City metro
     25
                                                                                         area and the Washington, DC,
                                                                                         metro area had the two longest
                                                                                         average travel times among metro
     24                                                                                  areas, at 34.9 minutes and 34.5
                                                                                         minutes, respectively.

                                                                                         Table 1 lists the distribution of
                                                                                         commuting times across several
     23
                                                                                         intervals. The percentage of work-
                                                                                         ers with commutes of 60 minutes
                                                                                         or longer was 8.1 percent in 2011.
     22                                                                                  Shorter travel time categories
                                                                                         accounted for a relatively high
                                                                                         percentage of commuters. For
                                                                                         example, 15.5 percent of workers
       0                                                                                 had commutes of 15 to 19 minutes,
            2000            2006     2007    2008     2009     2010     2011
                                                                                         and 14.8 percent had commutes of
           Census           ACS      ACS     ACS      ACS      ACS      ACS
                                                                                         20 to 24 minutes. The percentage
     Source: U.S. Census Bureau, Census 2000 and 2006–2011 American Community Surveys.   of workers with commutes of 60
                                                                                         minutes or longer was 8.0 percent
                                                                                         in 2000, and this proportion has
                                                                                         fluctuated little between 2000 and
    What Is The American Community Survey?
                                                                                         2011, when it reached 8.1 percent
    The American Community Survey (ACS) is a nationwide survey designed                  (Figure 2). Commutes of 90 min-
    to provide communities with reliable and timely demographic, social,                 utes or longer (“extreme com-
    economic, and housing data for the nation, states, congressional dis-                mutes”) showed similar stability
    tricts, counties, places, and other localities every year. It had a 2011             across years, at 2.8 percent in 2000
    sample size of about 3.3 million addresses across the United States and              and 2.5 percent in 2011. Although
    Puerto Rico and includes both housing units and group quarters (e.g.,                this report focuses on commutes
    nursing facilities and prisons). The ACS is conducted in every county                of 60 minutes or longer, reference
    throughout the nation and every municipio in Puerto Rico, where it is                to commuting rates of 90 minutes
    called the Puerto Rico Community Survey. Beginning in 2006, ACS data                 or longer illustrates the stability of
    for 2005 were released for geographic areas with populations of 65,000               travel time patterns at the national
    and greater. For information on the ACS sample design and other topics,              level, even among the most
    visit <www.census.gov/acs/www>.                                                      extreme commutes. This trend may
                                                                                         be contrary to popular assumptions
                                                                                         about national travel time patterns,
                                                                                         which are likely to be informed




2                                                                                                              U.S. Census Bureau
by local trends that show more                  Table 1.
variation. For the remainder of the             Travel Time to Work: 2011
report, “long commutes” will refer              (For information on confidentiality protection, sampling error, nonsampling error,
to those of 60 minutes or longer.               and definitions, see www.census.gov/acs/www/)
                                                   One-way travel time interval                         Percentage of workers              Margin of error1 (±)
Rates of long commutes vary
                                                Less than 10 minutes  .  .  .  .  .  .  .  .                            13 .4                                  0 .1
across residence and workplace
                                                10 to 14 minutes  .  .  .  .  .  .  .  .  .  .  .  .                    14 .3                                  0 .1
community types throughout met-                 15 to 19 minutes  .  .  .  .  .  .  .  .  .  .  .  .                    15 .5                                  0 .1
ropolitan areas (Table 2).2 Workers             20 to 24 minutes  .  .  .  .  .  .  .  .  .  .  .  .                    14 .8                                  0 .1
                                                25 to 29 minutes  .  .  .  .  .  .  .  .  .  .  .  .                     6 .1                                  0 .1
residing outside of a principal city
                                                30 to 34 minutes  .  .  .  .  .  .  .  .  .  .  .  .                    13 .7                                  0 .1
(in a metropolitan area) and work-              35 to 44 minutes  .  .  .  .  .  .  .  .  .  .  .  .                     6 .4                                  0 .1
ing in a principal city show the                45 to 59 minutes  .  .  .  .  .  .  .  .  .  .  .  .                     7 .5                                  0 .1
highest rate of long commutes, at               60 or more minutes  .  .  .  .  .  .  .  .  .  .                         8 .1                                  0 .1

12.5 percent. Among workers who                      1
                                                       Data are based on a sample and are subject to sampling variability . A margin of error is a measure
travel 60 minutes or longer, those              of an estimate’s variability . The larger the margin of error in relation to the size of the estimates, the less
                                                reliable the estimate . When added to and subtracted from the estimate, the margin of error forms the 90
living and working outside of a                 percent confidence interval .
principal city but in a metro area,                  Source: U .S . Census Bureau, 2011 American Community Survey .
had the lowest rate of long com-
mutes, at 6.6 percent, a rate lower
than that of workers living and
                                                       Figure 2.
working in principal cities, at 7.1
                                                       Percentage of Workers With One-Way Commutes of
percent. Among workers engag-                          60 and 90 Minutes or Longer: 2000–2011
ing in a “reverse commute,” that is,                   (Data based on sample. For information on confidentiality protection,
living in a principal city and work-                   sampling error, nonsampling error, and definitions, see
ing outside of a principal city, 9.0                   www.census.gov/acs/www/)
percent reported a long commute.                             Percent
Among workers living outside of                        10
a metro area, 7.1 percent had a
long commute.                                            9

The distribution of transportation                       8
modes used by workers with long
                                                                                     60 minutes or longer
commutes differs from that of the                        7
general worker population (Table
3). Among workers with long com-                         6
mutes, only 61.1 percent drove
to work alone, compared with                             5
79.9 percent for all workers who
                                                         4
worked outside the home. Workers
with long commutes had a notably
                                                         3
higher rate of public transportation
usage at 23.0 percent, compared                          2                                  90 minutes or longer
with 5.3 percent for the general
worker population. This differ-                          1
ence might be expected, given
    2
      For more detailed information about the            0
                                                               2000                            2006    2007    2008     2009      2010        2011
Office of Management and Budget’s (OMB)
                                                              Census                           ACS     ACS     ACS      ACS       ACS         ACS
standards for delineating metropolitan and
micropolitan statistical areas, visit                  Source: U.S. Census Bureau, Census 2000 and 2006–2011 American Community Surveys.
<www.census.gov/population/metro/>. This
analysis uses 2003 OMB metro area
definitions.




U.S. Census Bureau                                                                                                                                                 3
Table 2.
Long Commutes by Residence and Workplace Community Type: 2011
(For information on confidentiality protection, sampling error, nonsampling error, and definitions, see www.census.gov/acs/www/)
                                                                                                                                    Total number of   Margin of    Percentage of          Margin of
           Home and workplace metropolitan area component
                                                                                                                                            workers   error1 (±)        workers           error1 (±)
All Workers Who Did Not Work at Home
1 to 59 minutes  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .     121,496,438      135,572             91 .9                   –
60 minutes or longer  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .             10,779,412       67,179              8 .1                   –
Suburb to City (Lived in metro area outside any principal city,
 worked in any principal city)
1 to 59 minutes  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .       22,397,939      74,481             87 .5                 0 .1
60 minutes or longer  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .               3,211,045      33,808             12 .5                 0 .1
Suburb to Suburb (Lived in metro area outside any principal
 city, worked outside any principal city)
1 to 59 minutes  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .       40,319,502      95,296             93 .4                 0 .1
60 minutes or longer  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .               2,867,944      33,432              6 .6                 0 .1
City to City (Lived in metro area in principal city, worked in any
 principal city)
1 to 59 minutes  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .       31,195,540      82,991             92 .9                 0 .1
60 minutes or longer  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .               2,383,964      29,891              7 .1                 0 .1
City to Suburb (Lived in metro area in principal city, worked
 outside any principal city)
1 to 59 minutes  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .        9,263,346      55,843             91 .0                 0 .2
60 minutes or longer  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .                 912,353      17,896              9 .0                 0 .2
Lived Outside of Any Metro Area
1 to 59 minutes  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .       18,320,111      51,938             92 .9                 0 .1
60 minutes or longer  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .               1,404,106      15,846              7 .1                 0 .1

     – Represents or rounds to zero .
     1
       Data are based on a sample and are subject to sampling variability . A margin of error is a measure of an estimate’s variability . The larger the margin of error
in relation to the size of the estimates, the less reliable the estimate . When added to and subtracted from the estimate, the margin of error forms the 90 percent
confidence interval .
     Source: U .S . Census Bureau, 2011 American Community Survey .



    Definitions
    A long commute refers to a one-way commute of 60 minutes or longer.

    Workers are civilians and members of the Armed Forces, 16 years and older, who were at work the previous
    week. Persons on vacation or not at work the prior week are not included.

    Means of transportation to work refers to the principal mode of travel that the worker usually used to get
    from home to work during the reference week. People who used different means of transportation on different
    days of the week were asked to specify the one they used most often. People who used more than one means
    of transportation to get to work each day were asked to report the one used for the longest distance during the
    work trip. Workers who worked at home are not included in information presented in this report unless other-
    wise stated. For more detailed definitions of these terms and other ACS terms, see the ACS subject definitions
    list at <www.census.gov/acs/www/data_documentation/documentation_main/>.

    The largest city in each metropolitan or micropolitan statistical area is designated a principal city. Additional
    cities qualify if specified requirements are met concerning population size and employment. The title of each
    metropolitan or micropolitan statistical area consists of the names of up to three of its principal cities and the
    name of each state into which the metropolitan or micropolitan statistical area extends.




4                                                                                                                                                                                  U.S. Census Bureau
Table 3.
Commute Mode by Long Commute Status: 2011
(For information on confidentiality protection, sampling error, nonsampling error, and definitions, see www.census.gov/acs/www/)
                                                                                                                        Total number of          Margin of      Percentage of         Margin of
                                         Commute mode
                                                                                                                                workers          error1 (±)          workers          error1 (±)
All Workers Who Did Not Work at Home
       Total  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .     132,275,850             131,412
Drove alone  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .      105,639,344             118,012               79 .9               0 .1
Carpooled  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .      13,387,578              69,112               10 .1               0 .1
Public transportation  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .                   6,955,978              46,380                5 .3                  –
  Subway or railroad  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .                    3,165,500              37,776                2 .4                  –
  Other public transportation .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .                              3,790,478              34,742                2 .9                  –
Other means  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .           6,292,950              51,927                4 .8                  –
Workers With Travel Times of 1 to 59 Minutes
       Total  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .     121,496,438             135,572
Drove alone  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .       99,050,582             121,894               81 .5               0 .1
Carpooled  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .      11,992,482              63,735                9 .9               0 .1
Public transportation  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .                   4,475,271              35,094                3 .7                  –
  Subway or railroad  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .                    1,892,376              25,018                1 .6                  –
  Other public transportation .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .                              2,582,895              26,132                2 .1                  –
Other means  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .           5,978,103              49,233                4 .9                  –
Workers With Travel Times of 60 Minutes or Longer
       Total  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .       10,779,412             67,179
Drove alone  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .         6,588,762             47,638               61 .1               0 .3
Carpooled  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .        1,395,096             25,020               12 .9               0 .2
Public transportation  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .                    2,480,707             29,476               23 .0               0 .2
  Subway or railroad  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .                     1,273,124             22,299               11 .8               0 .2
  Other public transportation .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .                               1,207,583             21,835               11 .2               0 .2
Other means  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .              314,847             10,799                2 .9               0 .1

     – Represents or rounds to zero .
     1
       Data are based on a sample and are subject to sampling variability . A margin of error is a measure of an estimate’s variability . The larger the margin of error
in relation to the size of the estimates, the less reliable the estimate . When added to and subtracted from the estimate, the margin of error forms the 90 percent
confidence interval .
     Source: U .S . Census Bureau, 2011 American Community Survey .



that the average travel time for                                                                       workers living in a given state, New               long commutes, while a distinct
public transportation commuters is                                                                     York shows the highest rate of long                pocket of the Midwest, including
consistently longer than that of the                                                                   commutes at 16.2 percent, fol-                     Nebraska, Kansas, South Dakota,
general working population. Rail                                                                       lowed by Maryland and New Jersey                   and Iowa, has comparatively low
travel accounted for 11.8 percent                                                                      at 14.8 percent and 14.6 percent,                  rates of long commutes.
of workers with long commutes,                                                                         respectively.3 These states and sev-
                                                                                                                                                          Focusing on workers working in a
and other forms of public transpor-                                                                    eral others with high rates of long
                                                                                                                                                          given state rather than residing in
tation accounted for 11.2 percent.                                                                     commutes among resident work-
                                                                                                                                                          it (Table 4), workers in the District
Air travel is not included as a                                                                        ers contain or are adjacent to large
                                                                                                                                                          of Columbia showed the highest
separate category in the ACS travel                                                                    metropolitan areas. Workers in
                                                                                                                                                          rate of long commutes. More than
mode question, so it is not possible                                                                   large metro areas such as New York
                                                                                                                                                          a quarter (27.4 percent) of District
to determine the percentage of                                                                         City and Washington, DC, generally
                                                                                                                                                          of Columbia workers traveled 60
commutes by this mode.                                                                                 have longer average travel times
                                                                                                                                                          minutes or longer to get to work,
                                                                                                       than those in smaller metro areas.
Table 4 shows the number and per-                                                                                                                         notably higher than that of any
                                                                                                       The map illustrates spatial patterns
centage of workers with long com-                                                                                                                         other state. The District of Columbia
                                                                                                       associated with long commutes.
mutes for each state, organized by                                                                                                                        is followed by New York, with 18.2
                                                                                                       Several states in the Northeast have
residence in each state and workers                                                                                                                       percent of its workers reporting
                                                                                                       a high percentage of workers with
in each state. Figure 3 presents a                                                                                                                        long commutes. A high percentage
map of the same information. For                                                                          3
                                                                                                            Values for Maryland and New Jersey are        of long commutes among a state’s
                                                                                                       not statistically different from one another.




U.S. Census Bureau                                                                                                                                                                             5
Table 4.
Workers With Commutes of 60 Minutes or Longer by State: 2011
(For information on confidentiality protection, sampling error, nonsampling error, and definitions, see www.census.gov/acs/www/)
                                                               Workers living in specified state, commuting           Workers working in specified state, commuting
                                                                           60 minutes or longer                                  60 minutes or longer
                      State
                                                                           Margin of                    Margin of                 Margin of                    Margin of
                                                                 Total     error1 (±)      Percent      error1 (±)       Total    error1 (±)      Percent      error1 (±)
Alabama  .  .  .  .  .  .  .  .  .  .  .  .  .  .              112,523        5,536            5 .9           0 .3     111,626        5,573           6 .0            0 .3
Alaska  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .          14,499        2,275            4 .4           0 .7      16,175        2,643           4 .8            0 .8
Arizona  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .           150,478        9,174            6 .0           0 .4     147,200        9,284           5 .9            0 .4
Arkansas  .  .  .  .  .  .  .  .  .  .  .  .  .  .              58,237        4,679            5 .0           0 .4      57,331        4,453           4 .9            0 .4
California  .  .  .  .  .  .  .  .  .  .  .  .  .  .         1,530,679       24,369           10 .1           0 .2   1,531,308       24,531          10 .1            0 .2
Colorado  .  .  .  .  .  .  .  .  .  .  .  .  .  .             154,446        8,769            6 .6           0 .4     148,447        8,422           6 .4            0 .4
Connecticut  .  .  .  .  .  .  .  .  .  .  .  .                125,820        5,966            7 .7           0 .4     105,633        6,203           6 .4            0 .4
Delaware  .  .  .  .  .  .  .  .  .  .  .  .  .  .              33,311        3,253            8 .3           0 .8      24,802        2,292           6 .3            0 .5
District of Columbia  .  .  .  .  .  .                          26,840        2,702            9 .2           0 .9     216,381        9,537          27 .4            1 .0
Florida  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .        491,314       15,109            6 .4           0 .2     483,540       15,711           6 .4            0 .2
Georgia  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .          367,181        13,478            9 .3           0 .3    361,865        13,130           9 .1            0 .3
Hawaii  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .         50,594         4,327            8 .2           0 .7     50,010         4,296           8 .1            0 .7
Idaho  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .       26,363         2,486            4 .2           0 .4     22,567         2,137           3 .7            0 .4
Illinois .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .    613,124        15,004           11 .0           0 .3    627,895        15,829          11 .3            0 .3
Indiana  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .       163,313         6,673            5 .8           0 .2    141,776         6,290           5 .2            0 .2
Iowa  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .     52,782         3,376            3 .7           0 .2     53,287         3,506           3 .7            0 .2
Kansas .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .          43,204         3,304            3 .3           0 .2     47,439         4,060           3 .6            0 .3
Kentucky  .  .  .  .  .  .  .  .  .  .  .  .  .  .             98,383         4,844            5 .6           0 .3     99,941         5,085           5 .6            0 .3
Louisiana  .  .  .  .  .  .  .  .  .  .  .  .  .  .           142,571         5,709            7 .5           0 .3    148,890         6,032           7 .8            0 .3
Maine  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .       39,620         2,740            6 .6           0 .4     33,815         2,591           5 .8            0 .4
Maryland  .  .  .  .  .  .  .  .  .  .  .  .  .  .            404,601         9,963           14 .8           0 .4    289,984         8,704          11 .8            0 .3
Massachusetts .  .  .  .  .  .  .  .  .  .                    334,831         9,878           10 .9           0 .3    366,464        10,482          11 .7            0 .3
Michigan  .  .  .  .  .  .  .  .  .  .  .  .  .  .            238,502         7,534            6 .0           0 .2    233,459         7,185           6 .0            0 .2
Minnesota  .  .  .  .  .  .  .  .  .  .  .  .  .              135,560         5,289            5 .3           0 .2    140,142         5,640           5 .5            0 .2
Mississippi  .  .  .  .  .  .  .  .  .  .  .  .  .             74,559         4,749            6 .6           0 .4     65,249         4,905           6 .0            0 .4
Missouri  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .         131,969         6,425            5 .1           0 .2    135,752         6,341           5 .2            0 .2
Montana .  .  .  .  .  .  .  .  .  .  .  .  .  .  .            19,133         2,056            4 .3           0 .5     18,344         1,916           4 .1            0 .4
Nebraska  .  .  .  .  .  .  .  .  .  .  .  .  .  .             25,551         2,538            2 .9           0 .3     27,955         2,687           3 .1            0 .3
Nevada  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .            66,218         6,070            5 .7           0 .5     64,629         6,061           5 .5            0 .5
New Hampshire  .  .  .  .  .  .  .  .  .                       61,139         4,065            9 .7           0 .6     37,217         3,077           6 .3            0 .5
New Jersey  .  .  .  .  .  .  .  .  .  .  .  .                 571,585       12,190           14 .6           0 .3     403,205       10,681          11 .1            0 .3
New Mexico  .  .  .  .  .  .  .  .  .  .  .  .                  41,244        4,119            5 .0           0 .5      42,473        4,043           5 .2            0 .5
New York  .  .  .  .  .  .  .  .  .  .  .  .  .  .           1,366,877       21,358           16 .2           0 .2   1,589,525       23,149          18 .2            0 .2
North Carolina  .  .  .  .  .  .  .  .  .  .                   204,833        7,532            5 .1           0 .2     201,843        8,011           5 .1            0 .2
North Dakota  .  .  .  .  .  .  .  .  .  .  .                   15,743        1,928            4 .5           0 .6      21,451        2,242           5 .7            0 .6
Ohio  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .     243,812        8,132            4 .9           0 .2     242,570        8,109           4 .9            0 .2
Oklahoma  .  .  .  .  .  .  .  .  .  .  .  .  .                 74,389        3,898            4 .6           0 .2      73,105        4,291           4 .6            0 .3
Oregon .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .           86,808        5,296            5 .5           0 .3      91,899        5,544           5 .7            0 .3
Pennsylvania  .  .  .  .  .  .  .  .  .  .  .                  461,531       10,197            8 .4           0 .2     431,764        8,807           7 .9            0 .2
Rhode Island  .  .  .  .  .  .  .  .  .  .  .                   28,502        2,516            5 .9           0 .5      22,594        2,748           4 .8            0 .6
South Carolina  .  .  .  .  .  .  .  .  .  .                   98,823         5,139            5 .2           0 .3     99,397         5,913           5 .4            0 .3
South Dakota  .  .  .  .  .  .  .  .  .  .  .                  13,936         1,902            3 .6           0 .5     14,820         1,830           3 .8            0 .5
Tennessee  .  .  .  .  .  .  .  .  .  .  .  .  .              150,119         6,911            5 .7           0 .3    152,272         7,238           5 .7            0 .3
Texas  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .      756,492        16,873            7 .0           0 .2    754,458        17,435           7 .0            0 .2
Utah  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .     54,742         4,156            4 .6           0 .3     53,477         4,050           4 .5            0 .3
Vermont  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .           14,400         1,461            4 .8           0 .5     15,373         1,560           5 .2            0 .5
Virginia .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .       372,087        10,484           10 .0           0 .3    339,791        10,411           9 .4            0 .3
Washington  .  .  .  .  .  .  .  .  .  .  .  .                225,679         7,886            7 .7           0 .3    217,868         7,913           7 .6            0 .3
West Virginia  .  .  .  .  .  .  .  .  .  .  .                 65,874         3,981            9 .3           0 .6     51,391         3,169           7 .4            0 .4
Wisconsin  .  .  .  .  .  .  .  .  .  .  .  .  .              128,362         5,118            4 .8           0 .2    115,500         4,504           4 .4            0 .2
Wyoming  .  .  .  .  .  .  .  .  .  .  .  .  .  .              16,229         2,199            5 .9           0 .8     18,443         2,490           6 .6            0 .9
Puerto Rico  .  .  .  .  .  .  .  .  .  .  .  .               144,030         6,779           13 .9           0 .6    143,928         6,785          13 .9            0 .6

     1
       Data are based on a sample and are subject to sampling variability . A margin of error is a measure of an estimate’s variability . The larger the margin of error
in relation to the size of the estimates, the less reliable the estimate . When added to and subtracted from the estimate, the margin of error forms the 90 percent
confidence interval .
     Note: Estimates do not include workers who worked at home .
     Source: U .S . Census Bureau, 2011 American Community Survey .



6                                                                                                                                                      U.S. Census Bureau
                                                Figure 3.
                                AK              Percentage of Workers Living in State With Commutes of 60 Minutes
                                                or Longer: 2011




U.S. Census Bureau
                                                (Data based on sample. For information on confidentiality protection, sampling error, nonsampling error,
                                                and definitions, see www.census.gov/acs/www)




                               WA

                                                                                                                                                      ME
                                                   MT                 ND
                                                                                                      MI
                          OR                                                      MN                                                        VT
                                     ID                                                                                                          NH
                                                                      SD                         WI                                    NY        MA
                                                                                                            MI
                                                     WY
                                                                                                                                                            RI
                                                                                                                                                       CT
                                                                                       IA                                         PA
                                                                       NE                                                                         NJ
                               NV                                                                                     OH
                                           UT                                                     IL       IN                                    DE
                     CA                                                                                                     WV                   MD
                                                          CO
                                                                            KS          MO                                        VA              DC
                                                                                                                 KY
                                                                                                                                  NC
                                                                                                           TN
                                                                             OK
                                      AZ                                                    AR
                                                     NM                                                                      SC
                                                                                                                                            Percent of workers
                                                                                                  MS       AL          GA
                                                                                                                                                   Less than 4 percent

                                                                      TX                                                                           4 to 5.9 percent
                                                                                            LA
                                                                                                                                                   6 to 8.9 percent
                                                                                                                             FL                    9 to 11.9 percent
                                                                                                                                                   12 percent or greater

                                                                                                                                            National average: 8.1 percent

                                      HI

                                                            Source: U. S. Census Bureau, American Community Survey, 2011.




7
workers may reflect several travel
characteristics, such as long travel                                                       Figure 4.
distances, high levels of congestion,                                                      Average Travel Time by Workplace Location: 2011
or a diverse set of commute modes.                                                         (In minutes. Data based on sample. For information on confidentiality
                                                                                           protection, sampling error, nonsampling error, and definitions, see
At 3.8 percent of U.S. workers in                                                          www.census.gov/acs/www/)
2011, out-of-state commutes repre-
sent a small portion of all workers,                                                                                                               44.8
but a relatively high percentage
of long commutes. Table 5 links
the concept of long commutes to
out-of-state commuting, showing
that among workers who commute
outside of their state of residence,
27.2 had long commutes, notably
                                                                                                    25.5
higher than the 7.4 percent of long                                                                                        24.7
commutes associated with workers
who worked within their residence
state. At 44.8 minutes, out-of-state
workers also had a longer average
travel time than in-state workers,
who averaged 24.7 minutes (Figure
4). While out-of-state commutes
are sometimes long, interstate
commuting does not necessarily
imply long distance travel. Inter-
state commutes may be relatively                                                                 All workers             Worked in            Worked outside
                                                                                                                     state of residence      state of residence
short, often reflecting incidental
state boundaries that transect large
expanses of urbanized space. Sub-                                                         Source: U.S. Census Bureau, 2011 American Community Survey.
sequent sections provide several



Table 5.
Long Commutes by Workplace Location: 2011
(For information on confidentiality protection, sampling error, nonsampling error, and definitions, see www.census.gov/acs/www/)
                                                                                           Total number of              Margin of          Percentage of             Margin of
                        Workplace location
                                                                                                   workers              error1 (±)              workers              error1 (±)
Worked in State of Residence
1 to 59 minutes  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .      117,650,194                 134,323                    92 .6                     –
60 minutes or longer  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .               9,340,682                  61,519                     7 .4                     –
Worked Outside State of Residence
1 to 59 minutes  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .         3,846,244                 28,056                    72 .8                   0 .3
60 minutes or longer  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .                1,438,730                 23,490                    27 .2                   0 .3

     – Represents or rounds to zero .
     1
       Data are based on a sample and are subject to sampling variability . A margin of error is a measure of an estimate’s variability . The larger the margin of error
in relation to the size of the estimates, the less reliable the estimate . When added to and subtracted from the estimate, the margin of error forms the 90 percent
confidence interval .
     Source: U .S . Census Bureau, 2011 American Community Survey .




8                                                                                                                                                             U.S. Census Bureau
examples of metro areas that                 in Maryland and Virginia accounted      routinely fly to far-away states for
straddle two or more states.                 for 70.4 percent of all workers         work purposes, readers should
                                             who work in the District of             assume that many of these cross-
OUT-OF-STATE COMMUTES                        Columbia. No other state’s work-        country trips represent infrequent
Table 6 provides estimates for               force exceeded 20.0 percent in its      work-related travel.5
two concepts of out-of-state com-            rate of out-of-state commuters. In
                                                                                     Table 7 shows 15 of the top state-
muting. The first set of estimates           addition to the District of Colum-
                                                                                     to-state commuting flows accord-
shows the number and percentage              bia, five states, all with relatively
                                                                                     ing to the number of workers com-
of workers who worked outside of             small populations, had rates of
                                                                                     muting from one state to another.
their state of residence, and the            10.0 percent or higher. Among
                                                                                     Consistent with patterns in Table
second set of estimates shows the            these are several geographically
                                                                                     6, Table 7 shows a high degree of
number and percentage of work-               small states in the Northeast,
                                                                                     interconnectedness among states
ers who worked in a given state              including Delaware, Rhode Island,
                                                                                     that make up large metropolitan
and lived outside of that state.4            and New Hampshire. At 11.6 per-
                                                                                     areas in the Northeastern United
Estimates in Table 6 do not include          cent, North Dakota also showed a
                                                                                     States. It also shows a considerable
workers who worked at home. The              relatively high rate of workers who
                                                                                     degree of reciprocal exchange of
District of Columbia showed the              live in a different state, with Min-
                                                                                     workers among several state pairs,
highest rate of out-of-state com-            nesota accounting for the largest
                                                                                     such as New Jersey and New York,
muters among its resident workers            share of out-of-state workers, at
                                                                                     and New Jersey and Pennsylvania.
at 25.2 percent, followed by Mary-           29,449.
                                                                                     Contiguity and spatial proximity
land at 18.3 percent. Maryland and           Information about commuting             clearly exert influence on commut-
the District of Columbia represent           activity between two specific           ing activity between states. Com-
states with a high degree of recip-          geographic areas helps define           muting flow patterns for several
rocal residence-to-workplace ties.           commuting patterns and provides         state pairs are largely driven by
About 12.0 percent of Maryland               a gauge of economic interconnect-       commutes that occur within one
workers commute to the District of           edness. When combined, informa-         large metro area that spans two
Columbia for work, and about 13.0            tion about workers’ residence loca-     or more states. For example, a
percent of District of Columbia              tion and workplace location form        great deal of commuting between
workers commute to Maryland.                 the basis of residence-to-workplace     Missouri and Kansas takes place
Table 6 also shows the percentage            “commuting flows.” For a list of        within the Kansas City metro area,
of people who work in a state                state-to-state commuting flows          and Portland, Oregon’s, suburbs
that is different from their state           and associated margins of error         in Washington state account for
of residence. The District of                available for download, see             much of the commuting between
Columbia stood out as a work loca-           <www.census.gov/hhes                    those states.
tion with a particularly high rate           /commuting/>. This table provides
                                                                                     While the percentage of long com-
of out-of-state workers. Among all           the number of commuters who
                                                                                     mutes has changed little at the
people who work in the District              live in a given state and travel to a
                                                                                     national level, some communities
of Columbia, 72.4 percent live in            different state for work. It shows
a different state. The District of           considerable variation across
                                             states in attracting workers from           5
                                                                                           The ACS asks respondents in the work-
Columbia is unique among states                                                      force about their principal workplace location
in that it is geographically small,          other states. For example, only         during the reference week, a week that may
the entire area is urban, and it             four states draw 100 or more            not represent their typical commute. Place-
                                                                                     of-work data show some workers who made
serves as a job center for all of its        workers who reside in Alaska,           atypical daily work trips (e.g., workers who
adjoining counties in Maryland and           but states such as California and       lived in New York and worked in California).
                                                                                     Such cases may represent workers who
Virginia. Together, persons living           Texas draw 100 or more work-            worked during the reference week at a loca-
                                             ers from more than 40 different         tion that was different from their usual place
   4
     Includes the District of Columbia and                                           of work, such as people away from home on
Puerto Rico.
                                             states. While some commuters may        business.




U.S. Census Bureau                                                                                                               9
Table 6.
Out-of-State Workers by State: 2011
(For information on confidentiality protection, sampling error, nonsampling error, and definitions, see www.census.gov/acs/www/)
                                                                Workers living in state, but working in                   Workers working in state, but living in
                                                                            different state                                         different state
                      State
                                                                         Margin of                        Margin of                Margin of                        Margin of
                                                               Total     error1 (±)       Percent         error1 (±)     Total     error1 (±)       Percent         error1 (±)
Alabama  .  .  .  .  .  .  .  .  .  .  .  .  .  .             85,653         4,549            4 .5              0 .2    47,135        3,835             2 .5              0 .2
Alaska  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .         1,643           688            0 .5              0 .2     8,791        1,637             2 .6              0 .5
Arizona  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .          48,380         5,242            1 .9              0 .2    21,652        2,521             0 .9              0 .1
Arkansas  .  .  .  .  .  .  .  .  .  .  .  .  .  .            44,014         3,536            3 .7              0 .3    43,003        3,347             3 .7              0 .3
California  .  .  .  .  .  .  .  .  .  .  .  .  .  .          76,452         4,738            0 .5                 –    71,874        5,089             0 .5                 –
Colorado  .  .  .  .  .  .  .  .  .  .  .  .  .  .            33,969         3,424            1 .5              0 .1    18,602        2,035             0 .8              0 .1
Connecticut  .  .  .  .  .  .  .  .  .  .  .  .              104,332         4,883            6 .4              0 .3   104,197        5,883             6 .4              0 .3
Delaware  .  .  .  .  .  .  .  .  .  .  .  .  .  .            65,449         4,802           16 .4              1 .1    58,119        3,735            14 .8              0 .8
District of Columbia  .  .  .  .  .  .                        73,476         4,056           25 .2              1 .3   572,256       13,897            72 .4              0 .8
Florida  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .       91,586         5,628            1 .2              0 .1    50,954        4,245             0 .7              0 .1
Georgia  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .         119,140         6,433            3 .0              0 .2   119,273         6,556            3 .0              0 .2
Hawaii  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .         4,935         1,133            0 .8              0 .2     4,880         1,393            0 .8              0 .2
Idaho  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .      38,600         3,598            6 .1              0 .6    16,677         1,842            2 .7              0 .3
Illinois .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .   198,936         8,311            3 .6              0 .1   191,046         7,704            3 .4              0 .1
Indiana  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .      162,191         6,398            5 .8              0 .2   113,438         6,060            4 .1              0 .2
Iowa  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .    68,769         2,788            4 .8              0 .2    72,482         3,446            5 .0              0 .2
Kansas .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .        102,230         5,150            7 .7              0 .4   111,158         5,028            8 .4              0 .4
Kentucky  .  .  .  .  .  .  .  .  .  .  .  .  .  .           115,904         5,757            6 .6              0 .3   138,776         6,001            7 .8              0 .3
Louisiana  .  .  .  .  .  .  .  .  .  .  .  .  .  .           41,724         3,452            2 .2              0 .2    54,238         4,827            2 .8              0 .2
Maine  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .      27,855         2,576            4 .7              0 .4    10,562         1,614            1 .8              0 .3
Maryland  .  .  .  .  .  .  .  .  .  .  .  .  .  .           500,637       12,628            18 .3              0 .4   223,634         8,172            9 .1              0 .3
Massachusetts .  .  .  .  .  .  .  .  .  .                   136,843        6,138             4 .5              0 .2   196,931         7,640            6 .3              0 .2
Michigan  .  .  .  .  .  .  .  .  .  .  .  .  .  .            85,559        3,915             2 .2              0 .1    44,407         3,361            1 .1              0 .1
Minnesota  .  .  .  .  .  .  .  .  .  .  .  .  .              71,556        3,186             2 .8              0 .1    77,074         3,342            3 .0              0 .1
Mississippi  .  .  .  .  .  .  .  .  .  .  .  .  .            92,602        5,806             8 .1              0 .5    45,889         3,572            4 .2              0 .3
Missouri  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .        156,253        6,114             6 .0              0 .2   193,835         7,970            7 .4              0 .3
Montana .  .  .  .  .  .  .  .  .  .  .  .  .  .  .            6,827        1,146             1 .5              0 .3     5,819         1,466            1 .3              0 .3
Nebraska  .  .  .  .  .  .  .  .  .  .  .  .  .  .            28,034        2,634             3 .2              0 .3    45,923         3,026            5 .1              0 .3
Nevada  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .           25,112        2,702             2 .2              0 .2    31,936         3,335            2 .7              0 .3
New Hampshire  .  .  .  .  .  .  .  .  .                     107,062        4,674            17 .0              0 .7    63,195         3,070           10 .8              0 .5
New Jersey  .  .  .  .  .  .  .  .  .  .  .  .               548,040       12,944            14 .0              0 .3   282,295        8,405             7 .8              0 .2
New Mexico  .  .  .  .  .  .  .  .  .  .  .  .                24,582        3,304             3 .0              0 .4    21,704        2,656             2 .7              0 .3
New York  .  .  .  .  .  .  .  .  .  .  .  .  .  .           233,990        9,032             2 .8              0 .1   556,295       14,236             6 .4              0 .2
North Carolina  .  .  .  .  .  .  .  .  .  .                 100,320        7,010             2 .5              0 .2   104,319        6,000             2 .6              0 .1
North Dakota  .  .  .  .  .  .  .  .  .  .  .                 14,119        2,019             4 .1              0 .6    43,812        3,006            11 .6              0 .7
Ohio  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .   151,760        5,776             3 .1              0 .1   153,054        5,447             3 .1              0 .1
Oklahoma  .  .  .  .  .  .  .  .  .  .  .  .  .               44,359        3,146             2 .8              0 .2    33,110        3,327             2 .1              0 .2
Oregon .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .         38,275        3,213             2 .4              0 .2    84,219        5,110             5 .2              0 .3
Pennsylvania  .  .  .  .  .  .  .  .  .  .  .                299,970        8,713             5 .4              0 .2   248,693        8,757             4 .6              0 .2
Rhode Island  .  .  .  .  .  .  .  .  .  .  .                 75,143        4,783            15 .6              0 .9    59,696        4,378            12 .8              0 .9
South Carolina  .  .  .  .  .  .  .  .  .  .                  96,459        5,781             5 .1              0 .3    67,333         5,255            3 .6              0 .3
South Dakota  .  .  .  .  .  .  .  .  .  .  .                 10,869        1,322             2 .8              0 .3    16,052         1,830            4 .1              0 .5
Tennessee  .  .  .  .  .  .  .  .  .  .  .  .  .             102,514        5,910             3 .9              0 .2   148,220         6,564            5 .5              0 .2
Texas  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .     126,741        7,189             1 .2              0 .1   109,746         5,824            1 .0              0 .1
Utah  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .    15,744        1,812             1 .3              0 .2    15,962         2,599            1 .3              0 .2
Vermont  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .          21,457        1,613             7 .2              0 .5    20,999         2,245            7 .1              0 .7
Virginia .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .      353,492       11,790             9 .5              0 .3   245,241         8,079            6 .8              0 .2
Washington  .  .  .  .  .  .  .  .  .  .  .  .               106,585        5,079             3 .6              0 .2    59,033         4,719            2 .0              0 .2
West Virginia  .  .  .  .  .  .  .  .  .  .  .                85,538        4,534            12 .1              0 .6    68,849         3,754           10 .0              0 .5
Wisconsin  .  .  .  .  .  .  .  .  .  .  .  .  .             111,719        4,246             4 .2              0 .2    65,318         4,410            2 .5              0 .2
Wyoming  .  .  .  .  .  .  .  .  .  .  .  .  .  .              7,575        1,579             2 .8              0 .6    14,498         1,762            5 .2              0 .6
Puerto Rico  .  .  .  .  .  .  .  .  .  .  .  .                1,320           538            0 .1              0 .1      683            339            0 .1                –

     – Represents or rounds to zero .
     1
       Data are based on a sample and are subject to sampling variability . A margin of error is a measure of an estimate’s variability . The larger the margin of error
in relation to the size of the estimates, the less reliable the estimate . When added to and subtracted from the estimate, the margin of error forms the 90 percent
confidence interval .
     Note: Estimates do not include workers who worked at home .
     Source: U .S . Census Bureau, 2011 American Community Survey .


10                                                                                                                                                      U.S. Census Bureau
Table 7.
Top Commuting Flows From Residence State to Workplace State: 2011
(For information on confidentiality protection, sampling error, nonsampling error, and definitions, see www.census.gov/acs/www/)
                                                                                                                                                                 Number of                   Margin of
          Sending (residence) state                                                                   Workplace state
                                                                                                                                                                   workers                   error1 (±)
New Jersey  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .               New York  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .             396,520                      11,490
Maryland  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .           District of Columbia  .  .  .  .  .  .  .  .  .  .  .  .                         330,171                      10,226
Virginia .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .      District of Columbia  .  .  .  .  .  .  .  .  .  .  .  .                         226,407                       9,251
New York  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .           New Jersey  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .                 128,891                       6,429
New Jersey  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .               Pennsylvania  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .                  123,650                       5,307
Pennsylvania  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .                New Jersey  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .                 121,698                       5,768
Maryland  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .           Virginia .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .        113,150                       5,702
Missouri  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .        Kansas .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .           95,599                       4,594
Kansas .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .        Missouri  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .           87,257                       4,744
New Hampshire  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .                     Massachusetts .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .                      85,567                       4,196
Illinois .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .   Missouri  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .           80,630                       4,795
Washington  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .               Oregon .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .           73,498                       4,666
Virginia .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .      Maryland  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .              68,236                       4,840
Connecticut  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .              New York  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .              66,652                       4,027
Indiana  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .      Illinois .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .      63,276                       4,619

     1
       Data are based on a sample and are subject to sampling variability . A margin of error is a measure of an estimate’s variability . The larger the margin of error
in relation to the size of the estimates, the less reliable the estimate . When added to and subtracted from the estimate, the margin of error forms the 90 percent
confidence interval .
     Source: U .S . Census Bureau, 2011 American Community Survey .



have experienced notable changes                                                                            interviewed in 2011. The estimates                    survey data such as editing, review-
in long commuting rates over                                                                                based on this sample approximate                      ing, or keying data from question-
time. While such community-level                                                                            the actual values and represent                       naires. For more information on
analysis is beyond the scope of this                                                                        the entire U.S. resident household                    sampling and estimation methods,
short report, some of the measures                                                                          and group quarters population.                        confidentiality protection, and
presented here, including out-of-                                                                           Sampling error is the difference                      sampling and nonsampling errors,
state and out-of-county commuting                                                                           between an estimate based on                          please see the 2011 ACS Accuracy
rates and travel time indicators, are                                                                       a sample and the corresponding                        of the Data document located at
available to the public for smaller                                                                         value that would be obtained if the                   <www.census.gov/acs
geographic summary levels such as                                                                           estimate were based on the entire                     /www/Downloads/data_documen-
metro areas or counties.6 Such data                                                                         population (as from a census).                        tation/Accuracy/ACS_Accuracy_of
may be obtained from the                                                                                    Measures of the sampling errors                       _Data_2011.pdf>.
U.S. Census Bureau’s American                                                                               are provided in the form of margins
                                                                                                                                                                  For more information about the
FactFinderII site.7                                                                                         of error for all estimates included
                                                                                                                                                                  commuting patterns of U.S. work-
                                                                                                            in this report. All comparative
SOURCE AND ACCURACY                                                                                                                                               ers, go to the U.S. Census Bureau’s
                                                                                                            statements in this report have
                                                                                                                                                                  Journey to Work and Migration
The data presented in this report                                                                           undergone statistical testing, and
                                                                                                                                                                  Statistics Branch Web site, at
are based on the ACS sample                                                                                 comparisons are significant at the
                                                                                                                                                                  <www.census.gov/hhes
                                                                                                            90 percent level unless otherwise
                                                                                                                                                                  /commuting/>, or contact the
                                                                                                            noted. In addition to sampling
    6
      For information on out-of-state and out-                                                                                                                    Journey to Work and Migration
of-county commuting rates, see ACS Table                                                                    error, nonsampling error may be
B08007; for information on travel time, see                                                                                                                       Statistics Branch at 301-763-2454.
                                                                                                            introduced during any of the opera-
ACS Table B08012.
    7
      See <www.Factfinder2.census.gov>.                                                                     tions used to collect and process




U.S. Census Bureau                                                                                                                                                                                  11

				
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