Issued February 2013

ACS-20

American Community Survey Reports

Out-of-State and Long Commutes: 2011

By Brian McKenzie

U.S. Department of Commerce

Economics and Statistics Administration

U.S. CENSUS BUREAU

census.gov

A complex set of factors influences variation in commuting patterns across the United States, and multiple 

indicators may be considered when assessing such patterns. Among other factors, the relationship between 

home and work is influenced by community development patterns, labor market shifts, and technological 

changes that expand workers’ options for where and 

how to work. The American Community Survey (ACS) 

provides critical information about several aspects of 

commuting for U.S. workers. The ACS is an ongoing 

survey conducted annually by the U.S. Census Bureau 

that captures changes in the socioeconomic, housing, 

and demographic characteristics of communities across 

the United States and Puerto Rico.1

The ACS questions related to travel focus solely on the 

work trip and do not ask about leisure travel or other 

nonwork trips. Among other commuting questions, 

the ACS asks respondents in the workforce about their 

principal workplace location and the number of minutes it usually takes to get from home to work, one 

way. This report uses 2011 ACS data at the state level 

to explore two commuting indicators related to travel 

time and work location: (1) the percentage of commuters with long commutes (commutes of 60 minutes or 

longer) and (2) the percentage of workers who work 

1 The ACS uses a series of monthly samples to produce annual 

estimates. Detailed questions that previously appeared on the decennial census long form are now included in the ACS, and the decennial 

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 

to ensure respondent confidentiality for smaller communities and for 

small geographic units such as census tracts or block groups. For 

larger geographies, specifically those with populations of 65,000 or 

greater, estimates are available annually. For selected geographies 

with populations of 20,000 or greater, combined 3-year estimates 

are available.

outside of their state of residence. These topics are 

subsets of a much broader, more complex set of travel 

time and place indicators. The media occasionally discuss such commuting patterns within several contexts, 

including health, interstate commuter taxes, and shifts 

in the housing and labor markets. This report may 

serve as a baseline statistical reference point for such 

discussions. Unless otherwise noted, estimates refer to 

the working population who did not work at home. 

HIGHLIGHTS

• Among U.S. workers who did not work at home,

8.1 percent had commutes of 60 minutes or longer 

in 2011.

• An estimated 61.1 percent of workers with “long 

commutes” drove to work alone, compared with 

79.9 percent for all workers who did not work

at home.

• New York shows the highest rate of “long commutes” 

at 16.2 percent, followed by Maryland and New 

Jersey at 14.8 and 14.6 percent, respectively.

• The District of Columbia has the highest rate of outof-state commuters among its resident workers at 

25.2 percent, followed by Maryland at 18.3 percent.

• Among all people who work in the District of 

Columbia, 72.4 percent live outside the District 

of Columbia.

COMMUTES OF 60 MINUTES OR LONGER

As a relative concept, the definition of a long commute 

varies across people and communities. For simplicity, this report defines long commutes as those of 60 
2 U.S. Census Bureau

minutes or longer (one way). This 

threshold is well above the national 

average travel time of 25.5 minutes in 2011. Figure 1 shows that 

the national average travel time 

fluctuated little between 2000 and 

2011. The 60-minute travel time 

threshold is also roughly twice that 

of metro areas with the longest 

average travel times, which exceed 

30 minutes. For example, in 2011, 

workers in the New York City metro 

area and the Washington, DC, 

metro area had the two longest 

average travel times among metro 

areas, at 34.9 minutes and 34.5 

minutes, respectively. 

Table 1 lists the distribution of 

commuting times across several 

intervals. The percentage of workers with commutes of 60 minutes 

or longer was 8.1 percent in 2011. 

Shorter travel time categories 

accounted for a relatively high 

percentage of commuters. For 

example, 15.5 percent of workers 

had commutes of 15 to 19 minutes, 

and 14.8 percent had commutes of 

20 to 24 minutes. The percentage 

of workers with commutes of 60 

minutes or longer was 8.0 percent 

in 2000, and this proportion has 

fluctuated little between 2000 and 

2011, when it reached 8.1 percent 

(Figure 2). Commutes of 90 minutes or longer (“extreme commutes”) showed similar stability 

across years, at 2.8 percent in 2000 

and 2.5 percent in 2011. Although 

this report focuses on commutes 

of 60 minutes or longer, reference 

to commuting rates of 90 minutes 

or longer illustrates the stability of 

travel time patterns at the national 

level, even among the most 

extreme commutes. This trend may 

be contrary to popular assumptions 

about national travel time patterns, 

which are likely to be informed 

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Figure 1. 

Average One-Way Travel Time for U.S. Workers:

2000–2011

(Data based on sample. For information on confidentiality protection, 

sampling error, nonsampling error, and definitions, see 

www.census.gov/acs/www/)

Source: U.S. Census Bureau, Census 2000 and 2006–2011 American Community Surveys. 

Minutes

What Is The American Community Survey? 

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>.
U.S. Census Bureau 3

by local trends that show more 

variation. For the remainder of the 

report, “long commutes” will refer 

to those of 60 minutes or longer. 

Rates of long commutes vary 

across residence and workplace 

community types throughout metropolitan areas (Table 2).2 Workers 

residing outside of a principal city 

(in a metropolitan area) and working in a principal city show the 

highest rate of long commutes, at 

12.5 percent. Among workers who 

travel 60 minutes or longer, those 

living and working outside of a 

principal city but in a metro area, 

had the lowest rate of long commutes, at 6.6 percent, a rate lower 

than that of workers living and 

working in principal cities, at 7.1 

percent. Among workers engaging in a “reverse commute,” that is, 

living in a principal city and working outside of a principal city, 9.0 

percent reported a long commute. 

Among workers living outside of 

a metro area, 7.1 percent had a 

long commute.

The distribution of transportation 

modes used by workers with long 

commutes differs from that of the 

general worker population (Table 

3). Among workers with long commutes, only 61.1 percent drove 

to work alone, compared with 

79.9 percent for all workers who 

worked outside the home. Workers 

with long commutes had a notably 

higher rate of public transportation 

usage at 23.0 percent, compared 

with 5.3 percent for the general 

worker population. This difference might be expected, given 

2 For more detailed information about the 

Office of Management and Budget’s (OMB) 

standards for delineating metropolitan and 

micropolitan statistical areas, visit

<www.census.gov/population/metro/>. This 

analysis uses 2003 OMB metro area

definitions. 

Figure 2.

Percentage of Workers With One-Way Commutes of 

60 and 90 Minutes or Longer: 2000–2011

(Data based on sample. For information on confidentiality protection, 

sampling error, nonsampling error, and definitions, see 

www.census.gov/acs/www/)

Source: U.S. Census Bureau, Census 2000 and 2006–2011 American Community Surveys. 

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Percent

60 minutes or longer

90 minutes or longer

Table 1.

Travel Time to Work: 2011

(For information on confidentiality protection, sampling error, nonsampling error, 

and definitions, see www.census.gov/acs/www/)

One-way travel time interval Percentage of workers Margin of error1 (±)

Less than 10 minutes . . . . . . . 13.4 0.1

10 to 14 minutes . . . . . . . . . . . 14.3 0.1

15 to 19 minutes . . . . . . . . . . . 15.5 0.1

20 to 24 minutes . . . . . . . . . . . 14.8 0.1

25 to 29 minutes . . . . . . . . . . . 6.1 0.1

30 to 34 minutes . . . . . . . . . . . 13.7 0.1

35 to 44 minutes . . . . . . . . . . . 6.4 0.1

45 to 59 minutes . . . . . . . . . . . 7.5 0.1

60 or more minutes . . . . . . . . . 8.1 0.1

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.
4 U.S. Census Bureau

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 otherwise 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.

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/)

Home and workplace metropolitan area component Total number of 

workers

Margin of

error1 (±)

Percentage of

workers

Margin of

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.
U.S. Census Bureau 5

that the average travel time for 

public transportation commuters is 

consistently longer than that of the 

general working population. Rail 

travel accounted for 11.8 percent 

of workers with long commutes, 

and other forms of public transportation accounted for 11.2 percent. 

Air travel is not included as a 

separate category in the ACS travel 

mode question, so it is not possible 

to determine the percentage of 

commutes by this mode. 

Table 4 shows the number and percentage of workers with long commutes for each state, organized by 

residence in each state and workers 

in each state. Figure 3 presents a 

map of the same information. For 

workers living in a given state, New 

York shows the highest rate of long 

commutes at 16.2 percent, followed by Maryland and New Jersey 

at 14.8 percent and 14.6 percent, 

respectively.3 These states and several others with high rates of long 

commutes among resident workers contain or are adjacent to large 

metropolitan areas. Workers in 

large metro areas such as New York 

City and Washington, DC, generally 

have longer average travel times 

than those in smaller metro areas. 

The map illustrates spatial patterns 

associated with long commutes. 

Several states in the Northeast have 

a high percentage of workers with 

3 Values for Maryland and New Jersey are 

not statistically different from one another.

long commutes, while a distinct 

pocket of the Midwest, including 

Nebraska, Kansas, South Dakota, 

and Iowa, has comparatively low 

rates of long commutes. 

Focusing on workers working in a 

given state rather than residing in 

it (Table 4), workers in the District 

of Columbia showed the highest 

rate of long commutes. 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. The District of Columbia 

is followed by New York, with 18.2 

percent of its workers reporting 

long commutes. A high percentage 

of long commutes among a state’s 

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/)

Commute mode Total number of 

workers

Margin of

error1 (±)

Percentage of

workers

Margin of

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.
6 U.S. Census Bureau

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/)

State

Workers living in specified state, commuting

60 minutes or longer

Workers working in specified state, commuting

60 minutes or longer

Total 

Margin of

error1 (±) Percent 

Margin of

error1 (±) Total 

Margin of

error1 (±) Percent 

Margin of

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.
U.S. Census Bureau

7

DC

TX

CA

MT

AZ

ID

NV

NM

CO

IL

OR

UT

KS

WY

IA

NE

SD

MN

FL

ND

OK

WI

MO

WA

AL GA

AR

LA

MI

IN

PA

NY

NC

MS

TN

VA

KY

OH

SC

ME

WV

MI

VT

NH

MD

NJ

MA

CT

DE

RI

AK

HI

Figure 3.Percentage of Workers Living in State With Commutes of 60 Minutes or Longer: 2011(Data based on sample. For information on confidentiality protection, sampling error, nonsampling error, and definitions, see www.census.gov/acs/www)

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

Percent of workers

Less than 4 percent4 to 5.9 percent6 to 8.9 percent9 to 11.9 percent12 percent or greater

National average: 8.1 percent
8 U.S. Census Bureau

workers may reflect several travel 

characteristics, such as long travel 

distances, high levels of congestion, 

or a diverse set of commute modes. 

At 3.8 percent of U.S. workers in 

2011, out-of-state commutes represent a small portion of all workers, 

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 

higher than the 7.4 percent of long 

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. Interstate commutes may be relatively 

short, often reflecting incidental 

state boundaries that transect large 

expanses of urbanized space. Subsequent sections provide several 

Figure 4. 

Average Travel Time by Workplace Location: 2011

(In minutes. Data based on sample. For information on confidentiality 

protection, sampling error, nonsampling error, and definitions, see 

www.census.gov/acs/www/)

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

Worked outside

state of residence

Worked in

state of residence

All workers

25.5 24.7

44.8

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/)

Workplace location Total number of

workers

Margin of

error1 (±)

Percentage of

workers

Margin of

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.
U.S. Census Bureau 9

examples of metro areas that 

straddle two or more states. 

OUT-OF-STATE COMMUTES

Table 6 provides estimates for 

two concepts of out-of-state commuting. The first set of estimates 

shows the number and percentage 

of workers who worked outside of 

their state of residence, and the 

second set of estimates shows the 

number and percentage of workers who worked in a given state 

and lived outside of that state.4

Estimates in Table 6 do not include 

workers who worked at home. The 

District of Columbia showed the 

highest rate of out-of-state commuters among its resident workers 

at 25.2 percent, followed by Maryland at 18.3 percent. Maryland and 

the District of Columbia represent 

states with a high degree of reciprocal residence-to-workplace ties. 

About 12.0 percent of Maryland 

workers commute to the District of 

Columbia for work, and about 13.0 

percent of District of Columbia 

workers commute to Maryland. 

Table 6 also shows the percentage 

of people who work in a state

that is different from their state

of residence. The District of

Columbia stood out as a work location with a particularly high rate 

of out-of-state workers. Among all 

people who work in the District 

of Columbia, 72.4 percent live in 

a different state. The District of 

Columbia is unique among states 

in that it is geographically small, 

the entire area is urban, and it 

serves as a job center for all of its 

adjoining counties in Maryland and 

Virginia. Together, persons living 

4 Includes the District of Columbia and 

Puerto Rico.

in Maryland and Virginia accounted 

for 70.4 percent of all workers

who work in the District of

Columbia. No other state’s workforce exceeded 20.0 percent in its 

rate of out-of-state commuters. In 

addition to the District of Columbia, five states, all with relatively 

small populations, had rates of 

10.0 percent or higher. Among 

these are several geographically 

small states in the Northeast, 

including Delaware, Rhode Island, 

and New Hampshire. At 11.6 percent, North Dakota also showed a 

relatively high rate of workers who 

live in a different state, with Minnesota accounting for the largest 

share of out-of-state workers, at 

29,449.

Information about commuting 

activity between two specific

geographic areas helps define

commuting patterns and provides

a gauge of economic interconnectedness. When combined, information about workers’ residence location and workplace location form 

the basis of residence-to-workplace 

“commuting flows.” For a list of 

state-to-state commuting flows

and associated margins of error 

available for download, see

<www.census.gov/hhes

/commuting/>. This table provides 

the number of commuters who 

live in a given state and travel to a 

different state for work. It shows 

considerable variation across 

states in attracting workers from 

other states. For example, only 

four states draw 100 or more 

workers who reside in Alaska, 

but states such as California and 

Texas draw 100 or more workers from more than 40 different 

states. While some commuters may 

routinely fly to far-away states for 

work purposes, readers should 

assume that many of these crosscountry trips represent infrequent 

work-related travel.5

Table 7 shows 15 of the top stateto-state commuting flows according to the number of workers commuting from one state to another. 

Consistent with patterns in Table 

6, Table 7 shows a high degree of 

interconnectedness among states 

that make up large metropolitan 

areas in the Northeastern United 

States. It also shows a considerable 

degree of reciprocal exchange of 

workers among several state pairs, 

such as New Jersey and New York, 

and New Jersey and Pennsylvania. 

Contiguity and spatial proximity 

clearly exert influence on commuting activity between states. Commuting flow patterns for several 

state pairs are largely driven by 

commutes that occur within one 

large metro area that spans two 

or more states. For example, a 

great deal of commuting between 

Missouri and Kansas takes place 

within the Kansas City metro area, 

and Portland, Oregon’s, suburbs 

in Washington state account for 

much of the commuting between 

those states. 

While the percentage of long commutes has changed little at the 

national level, some communities 

5 The ACS asks respondents in the workforce about their principal workplace location 

during the reference week, a week that may 

not represent their typical commute. Placeof-work data show some workers who made 

atypical daily work trips (e.g., workers who 

lived in New York and worked in California). 

Such cases may represent workers who 

worked during the reference week at a location that was different from their usual place 

of work, such as people away from home on 

business.
10 U.S. Census Bureau

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/)

State

Workers living in state, but working in

different state

Workers working in state, but living in

different state

Total 

Margin of

error1 (±) Percent 

Margin of

error1 (±) Total 

Margin of

error1 (±) Percent 

Margin of

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.
U.S. Census Bureau 11

have experienced notable changes 

in long commuting rates over 

time. While such community-level 

analysis is beyond the scope of this 

short report, some of the measures 

presented here, including out-ofstate and out-of-county commuting 

rates and travel time indicators, are 

available to the public for smaller 

geographic summary levels such as 

metro areas or counties.6 Such data 

may be obtained from the

U.S. Census Bureau’s American

FactFinderII site.7

SOURCE AND ACCURACY

The data presented in this report 

are based on the ACS sample 

6 For information on out-of-state and outof-county commuting rates, see ACS Table 

B08007; for information on travel time, see 

ACS Table B08012. 7 See <www.Factfinder2.census.gov>.

interviewed in 2011. The estimates 

based on this sample approximate 

the actual values and represent 

the entire U.S. resident household 

and group quarters population. 

Sampling error is the difference 

between an estimate based on 

a sample and the corresponding 

value that would be obtained if the 

estimate were based on the entire 

population (as from a census). 

Measures of the sampling errors 

are provided in the form of margins 

of error for all estimates included 

in this report. All comparative 

statements in this report have 

undergone statistical testing, and 

comparisons are significant at the 

90 percent level unless otherwise 

noted. In addition to sampling 

error, nonsampling error may be 

introduced during any of the operations used to collect and process 

survey data such as editing, reviewing, or keying data from questionnaires. For more information on 

sampling and estimation methods, 

confidentiality protection, and 

sampling and nonsampling errors, 

please see the 2011 ACS Accuracy 

of the Data document located at 

<www.census.gov/acs

/www/Downloads/data_documentation/Accuracy/ACS_Accuracy_of

_Data_2011.pdf>.

For more information about the 

commuting patterns of U.S. workers, go to the U.S. Census Bureau’s 

Journey to Work and Migration

Statistics Branch Web site, at 

<www.census.gov/hhes

/commuting/>, or contact the

Journey to Work and Migration

Statistics Branch at 301-763-2454.

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/)

Sending (residence) state Workplace state Number of

workers

Margin of

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.