COU NCI L O F ECO NO MIC ADVI S ER S IS SU E BRI EF

JULY 2015

 

MAPPING THE DIGITAL DIVIDE 

“Today high speed broadband is not a luxury, it’s a necessity.” – President Obama, January 14, 2015 

Introduction 

The United States has long been the world leader at 

creating and deploying the Internet. From the original 

ARPANET through today’s advanced mobile networks, 

American engineers, companies, and consumers have 

pioneered advances in networking, applications, and 

content. Today, nearly every American can access the 

Internet, and the United States leads the world in the 

availability of advanced wireless broadband Internet 

services, such as 4G LTE. 

The benefits of this technological revolution, however, 

have not been evenly distributed. Millions of Americans 

still do not regularly use a computer, and research shows 

that there remain substantial disparities in both Internet 

use and the quality of access. This “digital divide” is 

concentrated among older, less educated, and less 

affluent populations, as well as in rural parts of the 

country that tend to have fewer choices and slower 

connections. 

Closing the digital divide can increase productivity and 

open ladders of opportunity, and President Obama has 

made expanding broadband Internet access a priority of 

his Administration. Since 2009, investments from the 

federal government have led to the deployment or 

upgrading of well over 100,000 miles of network 

infrastructure, while 45 million additional Americans 

have adopted broadband. The President’s ConnectED

initiative aims to connect 99 percent of American 

students to high-speed broadband in their classrooms by 

2018. And in January of this year, the President 

announced several steps that the Administration would 

take to ensure fast and reliable broadband is available to 

more Americans at lower cost, including efforts to 

promote community-based broadband and a call for 

State and local governments to roll back short-sighted 

regulations that restrict competition. 

 

1

 PUMAs are geographic areas defined for statistical use. 

PUMAs are built using census tracts and counties, nest 

within States, contain roughly 100,000 residents, and 

cover the entire United States. 

This report examines the state of the digital divide using 

new data from the Census’ 2013 American Community 

Survey (ACS), which we link with the most recent version 

of the National Broadband Map (NBM). The large scale 

of the ACS allows us to examine Internet use at a level of 

granularity that was not previously possible. Our most 

important findings illustrate how the digital divide 

reflects factors that influence the demand for Internet, 

such as household income, and also the costs of 

providing it (e.g. population density). Although we 

consider several potential explanations for the digital 

divide, our main goal is not to measure the causal impact 

of any particular factor, but rather to characterize 

disparities in Internet access and adoption as they exist 

today. 

Overall, the evidence shows that we have made 

progress, with the largest gains occurring for those 

groups that started with the least. While this suggests 

the beginning of convergence toward uniformly high 

levels of access and adoption, there is still a substantial 

distance to go, particularly in our poorest neighborhoods 

and most rural communities, to ensure that all 

Americans can take advantage of the opportunities 

created by recent advances in computing and 

communications technology. 

Mapping the Digital Divide 

The digital divide can be measured in many different 

ways, and we begin by considering the relationship 

between Internet use and household income across 

different areas of the entire United States. In Figure 1, 

each dot represents a single Public Use Microdata Area, 

or PUMA, containing roughly 100,000 residents.1

 The 

graph plots the share of residents in each PUMA who 

report that they use the Internet at home against the 

median household income for the same PUMA.2 

2

 The specific question item we used to calculate the share 

of households using the Internet was 2013 ACS question 

10, “At this house, apartment, or mobile home—do you or 

any member of this household access the Internet?” Thus, 

1
The figure shows a strong positive association between 

median income and Internet use. The most affluent 

PUMAs generally have home Internet adoption rates of 

80 to 90 percent, while the PUMAs with the lowest 

median incomes have adoption rates of around 50 

percent. Estimates from a linear regression suggest that 

doubling a PUMA’s median household income is 

associated with a 20.2 percentage point increase in the 

expected rate of Internet adoption.3

 In principle, higher 

income might lead to more Internet use, or vice versa. 

However, the fact that nearly all Americans have access 

to basic Internet service strongly suggests that income 

disparities are the dominant factor in explaining this 

relationship. 

Table 1 uses differences in educational attainment and 

race, rather than income, to measure the digital divide. 

In the 2013 ACS, less than half of households headed by 

someone who did not graduate high school had a home 

Internet connection, compared to over 90 percent of 

 

we do not include householders that only access the 

Internet at a public location, such as a school or library, in 

our measure of Internet adoption. Following the 

convention that Census uses in its public reports on 

computer and internet use, group quarters are excluded 

from these estimates, and a household is only counted as 

having internet access, if it reports having a subscription. 

households headed by a college graduate. Black and 

Hispanic households are also 16 and 11 percentage 

points less likely to have an Internet connection than 

white households, respectively, while Native American 

households trail white ones by 19 percentage points. 

3

 If we examine home-computer use rather than home 

Internet use, the overall pattern is very similar (although 

average computer adoption rates are higher (most so for 

the poorest 20% of households), and regression estimates 

suggest that doubling median household income is 

associated with a 19.3 percentage point increase in the 

probability of having a computer at home. 2001 2003 2007 2009 2013

All Households 50.6 54.7 61.5 68.7 74.4

Race of head of household

White alone 56.0 59.9 66.7 73.3 77.4

Black alone 31.0 36.2 44.8 54.2 61.3

Asian alone N/A 66.7 75.5 80.5 86.6

Native American Alone 38.5 41.6 41.3 53.4 58.2

Hispanic of any Race 34.3 36.0 43.2 52.7 66.7

Educational attainment of head of household*

 Less than High School 17.5 19.8 24.0 32.2 43.8

 High School Graduate 40.4 43.8 49.5 57.4 62.9

 Some College 57.8 62.6 68.5 74.8 79.1

 Bachelor's degree or higher 75.3 78.7 83.6 88.5 90.1

*Internet access by educational attainment is displayed here for those households where the head of the household is 

aged 25 or older.

Source: Census, Current Population Survey (2001, 2003, 2007, 2009); Census, American Community Survey (2013); CEA 

calculations.

Table 1: Percent of U.S. Households with Internet Access, 2001 to 2013 

2
However, Table 1 also shows that the digital divide has 

narrowed considerably since 2001. During that period, 

the largest increases in Internet adoption occurred for 

the demographic groups with the lowest initial adoption 

rate. For example, between 2001 and 2013, home 

Internet use has increased by 30.3 percentage points 

among black households, compared to 21.4 percent 

among white households. Similarly, Internet use grew by 

26.3 percentage points among those without a High 

School education compared to 14.8 percentage points 

for those with a bachelor’s degree. 

Figure 2 provides a third perspective on the digital divide 

by graphing the relationship between age and home 

Internet use in 2013 for persons with different levels of 

household income.4 While Internet use declines with 

age, this negative correlation is much stronger for 

Americans in the lowest quartile of household income. 

Figure 2 also shows that there is a strong positive 

relationship between income and Internet use even after 

accounting for age. For example, a 90 year old in the top 

quartile of the household income distribution is more 

likely to have an Internet connection in their home than 

a person of any age in the bottom quartile of the income 

distribution. 

There are several possible explanations for the patterns 

in Internet use illustrated above. Perhaps the simplest 

explanation is that Internet access is costly, and those 

with more income are more likely to be able to afford it. 

Indeed, a 2010 FCC survey found that 36 percent of nonadopters cited expense as the primary driver of their 

decision. However, factors like age and income may also 

be correlated with the non-monetary costs and benefits 

that an individual or a household derives from Internet 

use.5 For example, a recent review of broadband 

adoption by the Government Accountability Office cited 

not only affordability but also lack of perceived relevance 

and lack of necessary computer skills as the primary 

barriers to broadband Internet adoption. Moreover, if 

demographically similar households tend to locate close 

together, correlations between household 

demographics and Internet adoption may reflect shared 

variation in costs and prices. The next section of this 

report sheds some light on this latter possibility by 

examining the geography of Internet use. 

The Geographic Divide 

Figure 3 is a map of the United States that illustrates 

county-level rates of home Internet adoption in 2013.6

The map highlights the digital divide between urban and 

rural locations that has been documented in previous

research. For example, there are large areas of dark 

green (representing the top quintile of Internet 

adoption) in the Northeast corridor from Boston to 

Washington, around Chicago and its suburbs, and along 

the California coast from San Diego to the San Francisco 

Bay. The rural South, and those portions of the 

Southwest that are predominantly home to tribal and 

Indian lands, all host large numbers of counties that 

exhibit Internet adoption rates in the lowest quintile for 

all counties nationwide. 

 

4

 Note that a person is counted as using the Internet at 

home if they live in a household with a subscription, 

regardless of whether they are the primary user. 

5

 For example, a 2011 study by the NTIA found that among 

those who lack home Internet access, 67 percent of the 

those over age 65 say that they simply lack interest, 

compared to only 26 percent of those aged 16 to 44 who 

offer the same explanation. 

6

 Because the ACS does not provide county-level data, we 

use the Geographic Correspondence Engine tool

developed by the University of Missouri Census Data 

Center to allocate PUMA-level Internet adoption rates to 

counties based on each PUMA’s share of a county’s total 

population.

Lowest Income 

Quartile (<$26k)

Second Income 

Quartile ($26k-$52k)

Third Income 

Quartile ($52k-

$93k)

Highest Income 

Quartile ($93k+)

0

20

40

60

80

100

Less

than

10

10 to

20

20 to

30

30 to

40

40 to

50

50 to

60

60 to

70

70 to

80

80 to

90

90 or

Older

Figure 2: Home Internet Use by Age and Income (2013)

Percent

Source: American Community Survey, Census

Age Range

3
Figure 3: Internet Adoption in United States by County: 2013 

While the map in Figure 3 strongly suggests an urbanrural divide, it also reveals several rural areas that have 

relatively high rates of Internet adoption. Examples 

include much of the Northern Great Plains and several 

counties in Montana, Wyoming, North Dakota, Colorado 

and Utah. This suggests that even though geography is 

known to have a large impact on costs, other factors can 

influence Internet adoption even after conditioning on 

geography. 

International comparisons also show relatively high U.S. 

Internet adoption given geography. In particular, Norway 

and Switzerland are the only two OECD countries that 

have both higher rates of Internet use and a larger share 

of the population living in rural locations.7 Nevertheless, 

in terms of overall Internet adoption, the United States 

falls in the middle of the pack of more developed OECD 

countries, and well behind a group of Nordic countries 

that have individual Internet adoption rates above 90 

percent. 

 

7

 This is based on combining data on Internet adoption 

from the International Telecommunications Union with 

To examine the idea that there may still be an association 

between income and Internet adoption in the United 

States, even after conditioning on geography, we can 

focus on variation within individual cities. Figure 4 

presents a series of maps of Washington, DC, 

Philadelphia, PA and San Antonio, TX. The maps in the 

left column illustrate the rate of Internet adoption (by 

quintile) in all of the PUMAs associated with each city, 

and the maps in the right column show the mean 

household income (by quintile) for each PUMA. 

Overall, the maps illustrate two points: there is 

substantial within-city variation in Internet adoption, and 

this variation is strongly correlated with household 

income. San Antonio provides a good example. Several 

PUMAs in the central city fall into the lowest quintile of 

U.S PUMAs for both Internet adoption and household 

income, while its northern suburbs are in the highest 

quintile of U.S. PUMAs for both Internet and income. 

Moreover, because central San Antonio is denser than its 

northern suburbs, this example suggests that income 

the share of rural population from the World 

Development indicators. 

4
Figure 4: Internet Adoption and Income in Select Cities by PUMA (2013) 

Table 2: Internet Use (Percentage) by Income and Population Density 

<56 56-67 67-85 >85 Total:

< 167 61 70 77 82 67

168-551 65 72 79 85 75

552-1,520 62 73 80 86 78

>1,520 62 72 77 86 76

Total: 62 72 78 86 74

S ou rce: Cen s u s , Am erican Com m u n ity S u rvey (2013); NTIA/FCC, Nation al Broad b an d Map ; CEA calcu lation s .

Pop. Density 

(persons/sq. mi.)

Yearly Household Income (Thousands of Dollars)

5
(which is closely linked to a host of other socio-economic 

variables) can be more important than population 

density (which is really a proxy for the cost of service) for 

explaining adoption. 

Taken together, the national and city-level maps suggest 

that both income and geography help explain the digital 

divide. To assess the relative importance of these factors, 

Table 2 divides all of the country’s PUMAs into 16 

categories, based on population density and household 

income, and examines the rate of home Internet 

adoption in the 2013 ACS.8

The numbers in the bottom row and the rightmost 

column of Table 2 show that Internet use increases with 

both population density and household income. 

However, there are indications that income explains 

more of the total variance in Internet adoption. In 

particular, moving from the bottom to the top quartile in 

household income is associated with a 24 percentage 

point change in a PUMA’s average Internet use, 

compared to a 9 percentage point change as one moves 

from the bottom to the top quartile in terms of 

population density. Most of the relationship between 

population density and Internet use is evident when 

comparing PUMAs from the lowest quartile of density to 

the rest of the population. This indicates that the effects 

of geography are non-linear and are concentrated 

among the most remote households.9 

The Broadband Divide 

While the digital divide is typically associated with 

disparities in Internet adoption, it can also be measured 

in terms of service quality. Data from the National 

Broadband Map have been used in prior research to 

highlight disparities in the availability of high-speed 

Internet connections in different locations. Figure 5 uses 

data from the NBM to illustrate the share of the U.S. 

population with access to Internet connections operating 

at various speeds, based on the maximum advertised 

download speed in the location where they live.10

 

 

8

 Because the thresholds used to define these categories 

are somewhat arbitrary, we used the quartiles of density 

and income distribution, so there are an equal number of 

PUMAs in each row and each column of the table (though 

not necessarily in each cell). 

9

 Indeed, grouping PUMAs in just four quartiles masks 

potentially large differences between the most remote 

Figure 5: Availability of High-Speed Internet 

Connections by Population 

Density and Household Income Level 

Affordability aside, almost all Americans have the option 

of purchasing an Internet connection with an advertised 

download speed of 10 Megabits per second (Mbps) – fast 

enough to stream a high definition movie. Near universal 

access to 10 Mbps Internet represents a large 

improvement over past quality of service indicators, and 

provides a sign that Americans are benefiting from 

broadband infrastructure investments, both public and 

private. 

households and those closer to the 25th percentile of the 

density distribution. 

10 To link the NBM and ACS data sets, we used the 

Geographic Correspondence Engine tool developed by the 

University of Missouri Census data center. 

Lowest Quartile 

(<167 persons/sq. 

mi.)

Second Quartile 

(168-551 

persons/sq. mi.)

Third Quartile 

(552-1,520 

persons/sq. mi.)

Source: Census, American Community Survey; NTIA/FCC, National Broadband Map; CEA 

Calculations

Highest Quartile 

(>1,520 

persons/sq. mi.)

0

20

40

60

80

100

3 Mbps 10 Mbps 25 Mbps 50 Mbps 100 Mbps 1 Gbps

Internet Speed Availability by Population Density

Percent of Population

Advertised Download Speed

6
Table 3: Population Share Using Fiber Optic Connection by Household Income and Population Density 

(Availability in Parentheses) 

However, the rapid growth of streaming video and the 

use of many devices within a household means that 10 

Mbps is in many cases no longer sufficient. This is why 

the FCC recently updated its definition of a “broadband” 

connection to require download speeds of 25 Mbps or 

greater. At that level, Figure 5 shows that there is still a 

substantial gap between urban and rural communities, 

as well as between the wealthiest PUMAs and the least 

affluent. In 2013, only 63 percent of persons in the 

lowest population density quartile PUMAs could get 25 

to 50 Mbps connections, and just 40 percent could access 

the Internet at 100 Mbps. There is also a broadband 

availability gap of roughly 20 percentage points between 

the wealthiest and least wealthy communities for 

advertised download speeds of 25 Mbps up to 100 Mbps. 

Finally, Figure 5 shows that very few Americans have 

access to the highest download speeds of 1 Gigabit per 

second (Gbps) or more. However, that end of the market 

is evolving rapidly, and future expansions of the network 

may replicate the disparities we currently observe at 

lower speeds. The only technology presently used to 

deliver residential Internet download speeds of 1 Gbps is 

a fiber-optic cable. Some Internet service providers are, 

however, starting to deploy gigabit-per-second service 

using cable modems. Table 3 illustrates large disparities 

in access to and use of consumer fiber. In the least dense 

and lowest income U.S. communities, just 10 percent of 

the population has access to a fiber connection, and only 

5 percent actually use one. In the wealthiest urban 

locations, 44 percent of the population have access to 

 

11 Note that the total count of wireless providers includes 

fixed wireless providers, which consumers typically use in 

a manner that is more similar to wireline internet. As a 

fiber and 21 percent actually purchase fiber access to the 

Internet. 

Table 2 showed how income explains more of the 

variance in Internet adoption than population density. 

Here, the relationship is more subtle. In particular, Table 

3 shows that moving from the lowest to the highest 

quartile of population density has a larger effect on the 

availability of fiber access than moving from the lowest 

to the highest income quartile. However, these same 

changes are both associated with a 10 percentage point 

increase in the use of a fiber optic connection. The fact 

that population density is more important for explaining 

access to fiber may reflect differences between the cost 

of bringing a new fiber optic cable to a consumer and 

upgrading an existing cable or telephone network. 

Similarly, differences in pricing (which we do not 

observe) may explain why only about half of those with 

access to fiber actually purchase that type of service. 

The Competitive Divide 

A final way to measure the digital divide emphasizes 

disparities in competition. Prior research shows that the 

number of wireline service providers declines rapidly at 

speeds greater than 25 Mbps. Table 4 shows the average 

number of wireline and wireless Internet service 

providers for all U.S. PUMAs by income and population 

density.11 There is clearly more competition in wireless 

than wireline access across all markets. Moreover, both 

wireline and wireless competition increase with 

population density, but are not strongly influenced by 

income levels. 

result, the number of wireless providers in Table 4 is 

overestimated from a conceptual perspective, meaning 

that the number of wireline providers is undercounted. 

<56 56-67 67-85 >85 Total:

< 167 5 (10) 7 (17) 7 (18) 9 (14) 6 (14)

168-551 6 (14) 6 (15) 8 (18) 10 (19) 8 (16)

552-1,520 8 (24) 10 (25) 13 (32) 16 (34) 13 (30)

>1,520 9 (31) 13 (35) 15 (37) 21 (44) 16 (38)

Total: 7 (18) 8 (21) 11 (26) 17 (35) 11 (25)

S ou rce: Cen s u s , Am erican Com m u n ity S u rvey (2013); NTIA/FCC, Nation al Broad b an d Map ; CEA calcu lation s .

Pop. Density 

(persons/sq. mi.)

Yearly Household Income (Thousands of Dollars)

7
Table 4: Average Number of Wireline and Wireless Service Providers by PUMA 

Figure 6 examines the relationship between wireline 

competition and home Internet adoption. Each orange 

dot in the Figure represents a PUMA whose population 

density is below the median for all U.S. PUMAs, and each 

blue dot a PUMA whose population density is above the 

median. The separation between the orange and blue 

dots illustrates the strong positive relationship between 

population density and wireline competition. However, 

Figure 6 also shows that there is a positive correlation 

between the number of wireline competitors and the 

rate of Internet adoption in less dense PUMAs. For 

PUMAs with higher levels of population density, there 

does not appear to be any relationship between wireline 

competition and Internet adoption. A linear regression 

analysis confirms that in low-density (orange) PUMAs, 

each additional wireline competitor is associated with a 

6.3 percentage point increase in Internet use, while there 

is no statistically significant relationship between 

wireline competition and Internet use in high-density 

(blue) PUMAs.12

 

12 We performed the same analysis using the number of 

wireless rather than wireline service providers, and found 

a smaller (but still statistically significant) effect in less 

Although Figure 6 highlights a statistical link between 

wireline competition and Internet adoption in rural 

markets, it is important to recognize that causality in this 

relationship could run in both directions. In particular, 

competition can stimulate adoption by leading to lower 

prices, higher quality, and more choice. At the same 

time, low levels of demand (or expected adoption)—

dense rural markets, and no statistically significant impact 

in high density urban markets. 

<56 56-67 67-85 >85 Total:

Wireline

< 167 1.8 2.0 2.0 2.4 1.9

168-551 2.4 2.4 2.6 2.8 2.6

552-1,520 2.9 2.8 3.0 3.1 3.0

>1,520 3.4 3.3 3.3 3.2 3.3

Total: 2.4 2.4 2.8 3.1 2.7

Wireless

< 167 4.2 4.9 5.0 5.1 4.6

168-551 5.3 5.4 5.6 5.5 5.5

552-1,520 5.2 5.3 5.4 5.4 5.4

>1,520 5.8 5.7 5.6 5.4 5.6

Total: 4.9 5.2 5.4 5.4 5.3

S ou rce: Cen s u s , Am erican Com m u n ity S u rvey (2013); NTIA/FCC, Nation al Broad b an d Map ; CEA calcu lation s .

Pop. Density 

(persons/sq. mi.)

Yearly Household Income (Thousands of Dollars)

20

40

60

80

100

0 1 2 3 4 5 6 7

Percent Using Internet

Average Number of Wireline Choices

Source: Census, American Community Survey; NTIA/FCC, Broadband Map; CEA Calculations.

Rural

Urban

Figure 6: Number of Provider Choices and Internet Use

8
combined with high costs of service provision—may lead 

to a dearth of competition. 

Conclusion 

The Internet can have a dramatic impact on our 

productivity and quality of life. Internet users have vast 

amounts of information literally at their fingertips, and 

an Internet connection allows individuals to 

communicate, collaborate, and transact on a global scale 

in ways that were unimaginable only a few years ago. 

One study by a former Chairman of CEA uses data on the 

amount of time Internet users spend online to estimate 

that Internet access produces thousands of dollars of 

consumer surplus per user each year. 

Closing the gap—between those who experience these 

social and economic benefits from Internet use, and 

those who do not—will require further efforts to reduce 

barriers in affordability, relevance, and computer 

literacy. The President’s broadband agenda tackles each 

of these challenges in turn, including infrastructure 

investments and robust competition policy to ensure 

widespread access to affordable high-quality Internet; 

spectrum policy to ensure that the dramatic growth in 

wireless broadband continues; and investments in 

education and training, especially for children, to remove 

computer literacy barriers that impede universal access. 

The digital divide is likely both a cause and a 

consequence of other demographic disparities, and 

sorting out the precise impact of closing the divide is 

more difficult than characterizing the current disparities, 

as we have done here. Policies that aim to close the 

divide are pursued in recognition of the fact that the 

opportunities afforded by Internet access should be 

accessible to every American, much like other universally 

available utilities such as water and electricity. Expanding 

broadband access is an important part of a larger middleclass economic policy agenda, both to support economic 

growth and to extend access to opportunity to more 

Americans. 

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10