United States 

Department of 

Agriculture

Economic 

Research 

Service

Economic 

Research 

Report 

Number 78

August 2009

Peter Stenberg, Mitchell Morehart, Stephen Vogel, 

John Cromartie, Vince Breneman, and Dennis Brown

Broadband Internet’s 

Value for Rural America
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Broadband Internet’s value for rural America.

 (Economic research report (United States. Dept. of Agriculture. 

Economic Research Service); no. 78)

 1. Internet—Economic aspects—United States. 

 2. Rural development—United States.

 I. Stenberg, Peter.

 II. United States. Dept. of Agriculture. Economic Research Service. 

III. Title.

HF54.56

www.ers.usda.gov

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United States

Department

of Agriculture

www.ers.usda.gov

A Report from the Economic Research Service

Abstract

As broadband—or high-speed—Internet use has spread, Internet applications requiring 

high transmission speeds have become an integral part of the “Information Economy,” 

raising concerns about those who lack broadband access. This report analyzes (1) rural 

broadband use by consumers, the community-at-large, and businesses; (2) rural broadband availability; and (3) broadband’s social and economic effects on rural areas. It also 

summarizes results from an ERS-sponsored workshop on rural broadband use, and other 

ERS-commissioned studies. In general, rural communities have less broadband Internet 

use than metro communities, with differing degrees of broadband availability across rural 

communities. Rural communities that had greater broadband Internet access had greater 

economic growth, which conforms to supplemental research on the benefits that rural 

businesses, consumers, and communities ascribe to broadband Internet use.

Keywords: Internet, broadband, high-speed Internet, rural economies, rural economic 

growth, digital economy, telemedicine, rural, urban, Census data, June Agricultural 

Survey, Agricultural Resource Management Survey (ARMS), ERS, USDA

Acknowledgments

The authors thank the many outstanding and practical comments from Mary Bohman, 

Patrick Sullivan, Jim Johnson, Robert Gibbs, Erik Dohlman, and the Peer Review 

Coordinating Council (USDA-Economic Research Service); John Allen ( Utah State 

University); Mary Campanola (USDA-Rural Development); William Chambers 

(USDA-Farm Service Agency); and an anonymous university reviewer. Thank you to 

the workshop participants (listed in the appendix) whose research helped our research 

immeasurably. Thanks to USDA-National Agricultural Statistics Service and the Federal 

Communications Commission whose data were critical in our research. Special thanks 

to Chris Dicken, Ryan Williams, and David Nulph for their excellent GIS support. Also 

special thanks to Dale Simms and Cynthia A. Ray for their superlative editorial and 

design assistance.

Peter Stenberg, Mitch Morehart, Stephen Vogel, 

John Cromartie, Vince Breneman, and 

Dennis Brown

Broadband Internet’s Value 

for Rural America

Economic

Research

Report

Number 78

August 2009
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Contents

Summary. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . iii

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1

The Internet Economy. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

Broadband Internet Adoption and Use . . . . . . . . . . . . . . . . . . . . . . . . . . . 5

 Dial-Up Versus Broadband Internet Use . . . . . . . . . . . . . . . . . . . . . . . . . 5

 Rural Internet Use . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7

Further Factors in Rural Broadband Use . . . . . . . . . . . . . . . . . . . . . . . . 10

Geography of Rural Broadband Providers. . . . . . . . . . . . . . . . . . . . . . . 14

Broadband’s Effect on the Rural Economy. . . . . . . . . . . . . . . . . . . . . . . 20

Rural Communities and Broadband Internet Use . . . . . . . . . . . . . . . . . 23

 Community Interactions and the Internet . . . . . . . . . . . . . . . . . . . . . . . . 23

 Telemedicine and Telehealth . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24

 Distance Education . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25

 The Service Sector in the Internet Economy . . . . . . . . . . . . . . . . . . . . . 25

 Telework . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26

Broadband Availability Leads to Use . . . . . . . . . . . . . . . . . . . . . . . . . . . 28

 Broadband Adoption on the Farm. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28

 Rural Broadband Availability and Adoption . . . . . . . . . . . . . . . . . . . . . 29

Broadband Internet Use and Rural Businesses. . . . . . . . . . . . . . . . . . . . 31

 Rural Businesses and Broadband . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31

 Rural Retailers and Broadband . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32

 Farm Businesses and Broadband . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32

 Farm-Rural Linkages in the Internet Economy. . . . . . . . . . . . . . . . . . . . 36

Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38

References. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40

Appendix A: Bureau of the Census Regions . . . . . . . . . . . . . . . . . . . . . . 47

Appendix B: Data Used in the Study . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48

Appendix C: Using the FCC Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50

Appendix D: Modeling Broadband Use on the Farm. . . . . . . . . . . . . . . 59

Appendix E: Quasi-Experimental Design . . . . . . . . . . . . . . . . . . . . . . . . 60

Appendix F: Economic Research Service’s Broadband Workshop, 

September 29-30, 2008. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61
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Summary

The Internet has become widely, but not universally, available. Two-thirds 

of U.S. adults had in-home Internet access by 2008. Rural businesses and 

consumers have become almost as likely as their urban counterparts to use 

the Internet, though broadband—or high-speed—access is less prevalent in 

rural areas than in more densely populated areas. The 2008 Farm Act reauthorized USDA’s telemedicine, distance learning, and rural broadband access 

grant and loan programs. 

What Is the Issue?

Broadband access is viewed as necessary to fully utilize the Internet’s potential. As the Internet economy has matured, more applications now require 

higher data transmission rates, even in the case of simple shopping websites. 

In a recessionary economy a number of Internet activities—including job 

searches and home businesses—may become more critical for households. 

Whereas an estimated 55 percent of U.S. adults had broadband access at 

home in 2008, only 41 percent of adults in rural households had broadband 

access. Evidence suggests that some of this shortfall in broadband use is 

involuntary, and may be due to the higher cost of broadband provision or 

lower returns to broadband investment in sparsely populated areas. 

What Did the Study Find?

Analysis suggests that rural economies benefi t generally from broadband 

availability. In comparing counties that had broadband access relatively early 

(by 2000) with similarly situated counties that had little or no broadband 

access as of 2000, employment growth was higher and nonfarm private earnings greater in counties with a longer history of broadband availability. 

By 2007, most households (82 percent) with in-home Internet access had a 

broadband connection. A marked difference exists, however, between urban 

and rural broadband use—only 70 percent of rural households with in-home 

Internet access had a broadband connection in 2007, compared with 84 

percent of urban households. The rural-urban difference in in-home broadband adoption among households with similar income levels refl ects the 

more limited availability of broadband in rural settings.

Areas with low population size, locations that have experienced persistent 

population loss and an aging population, or places where population is 

widely dispersed over demanding terrain generally have diffi culty attracting 

broadband service providers. These characteristics can make the fi xed cost 

of providing broadband access too high, or limit potential demand, thus 

depressing the profi tability of providing service. Clusters of lower service 

exist in sparsely populated areas, such as the Dakotas, eastern Montana, 

northern Minnesota, and eastern Oregon. Other low-service areas, such as 

the Missouri-Iowa border and Appalachia, have aging and declining numbers 

of residents. Nonetheless, rural areas in some States (such as Nebraska, 

Kansas, and Vermont) have higher-than-expected broadband service given 

their population characteristics, suggesting that policy, economic, and social 

factors can overcome common barriers to broadband expansion.
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In general, rural America has shared in the growth of the Internet economy. 

Online course offerings for students in primary, secondary, post-secondary, 

and continuing education programs have improved educational opportunities, especially in small, isolated rural areas. And interaction among students, 

parents, teachers, and school administrators has been enhanced via online 

forums, which is especially significant given the importance of ongoing 

parental involvement in children’s education.

Telemedicine and telehealth have been hailed as vital to health care provision in rural communities, whether simply improving the perception of 

locally provided health care quality or expanding the menu of medical 

services. More accessible health information, products, and services confer 

real economic benefits on rural communities: reducing transportation time 

and expenses, treating emergencies more effectively, reducing time missed 

at work, increasing local lab and pharmacy work, and generating savings for 

health facilities from outsourcing specialized medical procedures. One study 

of 24 rural hospitals placed the annual cost of not having telemedicine at 

$370,000 per hospital. 

Most employment growth in the U.S. over the last several decades has been 

in the service sector, a sector especially conducive for broadband applications. Broadband allows rural areas to compete for low- and high-end service 

jobs, from call centers to software development, but does not guarantee that 

rural communities will get them.

Rural businesses have been adopting more e-commerce and Internet practices, improving efficiency and expanding market reach. Some rural retailers 

use the Internet to satisfy supplier requirements. The farm sector, a pioneer in 

rural Internet use, is increasingly comprised of farm businesses that purchase 

inputs and make sales online. Farm household characteristics such as age, 

education, presence of children, and household income are significant factors 

in adopting broadband Internet use, whereas distance from urban centers 

was not a factor. Larger farm businesses are more apt to use broadband in 

managing their operation; the more multifaceted the farm business, the more 

the farm used the Internet.
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How Was the Study Conducted?

This report summarizes all available nationwide data on broadband use and 

availability and analyzes the data to isolate interactions between broadband 

use and economic activities. It also presents results from an ERS-sponsored 

workshop on rural broadband and ERS-commissioned research studies 

conducted by others. The aim is to assess the economic impact of not having 

broadband service on rural communities and their growth, community facilities, access to health care, and well-being, as requested by Congress on 

December 26, 2007. 

We first analyze who uses broadband, what it is used for, and what differences exist between the average urban and rural user to better understand 

the perceived usefulness of the Internet, especially broadband. We then 

identify rural areas that have broadband (by ZIP Code), determine when 

they acquired broadband service, and develop measurements of broadband 

availability over time. We analyze the effect of broadband Internet access 

on the rural economy using quasi-experimental design (QED), which 

allows us to compare two sets of counties alike in most aspects other than 

broadband availability. The results are interpreted using further analysis of 

rural businesses and consumers, including farm business logistic regression analysis, rural-farm linkage logistic regression analysis, and workshop research exploring many complex interactions between the Internet 

and socioeconomic components of the rural community: rural community 

social interactions; telemedicine; distance education; and rural businesses, 

including retail, service, and farm.

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Introduction

The Internet in its infancy was simply an alternative, and quite straightforward, communication device. Electronic mail was sent from one person to 

another. Intrinsically the Internet remains a communications device, but as it 

has grown more universally available, it has become more integrated into the 

rest of the economy. The simple e-mail system of sending a note has evolved 

to incorporate blogs, instant messaging (IM), text messaging, Facebook, and 

Twitter. Business, household, and government activities have moved and 

are moving onto Internet platforms (Greenstein and Prince, 2006; Leamer 

and Storper, 2001). Many Internet activities are self-sustaining as personal 

computers download upgrades and “patches” to their systems and automatic 

ordering, billing, and payment functions are conducted for households and 

businesses. The Internet is integral to the development and functioning of the 

digital or information economy.

Rural communities have not been left out, though from the outset equal 

access to the Internet has been a contentious issue. The farm sector of the 

rural economy helped to pioneer rural Internet use (Stenberg and Morehart, 

2007), and rural businesses and households have become almost as likely as 

their urban counterparts to use the Internet (Stenberg and Morehart, 2008). 

Access to the Internet through broadband (i.e., high-speed) technologies, 

however, has been less prevalent in rural areas than in much more densely 

populated areas of the country (see box, “What Is Broadband?”). Broadband 

Internet access has become the crux of today’s policy debate on equal access 

among urban and rural communities.

Broadband access is viewed as necessary to fully utilize the Internet’s potential (Greenstein and Prince, 2006; Parker, 2000). As the Internet economy has 

matured, more applications now require higher data transmission rates, even 

in the case of simple shopping websites.

The broad scope of the research presented here complements earlier studies 

on rural telecommunication policy by Parker and Hudson (1992), Internet 

access in the Appalachian region by Oden and Strover (2002), and businesses 

in the digital economy by Malecki (2008). 

This report examines (1) what role the Internet plays in the national 

economy; (2) how much, and for what purposes, consumers use the Internet, 

especially what differences might exist between broadband and nonbroadband Internet use by rural and urban consumers, including such uses 

as telemedicine, distance learning, and community involvement; (3) what 

determines whether and how rural businesses use broadband Internet; and 

(4) how broadband Internet affects the broader rural economy. Specifically, 

we address a question posed to ERS by Congress on December 26, 2007, 

concerning broadband’s impact on rural communities and their growth, 

community facilities, access to healthcare, and overall well-being. 

While we attempt to measure the observable economic effects of broadband 

Internet access and use, this study makes no attempt to comprehensively 

examine all the issues surrounding the growth of the Internet. For one, there 

are inherent limitations in measuring the economic impact, or value, of a 

rapidly evolving technology. The telegraph age, for example, ushered in a 
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number of unpredicted developments like the emergence of such companies as Sears Roebuck. This report neither forecasts new developments nor 

addresses social issues pertaining to Internet uses like privacy, chat rooms, or 

parental supervision.

What Is Broadband?

The transmission capacity, or bandwidth, of Internet access has been a major impediment limiting 

the economic returns from online activity. The slower the Internet access speed, the less useful the 

Internet is. Dial-up, which was the primary access method before broadband access became more 

widely available, is the slowest way to connect to the Internet. The highest speed by which data can 

be transferred using dial-up is 56 kilobytes per second (kbps). In rural areas the speed often has been 

much less, with connection speeds of 14 kbps common. Effectively, this consigns rural dial-up users 

to using the Internet for text e-mail messages only. Anything requiring large graphics is simply not 

practical. High-speed Internet access is necessary to make use of much of what is now offered on the 

Internet.

Broadband is the term used to denote high-speed access to the Internet. Although the term has been 

used to refer to other services, such as digital television, the matter of most interest to consumers, 

providers, and policymakers is broadband Internet connectivity (Eisenberg, 2002). With the convergence of video, audio, text, graphics, and other analogous enduring and transient products and services into digital streams that can be transported across the Internet, broadband Internet connections 

have become a necessity for common Internet usages and applications.

The Federal Communications Commission (FCC), though altering the broadband definition recently, 

historically defined 200 kilobits per second in one transmission direction as the minimum speed for 

Internet service to be classified as broadband. Unfortunately, the definition includes a wide array of 

technologies ranging from the old ISDN and T-1 lines to satellite service. Lumping very slow transmission and sometimes unreliable service in with superfast fiber-optic home service makes economic 

impact analysis and discussion of broadband Internet service from historical data challenging.

Most broadband Internet access in U.S. households is through DSL or cable modem technologies 

and is faster than the FCC standard. As of 2007, 55 percent of all households had broadband Internet 

access: 46 percent of these had DSL, 39 percent had cable modem, and 12 percent had wireless connections (PEW). DSL was the first technology to become widely deployed; cable and, more recently, 

fiber-optic lines are becoming the technologies of choice.
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The Internet Economy

In 1995, there were roughly 16 million Internet users across the globe; by 

2008 there were nearly 1.5 billion, about 22 percent of the world’s population. Two-thirds of U.S. adults had in-home Internet access by 2008 (PEW). 

Domain names have grown from 30,000 in 1994 to 168 million in 2008 

(Verisign). Hosts, also known as end-user computers, grew from 1,000 in 

1984 to 570 million in 2008 (Internet Systems Consortium). The Bureau 

of Census reports online retail sales went from $31 billion in 2001 to $107 

billion in 2007. Also according to U.S. census statistics, online wholesale 

trade in 2006 was an estimated $613 billion, or approximately 16 percent of 

sales. Online wholesale trade in farm products was an estimated $5 billion, or 

4 percent of all wholesale farm product sales in 2006.

Online economic activities may be grouped into three broad categories: 

information sharing, purchase channels, and sales channels. Information 

sharing can range from the trivial to critical life or business issues—from 

chat rooms to medical or financial storehouses—and is the most common 

application for businesses and consumers (Hopkins and Morehart, 2001; 

Stenberg, 1999; Varian, 2003). Even when purchases are not consummated online, purchase decisions are facilitated through price discovery or 

consumer information gathering. Real estate and automobiles are just two of 

the markets that have been transformed by price discovery online (Borenstein 

and Saloner, 2001).

The Internet has led to new sources of supplemental income for some 

households. Crafts, for example, that used to be pitched only at annual State 

and county fairs are now marketed year-round to wider audiences, and the 

Internet has led to the rise of auction sites such as E-Bay where anyone can 

be a buyer and seller of new and used goods and services.

For businesses, the Internet has reduced geographic isolation, with information from collaborating businesses or customers instantly available. The 

effective market area for producers has increased, though many businesses 

have not taken advantage of this potential (Brynjolfsson and Smith, 2000; 

Malecki and Moriset, 2007).

The increased speed and quantity of information, however, cannot reduce 

the physical distance that passengers and goods must travel (Malecki and 

Moriset, 2007). It is not clear whether the number of business trips has lessened due to the Internet (i.e., substituting Internet communication for travel). 

Anecdotal evidence suggests that as the price of transportation soared in 

early 2008, businesses cut back on travel (Odlyzko, 2008). Although the 

moving of farm, agricultural, and other physical goods from point A to point 

B involves the same distances as always, the Internet has enhanced the ability 

to track shipments and increased the efficiency of shipping companies.

As the Internet expands the effective market area for businesses, it also 

increases competition. The financial system is a prime example. Banks were 

traditionally local in nature. Historically, each farm community had its own 

bank. The bank held deposits from local residents and, in turn, loaned funds 

out to local farmers and the business community. This has changed, however, 

over the last several decades. First, the regulatory limitations on the markets 
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that banks could serve were relaxed or eliminated. With the new regulatory 

environment and the revolution in telecommunications, the number of locally 

owned banks has declined (DeYoung and Duffy, 2002; Keeton, 2001).

Depositors have increasingly turned to online banks or investment concerns 

that offer higher rates of return for their capital (DeYoung and Duffy). This 

has increased the financial returns of bank depositors, but has reduced the 

profit that local banks accrued from deposits. Many loan applicants have 

gone online to find the best rates and terms for home mortgages, home 

equity, and other loan instruments. This has reduced the cost for the loan 

applicant, but also eroded the profit from individual loans in the bank’s loan 

portfolio. To address this shortfall, many banks have increased their volume 

of transactions, often by increasing their effective market area. This may 

have hastened the consolidation of the financial market over the last 10 years.

E-government is another major development in the digital economy affecting 

rural America. Four kinds of activities fall within this area: information 

dissemination, citizen/customer services, government business transactions, and governance (Gallegos, 2002; Lanvin, 2008). Information typically 

disseminated includes public holidays and events, regulatory actions, issue 

briefs, public schedules, and school lessons and lunch menus. Twelve percent 

of all farms and 22 percent of all farms with Internet access, for example, 

retrieved information from Federal websites, according to analysis of 2007 

June Agricultural Survey (JAS) data.

Citizen or customer services include paying taxes and fees, lodging 

complaints, requesting additional information, scheduling of public facilities, 

and submitting applications for various programs. Four percent of all farms 

and 7 percent of all farms with Internet access conducted business with the 

U.S. Department of Agriculture over the Internet according to analysis of 

2007 JAS data.

Government business transaction costs have fallen for governments able to 

conduct much of their own back-office operations online, including supply 

purchases, bill payments, travel arrangements, and grant/loan operations 

with other agencies (Lanvin, 2002; Crescia, 2006). Governance changes are 

evident in the virtual town hall meetings, online polling, campaigning, and 

voting that characterized the 2008 election cycle.

Both government and the citizenry have benefited from the development of 

e-government via decreased costs to deliver or obtain services, increased 

or enhanced provision of information and services, and improved feedback 

between the citizenry and government (Lanvin).
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Broadband Internet Adoption and Use 

Dial-Up Versus Broadband Internet Use

That households and individuals greatly value the Internet, and especially broadband access to the Internet, is readily apparent from the data. 

Two major data sources directly address individual and household online 

proclivity and activity: the U.S. Bureau of the Census and PEW (PEW 

Internet & American Life Project). The Census Bureau has not collected 

thorough data on online activity since 2003, so we rely on the PEW surveys 

for our understanding of Internet users (see Appendix B for a description of 

this and other data used in this report). Aggregate e-retail, peer-to-peer, webpage access counts, and other such information are not used here because 

such measurements of volume give no information on individual behavior.

The PEW survey data suggest that rural and urban online behavior is alike if 

one controls for type of Internet access. In other words, rural and urban users 

with broadband Internet access have similar online behavior patterns vis-àvis each other; rural and urban users with dial-up Internet access have similar 

online behavior patterns as well. Users with broadband Internet access, 

however, exhibit different online behavior than users with dial-up access.

Among the conclusions drawn from 2008 PEW survey data: 

•	Three-quarters of all adults used the Internet, with 69 percent having

access at home.

•	Fifty-five percent of all adults had broadband access at home.

•	Only 41 percent of adults in rural households had broadband access at

home in 2008. 

Broadband access at home has increased dramatically for both urban and 

rural adults since 2001 (fig. 1).

Figure 1

Trends in home broadband adoption by region

2001 02 03 04 05 06 07 08

0

10

20

30

40

50

60

70

Rural

Urban

Suburban

Percent of households

Source: Horrigan, 2008
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The number of online activities varies between dial-up users and broadband 

users, but not between rural and urban broadband users (Horrigan, 2008).1 

Most Internet users go online everyday and most of these send e-mail or get 

information off the Internet (table 1). Getting information, including visiting 

State and local government websites, is the most common activity. Many of 

the activities, such as hobbies and web-surfi ng, are of a personal nature. Still, 

23 percent of adults used the Internet daily to conduct research for their job. 

Broadband Internet users were more likely than dial-up users to take part in 

any specifi c online activity, such as getting news online. The more data intensive the activity, the greater the difference is between dial-up and broadband 

user participation.

The Internet has reduced the economic involvement of the broker and other 

business middlemen in the economy. More bank transactions, for example, 

are taking place through ATMs or online instead of via tellers. According to 

a PEW survey in 2005, a quarter of all U.S. adults, or 44 percent of all adult 

Internet users, used the Internet for online banking. On any given day, 14 

percent of all U.S. adults perform some online banking activity. Broadband 

users are especially heavy users of online banking services—over 60 percent 

of urban and nearly 50 percent of rural broadband users conducted some 

online banking activity in 2007.

As online data intensiveness increases, broadband access becomes more of 

a necessity. Nearly all online activities are becoming more sophisticated, 

using more data intensive processes; e-mail, for example, is becoming more 

data intensive as people are more inclined to attach photo and video fi les. 

1John Horrigan and a number of other 

researchers whose works are discussed 

at length in this report presented their 

research at the Economic Research Service’s broadband workshop, September 

2008. For a complete listing of participants and papers, see the workshop 

agenda in appendix F.

Table 1

Online activities, 2008

Activity that has ever been done by a user All Internet 

users Dial-up at home Broadband at home

Percent

Use an online search engine 89 80 94

Check weather reports and forecasts 80 75 84

Get news online 73 61 80

Visit a State or local government website 66 55 72

Look online for information about the 2008 election 55 37 62

Watch a video on a videosharing site like YouTube or GoogleVideo 52 29 60

Look online for information about a job 47 36 50

Send instant messages 40 38 44

Read someone else’s blog 33 15 40

Use a social networking site like MySpace, Facebook, or LinkedIn 29 21 33

Make a donation to charity online 20 9 23

Download a podcast 19 8 22

Download or share fi les using peer-to-peer networks 

such as BiTorrent or LiveWire

15 15 17

Create or work on your own blog 12 8 15

Source: Pew Internet & American Life Project Survey, April 2008.
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Broadband access is not uniform across rural and urban America, nor is the 

broadband access transmission rate identical across the country. Any shortfall 

in rural broadband availability is an implicit loss in economic opportunity for 

businesses, consumers, and governments.

Rural Internet Use

While the surveys conducted by PEW indicate popular online activities 

among adults, we turn to the Current Population Survey (CPS) to better 

understand who uses the Internet and where. The most recent CPS data 

are from a survey administered in October 2007. This large sample survey 

does not include any questions on what the Internet is used for or where it 

is accessed outside the home, but it provides a better understanding of who 

uses the Internet and rural-urban regional differences in household online 

proclivity. 

Table 2 shows the share of households in which at least one person went 

online—no matter the technology—at home, school, work, or elsewhere in 

2007. Over 71 percent of all households included one or more members that 

went online during the year. The CPS data suggest a variation across the 

country in the occurrence of going online (table 2). Households in the South 

were the least likely of the four Census regions to go online (see Appendix A 

for a description of the regions).

Nonmetro areas, in aggregate, had a lower percentage of individuals going 

online in 2007. While the variation in overall online use was insignificant 

between regions outside of the South, the same did not hold for nonmetro 

areas. Only in the Northeast was there not a significant dropoff in online 

activity going from metro to nonmetro areas.

Income differences have often been offered as a key explanation for the 

disparity in Internet use by households (Choudrie and Dwivedi, 2006; Flamm 

and Chaudhuri, 2007; Stenberg and Morehart, 2006). Lower income households clearly access the Internet less than higher income households (fig. 2). 

Income, of course, is not the whole story as income is highly correlated with 

or determined by education, age, and other factors, but household income 

by itself does raise an intriguing question: to what extent does use of the 

Internet lead to higher household income, and to what extent does higher 

household income lead to higher levels of Internet use?

Table 2

Households with at least one person going online at home 

or elsewhere, 2007

Metro Nonmetro Total 

Percent

Northeast 71.0 69.5 70.9

Midwest 74.0 65.7** 72.1

South 70.7 58.3** 68.3

West 75.5 68.6** 74.9

Total 72.6 63.3** 71.1

** Metro/nonmetro difference significant at 0.01.

Source: ERS using Bureau of the Census CPS data.
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Over 80 percent of households with annual incomes above $40,000 used the 

Internet during 2007. The rural-urban gap in accessing the Internet—either 

in-home or elsewhere—is not evident between rural and urban households of 

the same income (fig. 2).

Sixty-two percent of all U.S. households had in-home Internet access in 2007 

(table 3). The West had the highest share of households with in-home access, 

partially reflecting the more urbanized population distribution there. A significant dropoff in in-home Internet access is apparent between urban and rural 

households, especially outside the Northeast; fewer than half of rural households in the South had Internet access at home in 2007.

Income is a major factor in whether a household has in-home Internet access 

(fig. 3). Over 70 percent of all households with incomes above $40,000 

had in-home Internet access, and again rural-urban differences are largely 

nonexistent between households of the same income level. The steeper slope 

Figure 2

Households accessing the Internet using any technology 

anywhere, 2007

Source: ERS using Bureau of the Census CPS data.

Household income ($)

Less than

5,000

7,500 to

 9,999

Total

Metro

Nonmetro

Percent of households

12,500 to

14,999

20,000 to

 24,999

30,000 to

34,999

40,000 to

49,999

60,000 to

74,999

100,000 to

149,999

0

10

20

30

40

50

60

70

80

90

100

Table 3

Households with at least one person going online at home 

using any technology, 2007

Metro Nonmetro Total 

Percent

Northeast 64.1 61.0 63.7

Midwest 63.1 53.7** 60.9

South 61.7 46.4** 58.7

West 67.0 56.9** 66.1

Total 63.7 51.9** 61.8

** Metro/nonmetro difference significant at 0.01.

Source: ERS using Bureau of the Census CPS data.
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for in-home access rates versus going online anywhere suggests that affordability may be a factor in Internet access at home.

Most households with in-home Internet access have broadband connections 

(table 4). This rate varies little across regions for urban households. The 

same cannot be said for rural households. A marked difference in broadband 

access exists between urban and rural residents, even in the Northeast. Only 

70 percent of rural households with in-home Internet access had broadband 

access in 2007, versus 84 percent of urban households. The data suggest that 

broadband availability is an issue for rural areas across the country.

The rural-urban dichotomy in broadband access becomes even more apparent 

when household income is taken into account (fig. 4). Income appears 

to be a minor factor in opting for broadband over dial-up for an in-house 

Internet connection. Generally, over 70 percent of Internet users, regardless of income, choose to pay for broadband (fig. 4). Thus, the gap between 

rural and urban household use of broadband suggests that the availability of 

broadband services is more of a challenge for rural than urban households 

(unless there is some systemic difference between rural and urban houseFigure 3

Home internet access by income, 2007

Percent of all households

Source: ERS analysis of Bureau of the Census CPS data.

Household income ($)

Less than

5,000

7,500 to

 9,999

12,500 to

14,999

20,000 to

 24,999

30,000 to

34,999

40,000 to

49,999

60,000 to

74,999

100,000 to

149,999

Total

Metro

Nonmetro

0

10

20

30

40

50

60

70

80

90

100

Table 4

Share of online households with broadband access, 2007

Metro Nonmetro Total 

Percent of online households

Northeast 87.3 68.8** 85.4

Midwest 82.9 70.6** 80.4

South 83.0 67.3** 80.5

West 85.3 75.2** 84.4

Total 84.4 69.7** 82.3

** Metro/nonmetro difference significant at 0.01.

Source: ERS using Bureau of the Census CPS data.
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holds that otherwise could explain the gap). Systemic household differences, 

if they exist, would have to explain why rural households are as likely as 

urban households to use the Internet but do not opt for broadband when they 

already use the Internet at home.

Further Factors in Rural Broadband Use

The presence of children in the household is a contributing factor in a 

household’s having in-home Internet access (Stenberg and Morehart, 2006; 

Choudrie and Dwivedi, 2006). One way in which in-home Internet access may 

improve household well-being is through educational programs. The Internet 

has increased course offerings for students in primary, secondary, postsecondary, and continuing education programs, especially those attending 

small, isolated rural primary and secondary schools. The Internet has also 

improved interaction among students, parents, teachers, and school administrators in primary and secondary education. This is especially significant as 

studies have shown the importance of parental involvement in their children’s 

education (Moore, 2007; Poley, 2008). As a result, education programs drive 

household demand for in-home Internet access. Analysis of the CPS data 

shows households with children have higher rates of in-home Internet access 

and households with teenage children are the most likely to have it (table 5).

Rural households, however, have uniformly less access to in-home Internet 

than urban households across all household composition types. Inasmuch as 

distance education is beneficial to economic well-being, continuation of this 

rural-urban dichotomy could put rural households at a disadvantage.

Once a household has in-home Internet access, the upgrade to broadband is 

seemingly not affected by household composition (table 6). The rural-urban 

gap, however, is more extreme and broadband’s role in distance education 

would seem to put rural households at a further disadvantage.

Figure 4

Households with broadband access by income, 2007

Percent of online households

Source: ERS analysis of Bureau of the Census CPS data.

Household income ($)

Less than

5,000

7,500 to

 9,999

12,500 to

14,999

20,000 to

 24,999

30,000 to

34,999

40,000 to

49,999

60,000 to

74,999

100,000 to

149,999

Total

Metro

Nonmetro

0

10

20

30

40

50

60

70

80

90

100
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In a recessionary economy a number of Internet activities—including job 

searches and home businesses—may become more critical for households. 

The 2007 CPS data give some information on both activities.

Unemployed adults, while less frequent users of the Internet than employed 

persons, still had high “anywhere” access rates (table 7). People not in 

the labor force due to retirement or disability had the lowest rate of online 

activity. Unemployed individuals looking for work were more likely to use 

the Internet than other people not employed. Rural people in the labor force 

had a lower access rate than urban people.

The picture changes for home Internet access, where affordability likely 

becomes an issue for unemployed or disabled/retired persons (table 8). The 

dropoff in use for these groups holds for both rural and urban residents. 

These individuals likely go online at such locations as libraries and schools 

when in-home access becomes unaffordable.

A broadband connection is again the choice for most homes with in-home 

Internet access across all labor force categories (table 9). Regardless of 

labor force status, whether the household is in an urban or rural location, if a 

household has in-home Internet access, the household will most likely have a 

broadband connection.

Table 5

All types of Internet access at home by household composition, 2007

Metro Nonmetro Total 

Percent of households

Not a parent 65.0 53.4** 63.3

No children under 18 years of age 69.7 59.4** 67.7

Only children less than 6 70.8 55.1** 68.7

At least one child 6-13 and none older than 13 72.8 65.4* 71.7

At least one child older than 13 81.4 76.5** 80.6

Total 68.5 58.1** 66.8

** Metro/nonmetro difference significant at 0.01; * difference significant at 0.05.

Source: ERS using Bureau of the Census CPS data.

Table 6

Broadband in homes with Internet access 

by household composition, 2007

Metro Nonmetro Total 

Percent of online households

Not a parent 85.7 71.4** 83.9

No children under 18 years of age 82.3 66.9** 79.7

Only children less than 6 90.5 78.4** 89.1

At least one child 6-13 and none older than 13 87.3 71.8** 85.2

At least one child older than 13 85.4 71.8** 83.3

Total 85.2 70.3** 83.1

** Metro/nonmetro difference significant at 0.01.

Source: ERS using Bureau of the Census CPS data.
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Table 7

Online activity using any access technology 

by labor force status, 2007

Metro Nonmetro Total 

Percent within labor

force category

Employed—At work 83.7 78.6** 82.9

Employed—Absent (on day of survey) 85.9 79.4** 84.8

Unemployed—On layoff 72.8 62.3** 70.6

Unemployed—Looking 77.7 72.8* 76.9

Retired—Not in labor force 52.6 43.7** 50.9

Disabled—Not in labor force 47.1 43.2* 46.1

Total of all adults 77.2 70.6** 76.1

** Metro/nonmetro difference significant at 0.01; * difference significant at 0.05.

Source: ERS using Bureau of the Census CPS data.

Table 8

Home Internet access using any technology 

by labor force status, 2007

Metro Nonmetro Total 

Percent within labor 

force category

Employed—At work 74.8 65.0** 73.3

Employed—Absent (on day of survey) 75.0 65.2** 73.5

Unemployed—On layoff 60.3 49.6** 58.1

Unemployed—Looking 63.8 51.4** 62.0

Retired—Not in labor force 48.8 41.3* 47.4

Disabled—Not in labor force 39.6 34.9* 38.4

Total of all adults 68.5 58.1** 66.9

** Metro/nonmetro difference significant at 0.01; * difference significant at 0.05.

Source: ERS using Bureau of the Census CPS data.

Table 9

Broadband in homes with Internet access by labor force status, 2007

Metro Nonmetro Total 

Percent within labor 

force category

Employed—At work 86.6 72.1** 84.6

Employed—Absent (on day of survey) 87.3 75.5** 85.6

Unemployed—On layoff 75.7 54.2** 72.0

Unemployed—Looking 83.7 72.0** 82.1

Retired—Not in labor force 75.0 59.0** 72.3

Disabled—Not in labor force 75.0 63.2** 72.4

Total of all adults 85.2 70.2** 83.1

** Metro/nonmetro difference significant at 0.01.

Source: ERS using Bureau of the Census CPS data.
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A small but significant number of households have home businesses 

covering a wide range of professions such as farmers, doctors, and artisans 

(table 10). Such households may become more commonplace in the current 

economic downturn as more households try to compensate for loss of jobs or 

reduced work hours by starting home businesses. Home businesses are more 

commonplace in rural areas than urban areas (table 10). In-home Internet 

access is much more common in households with home businesses (81 

percent) than among all households in the aggregate (62 percent). This is true 

for both urban (83 versus 64 percent) and rural home businesses (70 versus 

52 percent).

In summary, a broadband connection is almost the default for a great 

majority of online households. Analysis of the CPS data suggests that more 

rural households would have broadband connections if these connections 

were as readily available as in urban areas, implying lost economic opportunity for some rural households. 

The data, however, also suggest that some of the shortfall in rural Internet 

activity may be due to other factors that precede the decision to get a broadband connection. These factors include the lower average income for rural 

households, higher average age of the rural population, and lesser educational 

attainment of rural residents as compared to their urban counterparts.

Table 10

Internet users by home business status, 2007

Metro Nonmetro Total 

Percent

Households with home businesses 11.7 14.8* 12.2

Home businesses with any kind of home Internet 

access

83.3 70.1** 80.7

Proportion of home Internet access with broadband 87.6 71.3** 84.6

Note: Difference between metro/nonmetro ( *--significant at 0.05, ** -- significant at 0.01).

Source: ERS using Bureau of the Census CPS data.
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Geography of Rural Broadband Providers

Broadband provision follows a geographical pattern tied to population size 

and the urban-rural hierarchy. Limited provision is most strongly associated 

with low population size in a given area, but also exhibits regional patterns 

that reflect differences in urban concentration and challenges associated with 

mountainous terrain. The Federal Communications Commission (FCC) data 

on the number of broadband providers by ZIP Code area (see Appendix B) 

are the only source of geographically detailed information with national 

coverage. More robust findings would come from data measuring the actual 

number of broadband customers and variation in the price of service, rather 

than just the number of companies providing access. The FCC data, however, 

serve as the best available proxy of broadband accessibility. 

Metro ZIP Code areas average 88 square miles apiece and include just 

over 16,700 people on average.2 Nonmetro ZIP Code areas are generally much larger (131 square miles) with far fewer people (3,000) on 

average. Such population diversity drives geographic variation in the cost 

of broadband provision. While U.S. metro areas averaged close to nine 

providers per ZIP Code area in 2006, nonmetro ZIP Code areas averaged 

half that number (fig. 5).

Despite significant expansion, the metro-nonmetro gap in number of 

broadband providers remains and has even widened by some measures 

since 2000, when broadband provision was much more limited in scope. 

It is not surprising that, as broadband access has expanded to encompass 

a large majority of Americans, the remaining areas of limited coverage 

increasingly reflect the higher costs associated with providing service to 

smaller populations.

2Metro and nonmetro categories used 

here are based on the ERS Rural-Urban 

Commuting Areas and are defined using criteria similar to OMB’s countybased metro and nonmetro areas. 

Nonmetro ZIP Code areas are defined 

as those outside urban centers of 

50,000 or more and their surrounding 

commuting zones

Figure 5

Average number of broadband providers per ZIP Code by metro 

versus nonmetro area, 2000-2006

Number of providers

Source: USDA, Economic Research Service, using data from the FCC.

2000 01 02 03 04 05 06

0

1

2

3

4

5

6

7

8

9

Nonmetro

Metro
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Clusters of lower service provision in 2006 highlight clearly discernable 

regional patterns (fig. 6). The northern Great Plains, eastern Oregon, and 

northeastern New Mexico are sparsely populated. The Missouri-Iowa border 

area has experienced persistent population loss and an aging population. 

An extensive area of low service is evident in West Virginia and eastern 

Kentucky, but extends from Tennessee through upstate New York. This 

mountainous terrain, divided by innumerable ridges and narrow valleys, 

impedes broadband service provision to its widely dispersed, rural and 

small-town population. Though topography creates similar challenges in the 

West, people living there tend to concentrate more in towns and small cities, 

making broadband service less expensive to provide to each household.

The Economics of Broadband Delivery

The main economic principles underlying the diffusion and adoption of communication services 

across rural-urban space are twofold: companies invest where they earn the highest returns and 

households adopt if they can afford these services and either need or desire them (Davies, 1979; 

Rogers, 1995). The adoption and use of communication and information services, therefore, are not 

uniform across the country or among income groups.

Here we are interested in differences between rural and urban areas or, in Federal policy terminology, between high-cost and low-cost areas. Residents in rural areas have always faced higher costs 

for telecommunication services than those in urban areas and, at least for the foreseeable future, will 

continue to do so. Economies of scale for the current technology set are at the core of why they face 

higher costs (Stenberg, 2004).

Rural areas are characterized by low population density. With fewer people in any geographic space, 

the per capita costs of providing telecommunication services rise. Fewer customers share in the cost 

of the central office switches, loop maintenance, and other common components of the local telecommunication system.

Rural areas also have few large businesses or government operations. In the United States, private 

business and government use of telecommunication services has indirectly subsidized household use. 

In practice, this has meant that urban telecommunications service providers often charge higher rates 

to their business customers and lower rates to household customers than they would in a perfectly 

competitive market for telecommunication services (Egan, 1996). Rural telecommunications companies often do not have this luxury.

Rural telecommunications service providers must spend more per customer for maintenance and 

repair crews than urban providers. Rural maintenance and repair crews, especially those providing 

services in very remote regions, cover a larger territory than urban crews, resulting in more overtime, 

more travel expenditures, and all the other resultant expenditures that crews face when they are not 

near their home base (National Telephone Cooperative Association, 2000). Rural providers also need 

more resources per customer than urban telecommunications service providers, including duplicate 

facilities and backup equipment, to ensure network reliability (Egan, 1996).
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Access to services of any kind—hospitals, grocery stores, public transportation, Internet—is strongly related to overall population size, the degree 

to which population is concentrated in urban centers, and the population 

of neighboring areas. In the case of broadband service, as measured by the 

FCC data, population size is the predominant explanatory feature. For all 

ZIP Code areas nationally, the very strong (0.6, or 60 percent) correlation 

between population size and service provision in 2000 increased to 0.75 by 

2006 (fig. 7). Thus, low-service areas that remain, though far fewer, are more 

likely to be in sparsely settled territory throughout nonmetro America.

Within nonmetro areas, population size is the strongest predictor of where 

broadband access is likely to be available. Other dimensions of nonmetro 

population distribution, however, strongly correlate as well, especially 

the degree of population concentration as measured by percent urban 

(fig. 8). Correlation between broadband provision and the relative size of 

neighboring ZIP Code areas weakened from 2000 to 2006, as broadband 

provision increased.
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Results of a regression analysis conform to expectations regarding the 

geography of broadband provision driven by relative costs per capita (for a 

description of the ordinary least squares model, see Appendix C). In combination, the three population-based measures explained 63 percent of variation 

in broadband availability. Population size contributed the largest effect, but 

percent urban and size of nearby populations also were significantly related 

to broadband provision in 2006.

Figure 7

Strength of relationship between number of broadband providers 

and population size, 2000-2006

Correlation coefficient

Source: USDA, Economic Research Service, using data from the FCC.

2000 01 02 03 04 05 06

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

All ZIP Code areas Nonmetro ZIP Code areas

Figure 8

Strength of relationship between number of broadband providers in 

nonmetro ZIP Code areas and three population measures, 2000-2006

Correlation coefficient

Source: USDA, Economic Research Service, using data from the FCC.

2000 01 02 03 04 05 06

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

Population size Percent urban Nearby population
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Additional insights may be gained by examining where the number of broadband providers is higher or lower than expected, once these very strong and 

universal population effects are taken into account. This is accomplished by 

mapping the residuals from our regression model for 2006 (see Appendix 

C for an explanation of the model and the variables used). Residuals are 

measured for each ZIP Code area as the difference between the actual 

number of providers in that area and the number of providers predicted by 

the model, based on the area’s population size, urban concentration, and 

proximity to nearby population centers. In the West, higher-than-expected 

service occurs in the most sparsely populated sections (fig. 9). In Nebraska 

and Kansas, including the more densely settled eastern parts, broadband 

provision is higher than expected, compared with most neighboring States. 

Vermont similarly stands out among New England States.
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In Appalachia, broadband service provision is consistently lower than 

expected. The Ozarks in northeastern Arkansas show values similar to 

Appalachia, pointing to the role of topography in influencing broadband 

provision in the eastern half of the United States. 

Higher-than-expected service in Vermont, however, suggests that economic 

and social factors may influence the level of broadband service in nonmetro 

ZIP Code areas. Higher levels of income and education may increase demand 

for broadband. Vermont’s economy depends more heavily on tourism 

and recreation, and its population has high levels of college and technical 

training, especially in engineering, finance, and health. Both these features 

help explain differences in service levels compared with more southern 

Appalachian areas.

The geography of broadband service provision in 2006—in particular, the 

contrast between higher- and lower-than-expected service areas—suggests 

several factors contributing to service gaps beyond basic population barriers. 

First, the variation in broadband coverage is less pronounced in the West, 

especially in the Intermountain West, compared with the Midwest and 

Appalachia. This may be due to a more concentrated population pattern 

(though this analysis accounts for some of this effect by including percent 

urban); a recreation-based economy, attracting tourists who increasingly 

demand broadband availability; or a rapidly growing population made up 

of younger, more educated individuals, including tech-savvy entrepreneurs 

whose businesses depend on being connected to urban-based clients.

Second, Appalachia’s prominence as an underserved area suggests that 

topography significantly increases the cost of providing broadband service 

in this region. Education levels are below the national average, but no more 

than in many Coastal Plain States areas that are better served. The higher 

dependence on mining and other resource-based industries may play a role, 

but lower levels of broadband service exist even in areas of Appalachia 

where retirement and tourism have become important. And if a higher dependence on mining lowers Internet demand, the same is not true for agriculture. 

When population is taken into account, places with higher employment in 

agriculture exhibit higher levels of broadband support. 

Finally, higher-than-expected service in States such as Nebraska, Kansas, and 

Vermont indicate that State-level policies and programs may be behind the 

widespread availability of broadband. Here, we face limitations of data that 

simply show the number of providers in a ZIP Code area and may not always 

reflect differences in costs or level of service. Still, conditions at the State 

level seemingly can transcend economic and social differences that tend to 

handicap some rural areas.
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Broadband’s Effect on the Rural Economy 

Measuring the rural economic effects resulting from investment in broadband is challenging. Separating out the broadband effect from other causal 

factors in economic growth is difficult, especially given that broadband has 

not been available for long and its use has grown rapidly. The methodological approach that we take is called quasi-experimental design, and what 

is undertaken here may be considered an initial step toward ferreting out a 

causal relationship.

Quasi-experimental design (QED) is a statistical approach that simulates an 

ex-post laboratory experiment (Cook and Campbell, 1979). Like a laboratory 

or medical experiment, QED features both a treatment and control group. 

The treatment group is the group undergoing the “cure,” which in this case 

includes areas with some minimum level of broadband availability.

The control group, or the untreated group, serves as the counterfactual to the 

treatment group. In theory, the counterfactual is what would have happened 

to the treatment group if they had not undergone the “cure.” The control 

group provides the baseline forecast. Divergence in the post-treatment period 

is attributed to the effect resulting from the treatment.

Selection of control and treatment in QED (unlike a true laboratory experiment) is not perfectly random, hence the term “quasi.” Treatment groups are 

self-selected. Control groups are selected based on their characteristic similarity with the initial, or pre-treatment, characteristics of the treatment group. 

QED has been utilized in a large body of regional science research. It has 

been used in airport impact studies such as Farnsworth (1972) and Wheat 

(1970), fiscal policies such as Bender and Shwiff (1982), highway infrastructure studies such as Blum (1982) and Isserman (1987), and military base 

closure research such as Isserman and Stenberg (1994).

We use the year 2000 broadband density surface developed from the FCC 

broadband access data (see appendix C, specifically the section on enhancing 

the FCC data). In 2000, broadband was only starting to become widely 

available and it is the first year a broadband likelihood database could be 

constructed. Broadband access is based on the earliest reliable set of data 

from the FCC (according to our discussions with the FCC). Our 2000 likelihood data allow some effect resulting from broadband investment to start to 

appear in rural communities. Information technology takes time to be fully 

utilized after the technology’s introduction (Greenstein, 2000; Bresnahan et 

al., 1999; Greenstein and Prince, 2006).

We selected 228 rural counties for our treatment group that had relatively 

high broadband availability in 2000. For each of these counties, we found 

a rural “twin,” a county that most closely resembles the treatment county 

(outside of broadband availability) based on economic structure (farming, 

manufacturing, retail trade, Federal Government, and State/local government 

income as a percent of total income); spatial structure (population density, 

distance from various city sizes, and presence of interstate highway); and 

income (per capita, unearned, and transfer income) in 2000; as well as the 

growth in population and income from 1990 to 2000. Duplicate counties 
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were not allowed in the control group (see appendix E for further discussion 

of the methodology used).

Our post-treatment period is 2002 through 2006. Year 2006 is the last year 

for which broadband data are available, and the 5-year period provides time 

for an economic effect from broadband service to manifest itself. Due to the 

rapid spread of broadband Internet access, the initial short period may be the 

only period when we are able to detect differences in economic outcomes 

resulting from the availability of broadband access. 

We investigate changes in county employment and income in our QED analysis, and find that total employment grew faster in counties that had greater 

broadband Internet access sooner than in similarly situated rural counties 

without broadband access (table 11). Previous studies (Crandall et al., 2007) 

suggest that employment is not expected to be greatly influenced by broadband access. Simply put, the issue becomes whether the use of broadband 

Internet in business increases productivity, which subsequently either reduces 

actual employment (due to the productivity gain) or increases employment 

(as market share increases). At the county level, however, broadband availability may mean that the county’s employers are more competitive with 

employers in other counties. This would attract both new jobs and potentially 

new employers.

Wage and salary jobs, as well as number of proprietors, grew faster in counties with early broadband Internet access. The farm sector seems largely 

to have been unaffected by broadband Internet access. The farm sector, 

however, seems more likely to embed broadband Internet access into productivity as its basic inputs are more fixed than other sectors of the economy. 

Subsectors of the counties’ economies (not shown here), like wholesale trade, 

generally showed no significant effect from broadband access, though further 

analysis is warranted. The difference in nonfarm jobs starts to disappear as 

other counties get increased broadband access.

Income showed a mixed picture (table 12), though population showed 

greater growth in treatment counties than control counties. The normal yearto-year volatility of farm earnings due to weather and other causal factors 

not accounted for in the QED approach taken here may have been a factor 

in this outcome. Nonfarm earnings showed greater growth corresponding to 

Table 11

Difference in employment growth rates between early broadband and control counties

2002 2003 2004 2005 2006

Total number of jobs 0.003 0.0079* 0.0104* 0.0114* 0.0113

Total number of proprietors -0.0068 0.0072* 0.0199* 0.0280* 0.0363*

 Farm proprietors -0.0001 0.0001 0.0009 0.00197 0.0058

 Nonfarm proprietors -0.0075 0.0048 0.0152* 0.0195* 0.0224*

Wage and salary jobs 0.0062* 0.0092* 0.0088* 0.0075* 0.0053*

 Farm jobs -0.0052 -0.0028 -0.004 -0.0050 -0.0010

 Nonfarm jobs 0.00343 0.0076* 0.0096 0.0101 0.0087

Note: * significant at 10%. 

Source: ERS using selected data from Bureau of the Census and Bureau of Economic Analysis data.
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broadband availability. The difference between control and treatment counties lessens over time as other counties get better broadband access.

Private earnings—all earnings, excluding farm earnings and Federal, State 

and local government earnings—were greater for the treatment counties 

than for the control counties. The results we obtained are consistent with 

the argument that broadband Internet access has a positive effect on rural 

communities.

Our analysis supports the hypothesis that investment in broadband Internet 

access leads to a more competitive economy. Further analysis, however, 

is needed to address the issue of causality more completely. Why and how 

broadband may lead to the results of the QED analysis was the subject of 

other ERS research at the ERS Broadband Workshop. It is the subject of the 

rest of the report.

Table 12

Difference in income and population growth rates between early broadband and control counties

2002 2003 2004 2005 2006

Population (number of persons) 0.0041* 0.0063* 0.0065* 0.0076* 0.0093*

Personal income 0.0141* 0.0064 0.0028 0.0037 -0.0012

Per capita personal income (dollars) 0.0100* -0.0002 -0.0047 -0.0049 -0.012

Private earnings 0.0163* 0.0234* 0.0274* 0.0206* 0.0192

Farm earnings 0.7545 0.0568 0.2863 0.4327 0.5483

Nonfarm earnings 0.0114* 0.0114 0.0126 0.0068 0.0009

Note: * significant at 10%. 

Source: ERS using selected data from Bureau of the Census and Bureau of Economic Analysis data.
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Rural Communities and Broadband Internet Use 

Broadband Internet availability has direct implications for the well-being of 

communities. Limited or nonexistent broadband restricts Internet use in rural 

communities and subsequently the benefits derived from its use. Research 

suggests that broadband use fosters community involvement, enhances the 

provision of services such as health and education, and expands household 

income prospects through such activities as telework.

Community Interactions and the Internet

In the Internet’s infancy some researchers warned that its use would weaken 

community ties, splinter common interests, and erode levels of voluntary or 

community participation, according to Stern et al. (2008). Local communities would be destroyed as people went online and found their own virtual 

communities of shared interest.

Sociological research over the past decade, however, has found this 

concern largely unjustified. In fact, Internet use has been shown to bolster 

community vitality through civic engagement and community participation 

(Stern and Dillman, 2006; Stern et al., 2008; Wellman et al., 1996). The 

concern has now evolved into fear that those with antiquated or no connections to the Internet are systematically being left out of community activities (Stern et al., 2008).

By use of a logistic regression model, Stern et al. showed that the use of 

the Internet is associated with higher degrees of community participation 

across a variety of groups and organizations. People use the Internet to 

receive information via e-mail from organizations or to search out information groups. Using broadband technologies corresponds positively with 

higher levels of passive and active community participation. Stern et al. 

concluded that the quality of Internet access is also important to a community’s sociological well-being, regardless of factors such as income, age, 

education, and race.

Stern and others’ data suggest that rural communities that rely most on 

volunteerism to function might be at a disadvantage as a consequence of 

either a lack of Internet access or an unwillingness to adopt broadband 

technologies. Furthermore, the lack of broadband service may in itself 

discourage the development of proficiencies in using the Internet. In other 

words, sluggish dial-up service may preclude individuals from growing 

efficient in daily Internet use, and thereby attenuate their contribution to 

their local communities.

Broadband Internet services, however, offer more definitive, or at least 

economically measurable, benefits to rural communities. These benefits 

covered during the 2008 ERS broadband workshop span medical, educational, and job services. One particular benefit is telemedicine.
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Telemedicine and Telehealth

Rural communities have long faced challenges in getting adequate local 

health care. Telemedicine and telehealth have been hailed as vital to 

health care provision in rural communities, whether simply improving the 

perception of locally provided health care quality or expanding the menu 

of medical services (Goetz and Debertin, 1996). More accessible health 

information, products, and services confer real economic benefits on rural 

communities and their residents: reducing transportation time and expenses, 

treating emergencies more effectively, reducing time missed at work, 

increasing local lab and pharmacy work, and providing savings to health 

facilities from outsourcing specialized medical procedures (Capalbo and 

Heggem, 1999; Whitacre, 2008).

These benefits have been recognized by Federal policy. The USDA administers a number of programs aimed at improving in-clinic medical technology 

and broadband Internet access to fully utilize medical technologies in rural 

clinics. The 2008 Farm Act (the Food, Conservation, and Energy Act of 

2008) expands these programs.

Telemedicine studies have primarily been case studies on how hospitals 

have adapted to telemedicine or cost-benefit studies for hospitals adapting 

particular telemedicine applications. Whitacre (2008) examined the economic 

benefits from a community perspective. Rural hospital services affect a 

community directly in the health of its citizenry and financially since rural 

hospitals in the States studied are most often partially funded by local 

sales taxes. As a consequence, understanding the full economic potential 

of telemedicine is important in understanding the economic benefit of such 

programs for rural communities. 

Whitacre visited hospitals in 24 rural communities across Arkansas, Kansas, 

Oklahoma, and Texas. Four telemedicine benefits were catalogued: (1) 

hospital savings resulting from outsourcing specific procedures, (2) transportation savings accruing to patients, (3) income savings resulting from reduction in missed work, and (4) increases in local lab and pharmacy work.

Whitacre found wide variation in the way rural hospitals use teleradiology, 

teleoncology, and telepsychiatry, the specific telemedicine services analyzed 

in the study. The biggest benefit noted by hospital staff was in improved 

turnaround for patients. Cost savings for the hospital were typically not great, 

though annual cost savings varied significantly. Transportation savings to 

patients also varied considerably. The estimated transportation cost savings 

for patients not having to go to a more distant hospital after the initial visit 

was estimated to range from $2,000 to $110,000 per year per hospital across 

the 24 hospitals.

Estimated savings to patients who would have missed additional work 

time had they gone beyond their local hospital ranged from $3,000 to 

$70,000 for the 24 rural hospitals. Additional pharmacy and lab work 

that was gained by rural hospitals or their local affiliates was estimated 

to range from $31,000 to $1.5 million per annum. The cost of not having 

telemedicine thus was estimated to average $370,000 per annum for the 24 

rural hospitals. Communities with larger hospitals (2,000 or more patient 
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encounters per month) would be forgoing over $500,000 per year if telemedicine were not offered.

Distance Education

Education has long been shown to contribute positively to individuals’ 

economic well-being as well as to national economic growth (through labor 

productivity gains). Education, also a major factor in the well-being of 

rural America, has been undergoing a transformation because of broadband 

Internet, with promising economic consequences. The institutional changes 

taking place between students, parents, faculty, and education administrators 

are already evident.

School-to-school distance education systems have opened to other provider 

groups that reach beyond schools or learning centers (Poley, 2008). Learners 

include students in K-12 and higher education as well as new immigrants, 

continuing education students, and individuals taking courses for personal 

development. Providers of distance education include universities, community colleges, private companies, communities, professional organizations, 

primary and secondary schools, and individuals.

Learners “attend” anytime during the 24-hour day, at work sites, learning 

centers, and in the home (Poley). Elementary school learners can visit 

educational sites that were introduced in the classroom, complete research 

projects (often with the assistance of parents), and check up on assignments 

while home sick. Their parents also can interact with teachers more freely. 

Secondary school students can enroll in online Advance Placement courses 

and other college-prep and college-level courses.

Distance education for post-secondary institutions also saves resources—for 

schools by reducing overhead and for rural households by reducing travel 

costs. It enables motivated learners to complete a course of study that might 

otherwise be incompatible with their work schedules and parental responsibilities (Poley). The promise for rural residents is increased access to educational resources, at lower costs than without distance learning.

The Service Sector in the Internet Economy 

Most employment growth in the United States over the last several decades 

has been in the service sector, a sector especially conducive for broadband 

applications. Analysis of Bureau of Economic Analysis data shows services 

making up 50 percent of real private gross domestic product (GDP), 60 

percent of personal consumption expenditures, 16 percent of private investment, and 25 percent of total trade in 2007.

As the sector has grown, information technology has increased the sector’s 

productivity and globalized its marketplace. Information technology and the 

service sector are primary drivers of economic growth (Mann, 2008). As the 

global economy has grown, so have markets for information technology and 

services that process or trade through the Internet (Mann, 2006). Information 

technologies have allowed services to be fragmented between nontraded and 

tradable segments, such as back-office operations of financial firms, airline 

reservation offices, and software development for private business.
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During the ERS-sponsored workshop on rural broadband in 2008, Mann 

identified four overarching effects of the Internet on the service sector:

•	Greater international division of labor in services or standardization of

services,

•	Greater supply of intermediate services or fragmentation of services,

•	Greater demand for intermediate services or fragmenting of services, and

•	Globalization of both the supply and demand for services.

This has led to increasing private service sector exports and imports (table 

13), with the United States exporting more services than it imports.

Not all service sector trade is uniformly distributed. Mann (2008) concluded 

that the trade in services has harmed low-wage service work like call centers 

and may continue to do so. Codification of work processes, such as in the 

software industry, also puts some high-wage work at risk of going overseas. 

Broadband allows rural areas to compete for low- and high-end service jobs, 

such as software development, but does not guarantee that rural communities 

will get them.

Telework

Telework is one part of the service sector that could be greatly enhanced by 

broadband Internet. Might rural communities benefit? Do rural communities 

have people that would be interested in and able to work online? Are there 

firms that would be interested in rural sourcing rather than global sourcing 

some of their services? Morris and Goodridge (2008) addressed this during 

the ERS workshop. They surveyed businesses across the country and found 

that approximately 12 percent were engaged in global offshoring of some 

service support activity, mostly (52 percent) to India. 

The major advantages with offshoring cited by businesses were reducing 

costs, freeing up management time, and offering “24/7” customer access. 

Disadvantages were increased incidences of customer dissatisfaction and 

morale problems among domestic employees. The businesses indicated that 

Table 13

Trade in private services, 1997-2006

Exports Imports

1997 2002 2006 1997 2002 2006

Private services ($ million) 83,929 122,207 187,771 43,154 72,604 116,524

Percent of private services

Education services 10 10 8 3 4 4

Financial services 15 18 23 14 13 12

Insurance services 3 4 5 14 30 29

Telecommunications 5 3 3 19 6 4

Source: Mann, 2008.
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57 percent of customers were dissatisfied with outsourced services and only 

15 percent were satisfied. Around three-fourths of these businesses would 

be interested in bringing back some of the jobs if rural employees could be 

recruited. The most common reasons cited for bringing back service jobs 

were increased customer satisfaction (63 percent), favorable government tax 

incentives (53 percent), and ease of identifying skilled labor in rural America 

(51 percent).

Morris and Goodridge conducted three surveys in 2006 and 2007, with 

one drawing on individuals across the entire country. Of rural residents, 

37 percent were very interested in working from home to earn additional 

income, 39 percent were moderately or somewhat interested, and 21 

percent were not interested. Homemakers were least likely to be interested 

in working at home (40 percent), though 30 percent would be interested in 

working anywhere from 11 to 20 hours a week at home. 

Fifty percent of retirees, however, were interested in returning to the workforce, citing flexible schedule, supplemental income, social interaction, 

and intellectual stimulation as inducements. Fifty-four percent of retirees 

nationwide stated that they had broadband Internet access; the rate for rural 

retirees is uncertain, but is likely much lower given our analysis of Current 

Population Survey data. The relative lack of broadband access in rural 

communities may inhibit rural telework opportunities for retirees and others.
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Broadband Availability Leads to Use 

Several questions arise regarding policy intervention in broadband markets. 

Is there pent-up demand for broadband in areas that are unserved or underserved? Does greater availability beget correspondingly greater use of broadband Internet? When terrestrial broadband (DSL or cable) first becomes 

available, pent-up demand would be evident if conversion rates to broadband 

access are higher than in communities that have had terrestrial broadband for 

some time or are served only by satellite broadband. If the adoption rate is 

not higher, then broadband may be oversupplied or satellite is sufficient. A 

higher adoption rate would be another indicator that households do indeed 

value the Internet and broadband’s advantages over the dial-up alternative.

Broadband Adoption on the Farm

The paucity of national geographically specific data presents a challenge 

in trying to analyze whether availability leads to broadband adoption. Data 

from USDA’s June Agricultural Surveys provide a unique opportunity to 

examine geographically specific rural changes in Internet access methods 

(see Appendix B for a discussion of the June Agricultural Surveys). Figure 

10 shows the conversion to broadband Internet access by farms across the 
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country between 2005 and 2007. Unfortunately, a change in area identifiers 

did not allow us to match data for Illinois and Arkansas; hence, these States 

are omitted from the map and our analysis. By conversion we mean farms 

that did not already have broadband Internet access converted to broadband 

Internet access; farms may or may not have had dial-up Internet access.

The data presented in figure 10 show sharp differences in conversion rates 

across the country. When cross-referenced with the FCC broadband availability data (as estimated for likelihood for specific farm locations in 

December 2004 and December 2006, see Appendix C), our analysis of farm 

use of broadband supports the hypothesis that people embrace terrestrial 

broadband when given the option. Roughly 24 percent of all farms using the 

Internet in 2005 already had broadband Internet access of some type, and 

so could not convert. Conversions were nearly nonexistent in areas where 

broadband was available mostly via satellite. 

Farms were unlikely to make the direct jump from no Internet use to broadband Internet access; farms that already had dial-up Internet access were 

more likely to acquire broadband Internet access. DSL service was the most 

common broadband Internet access option among farms, whereas cable and 

fiber optics have shown the largest gains in highly urbanized areas over the 

last few years. The preponderance of DSL service for farms indicates both 

the rural location of most farms and Internet users finding satellite a less 

desirable option.

Rural Broadband Availability and Adoption

Some States collect data on broadband availability, enabling a more refined 

analysis of broadband deployment and adoption. Renkow (2008) examined 

broadband availability and adoption in two such States—Kentucky and North 

Carolina. Kentucky had both broadband availability and adoption data. North 

Carolina had broadband adoption data only. Broadband availability and 

adoption increased substantially during the last several years, with the largest 

proportional gains occurring in counties that had been the least well-served 

at the beginning of the period, typically rural counties. North Carolina had 

higher rates of adoption by all households than Kentucky (fig. 11).

Renkow found that population density was more important than income in 

driving broadband deployment. The relative insensitivity of local income to 

patterns of broadband deployment may indicate that broadband providers 

perceive demand as being highly income inelastic. If so, cost of physical 

infrastructure would be the primary consideration in extending capacity into 

unserved or underserved areas.

The growth of broadband availability even in the most sparsely populated 

counties, however, is striking. More than three-quarters of households in all 

but 8 of Kentucky’s 120 counties had broadband available to them by 2007. 

Seven of these eight counties were the least densely populated counties in the 

State. Interestingly, county adjacency to major urban areas was not related to 

broadband provision, as within-region clustering seems common. In addition, 

Renkow found evidence to suggest that the broadband loan program administered by USDA’s Rural Development Utilities Programs stimulated broadband deployment in rural areas.
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Figure 11

Residential broadband adoption in Kentucky and North Carolina

Percent of households

Source: Renkow, 2008.

Rural with

urban pop.

<2,500

Rural with

urban pop.

2,500−20,000

Rural with

urban pop.

>20,000

Metro

0

10

20

30

40

50

60

70

80

90

100

2005 2007

0

10

20

30

40

50

60

70

80

90

100

2002 2006

Rural with

urban pop.

<2,500

Rural with

urban pop.

2,500−20,000

Rural with

urban pop.

>20,000

Metro

North Carolina

Kentucky

Percent of households
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Broadband Internet Use and Rural Businesses 

One of the salient features of the Internet is its capacity to provide information quickly and cheaply compared to other dissemination methods 

(Henderson et al., 2000). Wider and more convenient access may reduce 

the costs of communicating, transacting, and sourcing information. With 

improved information and knowledge, individuals’ perception of products 

and services provided would be more accurate, thereby improving the adoption of worthwhile technologies and discarding those that have little value 

(Hooker et al., 2001; Just and Just, 2001). As a result, Internet use may 

lead to greater efficiency in the agricultural and other rural business sectors 

(Borenstein and Saloner, 2001; Gloy and Akridge, 2000; Greenstein and 

Prince, 2006). 

Crandall (2008) pointed out during the ERS workshop that the effect 

of information and communications technology (ICT) on productivity 

growth is clear. Overall U.S. labor productivity growth from 1995 to 2000 

was 2.5 percent per year, with an estimated 30 percent of it ascribed to 

ICT-producing and 56 percent due to ICT-consuming sectors of the economy 

(Fuss and Waverman, 2005). Measuring broadband Internet’s contribution 

to this, however, is challenging due to data limitations and the problems 

of separating out overlapping causal effects (Crandall). As a consequence, 

empirical studies directly linking broadband to regional productivity growth 

are largely nonexistent.

Crandall and some of his colleagues, however, studied the effect of broadband 

on output and job growth. In their attempt to establish a relationship between 

State gross domestic product (GDP) or job growth and broadband deployment, 

they conducted a cross-section regression analysis on variables capturing local 

economic characteristics (unionization, business tax, education, wage rates), 

quality-of-life characteristics (climate, mean temperature), and broadband lines 

per capita. They found that total nonfarm employment growth was significantly 

related to broadband lines per capita. The results for GDP were not statistically 

significant. The strongest effects of broadband Internet on employment growth 

were in finance and insurance, real estate, and education services. The results 

largely supported an earlier study by Gillett et al. (2006).

Rural Businesses and Broadband

Pociask (2005) found evidence that rural small businesses did not use broadband as much as their urban counterparts. He attributed the lower usage to 

fewer employees, on average, in rural businesses and higher prices for rural 

broadband service. Socioeconomic characteristics—such as rural-urban 

differences in age, education, and affluence—may also play a role (Pociask, 

2005; Stenberg, 2000). But what does this gap in broadband adoption mean 

for rural businesses?

Lamie et al. (2008) in their ERS workshop paper examined rural small 

business adoption of e-commerce practices. The rural businesses in their 

study were primarily manufacturing and retailing firms that fell into one of 

a number of e-commerce classifications: traditional local businesses that 

increased their market ranges and sales through e-commerce, virtual businesses (all marketing and sales conducted through e-commerce), businesses 
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that used e-commerce primarily to reduce marketing inputs and costs, and 

businesses that used e-commerce primarily for business-to-business (B2B) or 

business-to-consumer (B2C) transactions.

Most businesses in their study used e-commerce because it provided an 

opportunity for increased profits and enhanced sustainability. E-commerce 

may benefit a firm in product development, inventory management, manufacturing, marketing and sales, and customer service. The 28 rural businesses in 

the case study had varied experiences in the application of e-commerce. Most 

felt that e-commerce activities benefited their operations. Economic returns 

from their e-commerce activities were enhanced if the business served a 

niche market, took advantage of public and private IT service providers in 

the maintenance of their e-commerce operation, and integrated e-commerce 

into multiple aspects of the business operation.

Rural Retailers and Broadband

Retailers are a particularly important type of rural business. They are 

present in nearly every community, are often major local employers, and 

often serve as a social hub. In their workshop presentation, Stoel and Ernst 

(2008) examined the attitudes and beliefs of rural retail business owners 

(specifically apparel, hardware, and grocery) that may act as impediments to 

accepting the Internet in their businesses. Included were owners’ attitudes 

toward use of the Internet in their business, the perceived ease of use, and 

the Internet’s usefulness in operational efficiency, strategic positioning, and 

other applications.

In their survey of 181 retail business owners, Stoel and Ernst found that retail 

store owners that used the Internet were less enamored of the Internet than 

nonusers, perhaps due to a fuller realization of some of its shortcomings or to 

a begrudging compliance with suppliers’ demand that they use it. Broadband 

Internet access, however, did appear to facilitate using the Internet for operational effectiveness and business strategic positioning. Rural broadband users 

seemed to capitalize on the Internet’s capacity to increase operational effectiveness and exploit market niches. Broadband users perceive the Internet to 

be easier to use than non-broadband users (which may say something about 

slow-speed toleration in business Internet operations).

Ernst and Stoel (2008), in a more thorough survey of rural grocers, found 

that these retailers felt that they had to be more price competitive because 

consumers received more information and explored more options via 

the Internet. As a result, businesses were expanding their markets and 

commercial business was moving faster. Rural grocers did not believe that 

e-commerce reduced their profits or threatened their existence. Rather, 

customers were more familiar with their business because of the Internet.

Farm Businesses and Broadband

Agriculture is another rural business sector that benefits from the Internet. 

For farm operators with Internet access in 2000, 98 percent used it to gather 

information. Price tracking (82 percent) was the next most common application (Hopkins and Morehart, 2001).
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With growth in e-commerce, horticulture and other specialty farm products are 

increasingly sold direct to households. E-commerce has increased efficiencies 

in existing relationships along the food marketing chain, reduced the cost of 

expanding market area, and brought about new services such as supermarket 

home delivery and direct-to-consumer sales (Kinsey and Buhr, 2003).

Not all types of agricultural production lend themselves readily toward direct 

sales from producer to consumer. Still, the wholesale and retail food industry 

has enhanced its productivity with Internet adoption (Akridge, 2003; Beurskens, 

2003; Henderson et al., 2000; Stricker et al., 2003; Zilberman et al., 2002).

Respondents to the 2007 Agricultural Resources Management Survey 

(ARMS) were asked if they had Internet access and if it was “high-speed.” 

A majority of farms (63 percent) reported using the Internet in their farm 

business (fig. 12). Among those using the Internet, the predominant access 

method was broadband and this group of users accounted for over 60 percent 

of U.S. farm production. This is consistent with other estimates of farm 

broadband use. USDA’s National Agricultural Statistics Service (NASS) 

reported that, for the first time in 2007, the majority of farm Internet users 

were connecting with broadband Internet technologies (USDA/NASS, 2007). 

Prior research has identified several demographic and socioeconomic attributes that have consistently distinguished those who use the Internet from 

those who do not (Forman, 2005; Stenberg, 2006; Stenberg and Morehart, 

2007). These include income, education, age, and number of children. In our 

analysis of the determinants of broadband Internet use among farm households, we include household income, education level attained by the farm 

operator, age of the farm operator, off-farm work by spouse, presence of 

school-age children, number of hired farmworkers, rural-urban farm location, 

county net migration, and number of local broadband providers.

Figure 12

Distribution of farms and value of farm production 

by Internet use, 2007

Percent

Source: ERS analysis of 2007 ARMS (USDA, NASS and ERS).

Farms Value of farm production

0

10

20

30

40

50

60

70

No Internet access

Dialup

Broadband
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Income has consistently been cited as a primary factor determining Internet 

use (Stenberg, 2006). The greater the income level, the more likely that work 

is highly skilled. In addition, the more highly skilled the work, the more 

likely that computer technologies and the Internet are part of the work environment. As household income increases, regardless of location, the likelihood of Internet use increases (Stenberg, 2000).

Educational attainment has long been recognized as a determinant in income 

level (Becker, 1964). The prevalence of the Internet and computer technologies in educational institutions provides additional exposure and experience 

as years of formal education increase. Consequently, the greater an individual’s education, the greater the likelihood of Internet use at home or in the 

workplace (Stenberg, 2006).

Many (Oden and Strover, 2002; Grant and Meadows, 2002; Stenberg and 

Morehart, 2007) have cited age as a factor in determining the likelihood of 

Internet use. The literature suggests that older individuals are reticent about 

adopting the Internet, while the young readily adopt. The average age of farm 

operators claiming no Internet use in 2007 was 62, compared with 54 for 

those who accessed the Internet using broadband (table 14). 

Only about a third of spouses on farms with no Internet use reported working 

off-farm, compared to more than 50 percent on farms that used the Internet. 

On the one hand, off-farm employment may provide more income and exposure to Internet technologies, instigating home or farm adoption. On the other 

hand, a spouse who works off the farm may indicate financial stress and 

lesser wherewithal to invest in farm-specific Internet use. Households with 

school-age children are expected to have a higher awareness of the Internet 

and more demand for bandwidth-intensive applications (Grant and Meadows, 

2002). In keeping with this, the percentage of farms with school-age children 

was nearly two times higher in 2007 when Internet use was reported than 

when it was not (table 14).

We hypothesize that the greater the size and complexity of the farm business, 

as evidenced by the number of hired farmworkers, the more likely the farm is 

using broadband to access the Internet. Farms with broadband Internet access 

had twice the number of farmworkers, on average, as farms with no Internet 

access. Broadband use is also expected to be higher in ZIP Code areas 

with more providers, as competition for customers likely lowers the price 

differential between broadband and dial-up. The mean number of providers, 

however, showed little variation across Internet use categories (table 14) 

reflecting the predominantly rural location of farm operations. 

Maximum-likelihood methods were used to estimate a multinomial logit 

model that estimates the relationship between farm household socioeconomic 

characteristics and the type of Internet connection used. For the most part, 

coefficient signs and variable significance are consistent with expectations 

(table 15). The model fit—as indicated by the McFadden r-squared value 

of 0.089—is somewhat poor, even for a cross-sectional analysis. The coefficients represent the log-odds of a farm household using dial-up or broadband Internet access, relative to the base class (no Internet use by the farm). 

That is, what is the chance that, instead of not using the Internet at home, the 

household has an in-home dial-up or broadband Internet connection? These 
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are not the odds of using dial-up or broadband, only the odds relative to not 

being connected to the Internet at all. The sign of the coeffi cient gives the 

direction of the relationship: increase or decrease in probability due to the 

predictor. For example, as the age of the farm operator increases, the probability of having dial-up or broadband Internet access relative to no Internet 

access declines, as indicated by the negative and signifi cant coeffi cients. 

(More discussion on the underlying methodology of this analysis is presented 

in Appendix D.)

Other signifi cant model results include:

• Larger farm businesses, as indicated by more hired workers, have a 

higher probability of broadband Internet access.

• Farm households with income above $50,000 have a higher probability 

of broadband Internet access.

• The relative probability of broadband Internet use does not increase as 

the number of providers in an area increases.

Table 14

Weighted means and (standard errors) for selected variables, 2007

Internet use All family farms

Variable Name No Internet Dial-up Broadband 1997

Continuous variables:

 Operator age OP_AGE 61.90 55.15 53.85 57.20

(0.45) (0.34) (0.38) (0.20)

 No. broadband providers NOPROVIDERS06 6.80 6.71 6.83 6.79

(0.09) (0.09) (0.09) (0.05)

 Household income TOTHHI 61,614 77,831 121,141 87,523

(3,912.25) (2,396.71) (5,286.60) (2,548.60)

 No. farmworkers NOWORKERS 0.42 0.63 0.98 0.68

 (0.04) (0.03) (0.03) (0.01)

Dummy variables:

 Population change MIGCLS 0.58 0.60 0.56 0.58

(0.01) (0.01) (0.01) (0.01)

 Children CHILD 0.24 0.40 0.42 0.35

(0.01) (0.02) (0.02) (0.01)

 Spouse working off-farm SPOFF 0.34 0.52 0.51 0.45

(0.01) (0.02) (0.02) (0.01)

 College education COLLEGE 0.12 0.22 0.36 0.23

(0.01) (0.01) (0.02) (0.01)

 Urban RURAL 0.21 0.21 0.25 0.22

(0.01) (0.01) (0.02) (0.01)

 Not urban or rural 0.61 0.64 0.60 0.61

(0.01) (0.01) (0.02) (0.01)

 Rural 0.18 0.14 0.15 0.17

(0.01) (0.01) (0.01) (0.01)

 Source: ERS using FCC and 2007 ARMS (USDA, NASS and ERS).
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•	Having school-age children in the household is associated with higher

probability of broadband Internet use.

•	Operators with at least a college degree are more likely to use broadband.

•	Farms located in mixed urban/rural areas are less likely to use broadband

than those in urban areas.

The model’s results suggest that household characteristics such as age, education, 

presence of children, and household income are significant factors in adopting 

broadband Internet use. Farm business complexity, as measured by the number 

of farmworkers, was also related to the use of the Internet and broadband Internet 

access. Distance from urban centers was not a factor in Internet use. Our proxy 

for county economic well-being—population migration—was not significant 

and may be indicative of cross currents that are present; counties under economic 

distress may invest in broadband to help mitigate the distress, or may not have 

the economic wherewithal for broadband investment.

The relationship between Internet/broadband use and farm location is less 

clear. Farms in mixed urban-rural areas were less likely to use dial-up or 

broadband Internet. This may be a result of cost or availability of service. 

More isolated farms, as measured by the rurality of the county, had mixed, 

though not significant, results. These results warrant further analysis.

Farm-Rural Linkages in the Internet Economy

The Internet may change the economic relationship between farms and 

their local economies. Using data drawn from the 2004 ARMS, we investigate how Internet use affects the geography of farm input purchases. 

Table 15

Multinomial logistic regression results

Variable Dial-up Broadband Dial-up Broadband Dial-up Broadband

Estimate Estimate Std.Err Std.Err T value T value

(Intercept) -0.77 -0.57 0.07 0.09 -11.26** -6.27**

OP_AGE -50.75 -65.10 9.08 10.49 -5.59** -6.21**

(OP_AGE)2 -27.76 -32.38 6.75 6.99 -4.13** -4.64**

NOWORKERS 0.08 0.15 0.03 0.03 3.32** 5.18**

TOTHHI above 50k 0.27 0.44 0.07 0.06 4.01** 8.03**

NOPROVIDERS06 -11.45 -12.88 5.69 6.52 -2.01* -1.97*

(NOPROVIDERS06)2 -12.22 -5.32 4.98 6.69 -2.45** -0.08

MIGCLS 0.11 -0.02 0.09 0.08 1.20 -0.26

CHILD 0.17 0.29 0.09 0.12 2.10* 2.52*

SPOFF 0.29 0.12 0.10 0.12 2.93** 1.03

COLLEGE 0.70 1.34 0.11 0.11 5.89** 11.96**

Not urban or rural -0.24 -0.38 0.12 0.10 -1.96* -3.60**

Rural -0.09 0.10 0.06 0.06 -1.39 1.61

LR = 380954.54; AIC = 3905755.62; McFadden R2 = 0.089; McFadden Adj R2 = 0.089.

Note: ** - significant at 0.01, *- significant at 0.05. Equations simultaneously estimated.

Source: ERS using FCC and 2007 ARMS (USDA, NASS and ERS).
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Table 16

Logistic regression results1

Choice variable: Bypass the nearest town? Type of purchase

Farm inputs Farm equipment Farm credit

Odds ratios

Farm level variables:

 Log (gross farm sales) 1.1258*** 1.1223*** 1.1938***

 Operator’s years experience 1.0063 1.0192*** .9964

 Years of education 1.0710** 1.0675* 1.0244

 Internet farm purchase 2.0649*** 2.0148*** 1.5553*

County-level variables:

 No. of farm inputs merchants .9360***

 No. of farm equipment dealers .9303**

 Remote county .7456* .7417* 1.0081

 Log (highway miles) 1.3623*** 1.0956 1.2733**

 Log (population density) 1.1720** 1.1713* 1.0674

 Log (per capita income) 1.2686 1.0424 1.4158

Model statistics

No. of observations 2,793 2,793 2,793

Log pseudolikelihood -1,861.19 -1,620.98 -1,817.38

Wald 2 44.33 41.48 45.88 

Prob > 2 0.0000 0.0000 0.0000

Pseudo R2 .0386 .0388 .0343

1Odds ratioi

 = exp ( )

^

βi . Signifi cance level of the coeffi cient estimates ( )

^

βi :* p<.1; ** p<.05; *** p<.01.

Source: ERS analysis of 2004 ARMS data (USDA’s NASS and ERS) and other data.

Conceptually, farmers may choose to (1) purchase inputs in the nearest local 

town, (2) bypass the nearest local town but purchase inputs within the market 

reach of the nearest farm service center, or (3) bypass the farm service center 

altogether. Purchasing patterns are examined for three broad categories of 

resource inputs: farm inputs (feed, seed, and fertilizer), farm machinery and 

equipment, and farm credit. Comparing input purchases in each of these 

three mutually exclusive categories allows us to observe the changing nature 

of farm/local area interrelationships and the use of the Internet. We present 

results using logistic regression from one of these models in table 16.

Our results suggest that the market reach of the nearest town may no longer 

defi ne what the farm operator perceives as local. Making farm purchases over the 

Internet is the strongest factor increasing the likelihood of the operator bypassing 

the nearest town and even the more distant farm service center (table 16).

As farm operators increase their participation in e-commerce, their relationships with local suppliers are likely to weaken. Farm operators may increasingly opt for distant suppliers to secure lower prices or better access to niche 

inputs. Suppliers with an established Internet presence, including local ones, 

would appear better positioned to retain customers within the local economy.
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Conclusion

The Internet, and more specifically broadband Internet, has become an 

integral part of the broader economy. Since the digital or information 

economy incorporates computer processes, telephony, information storage 

and use, hardware, and software, however, it is challenging to separate out 

the Internet’s contribution to economic growth and well-being. In fact, the 

Internet’s economic contribution has more than occasionally been estimated 

using the residual in economic growth not otherwise explained.

Rural communities are invested in the digital economy, though equal access 

across the rural-urban landscape is questionable. Rural and farm households 

are almost as likely as urban households to use the Internet, but are less likely 

to use broadband. Rural businesses are less likely than urban businesses to 

use the Internet. Broadband access is less prevalent in rural areas than in 

more densely populated areas, and analysis of CPS data suggests that lower 

broadband use in rural areas may be involuntary.

Broadband provision follows a geographical pattern strongly tied to population size and the urban-rural hierarchy. Lack of broadband is most strongly 

associated with low population size in the area. Low broadband provision 

also exhibits very strong regional patterns that reflect differences in urban 

concentration and topography.

Broadband users use the Internet more intensively than dial-up users and 

now outnumber dial-up users. The high adoption rate of broadband technologies by urban Internet users indicates that people value what the Internet 

has to offer. Rural Internet users have less in-home broadband access, and 

this is likely due to its higher cost and limited availability in rural settings. 

Government policies to encourage deployment of broadband services in rural 

areas have increased availability and in some cases encouraged competitive pricing. Unfortunately, there are little national data that link Internet 

access choice with the cost of service. As a result, it is difficult to distinguish 

between financial and other motives when examining broadband adoption. 

Nonetheless, by using the Internet more intensively, on more activities, using 

newer (and presumably better) technologies, and bringing the Internet into 

their homes, schools, and workplaces, society has clearly indicated that it 

values Internet access.

More activities are shifting to the Internet. Some of these activities have 

great potential value for the rural economy. Education programs and 

offerings—primary, secondary, higher education, and continuing education—have become richer on the Internet. Telework is becoming a more 

practical option for workers and businesses. Some medical services may 

lend themselves readily to the Internet environment, with potential cost 

savings for rural residents and medical clinics that offer in-situ services not 

otherwise readily available in rural settings. Rural businesses are adopting 

more e-commerce and Internet practices, enhancing economic vitality and 

expanding market reach. Individuals are using the Internet to get involved 

with their communities.
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Analysis of farm businesses indicates that household characteristics such as 

age, education, presence of children, and household income are significant 

factors in adopting broadband Internet use. Distance from urban centers was 

not a factor in Internet access. Larger farm businesses are more apt to use 

broadband in managing their operation; the more multifaceted the farm business, the more the farm uses the Internet. 

Analysis suggests that rural economies benefit generally from broadband 

Internet availability. In comparing counties that had broadband access 

relatively early (by 2000) with similarly situated counties that had little 

or no broadband access as of 2000, employment growth was higher and 

nonfarm private earnings greater in counties with a longer history of 

broadband availability.

Government policies that encourage deployment of broadband services have 

broadened their availability in rural America. The 2008 Farm Act (Food, 

Conservation, and Energy Act of 2008) reauthorized USDA’s telemedicine, 

distance learning, and rural broadband access grant and loan programs. The 

American Recovery and Reinvestment Act of 2009 provided $2.5 billion to 

USDA for loans and grants to increase broadband provision in rural areas. As 

much as these funds address the needs of unserved and underserved communities, rural broadband availability will increase.

More research is needed in many areas to better understand broadband and 

rural economies. Better information on broadband availability, use, cost, 

and technical characteristics is needed to gain a better understanding of 

broadband Internet’s potential effect on rural economies. Broadband availability data are only now being collected below the ZIP Code area; the more 

geographically granular the data the better our understanding will become on 

unserved and underserved areas. Price data are largely unavailable, hindering 

economic analysis of supply and demand of the regional broadband market. 

Detailed broadband Internet use data also have not been collected since 

2003. Our understanding of broadband users’ online behavior is limited. 

For example, we know certain Internet-based education activities are taking 

place, but the extent to which Internet practices are taking place in rural 

education systems (in either the school or at home) is still unclear.
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References

Akridge, Jay T. (2003). “E-Business in the Agricultural Input Industries,” 

Review of Agricultural Economics, 25:1, pp. 3-13.

Becker, Gary (1964). Human Capital, New York: Columbia University 

Press.

Bender, Bruce, and Steven Shwiff (1982). “The Appropriation of Rents by 

Boomtown Governments,” Economic Inquiry, vol. 20, pp. 84-103.

Beurskens, Frank (2003). “The Economics of Dot.coms and E-commerce in 

the Agrifood Sector,” Review of Agricultural Economics, 25:1, pp. 22-28.

Blum, U. (1982). “Effects of Transportation Investments on Regional 

Growth: A Theoretical and Empirical Investigation,” Papers of the 

Regional Science Association, vol. 49, pp. 169-84.

Borenstein, Severin, and Garth Saloner (2001). “Economics and Electronic 

Commerce,” Journal of Economic Perspectives, 15:1, pp. 3-12.

Bresnahan, Timothy F., Erik Brynjolfsson, and Lorin M. Hitt (1999). 

Information Technology, Workplace Organization, and the Demand 

for Skilled Labor: Firm-Level Evidence, National Bureau of Economic 

Research, NBER Working Paper Series, Working Paper 7136.

Brynjolfsson, Erik, and Michael D. Smith (2000). “Frictionless Commerce? 

A Comparison of Internet and Conventional Retailers,” Management 

Science, 46:4(April), pp. 563-85.

Capalbo, Susan M., and Christine N. Heggem (1999). “Valuing Rural Health 

Care: Issues of Access and Quality,” American Journal of Agricultural 

Economics, 81: 3, pp. 674-679.

Choudrie, Jyoti, and Yogesh K. Dwivedi (2006). “Investigating Factors 

Infl uencing Adoption of Broadband in the Household,” The Journal of 

Computer Information Systems, 46(4), pp. 25-34.

Cook, Thomas D., and Donald T. Campbell (1979). Quasi-Experimentation: 

Design and Analysis Issues for Field Settings, Chicago: Rand McNally 

College Publications.

Crandall, Robert W. (2008). “Broadband, Jobs, and Regional Growth: The 

Limited Evidence.” Paper presented at the Economic Research Service’s 

Broadband in the Rural Economy workshop, Washington, DC, Sept.

Crandall, Robert, William Lehr, and Robert Litan (2007). “The Effects of 

Broadband Deployment on Output and Employment: A Cross-sectional 

Analysis of U.S. Data,” Issues in Economic Policy, The Brookings 

Institution, No. 6, July.

Crescia, Elena (2006). “Measuring e-gov Impact: The Experience of São 

Paulo, Brazil,” e-stratégia pública, Feb. 9.
41

Broadband Internet’s Value for Rural America / ERR-78

Economic Research Service/USDA

Davies, Stephen (1979). The Diffusion of Process Innovations, Cambridge 

University Press.

DeYoung, Robert, and Denise Duffy (2002). “The Challenges Facing 

Community Banks: In Their Own Words,” Economic Perspectives, 

Chicago Federal Reserve Bank.

Egan, Bruce L. (1996). Information Superhighways Revisited: The 

Economics of Multimedia, Boston: Artech House.

Eisenberg, Jon (2002). “Broadband: Bringing Home the Bits.” Paper 

presented at the 2002 TPRC meetings, Arlington, VA, Sept.

Ernst, Stan, and Leslie Stoel (2008). “Rural Grocers and Technology 

Adoption: Attitude Matters, Size Matters More.” Paper presented at the 

Economic Research Service’s Broadband in the Rural Economy workshop, Washington, DC, Sept.

Farnsworth, Don (1972). The Ohio County Airport Study 1964-1972, Ohio 

Department of Commerce, Division of Aviation, Columbus, Ohio.

Federal Communications Commission (2008). Trends in Telephone Service, 

http://hraunfoss.fcc.gov/edocs_public/attachmatch/DOC-284932A1.pdf .

Flamm, K., and A. Chaudhuri (2007). “An Analysis of the Determinants of 

Broadband Access,” Telecommunications Policy, 31: 312-326.

Forman, Chris (2005). “The Corporate Digital Divide: Determinants of 

Internet Adoption,” Management Science, 51:4, pp. 641-654.

Fuss, Melvyn, and Leonard Waverman (2005). “Canada’s Productivity 

Dilemma: The Role of Computers and Telecom,” Bell Canada’s 

Submission to the Telecommunications Review Panel, Appendix E-1.

Gallegos, Hugo C. (2002). “E Government: Defi nitions, Benefi ts, 

Development, Examples,” La Sociedad Digital. 

Gillett, Sharon E., William H. Lehr, Carlos A. Osorio, and Marvin A. Sirbu 

(2006). Measuring the Economic Impact of Broadband Deployment, Final 

Report, National Technical Assistance, Training, Research, and Evaluaton 

Project, U.S. Department of Commerce, Economic Development 

Administration.

Gloy, B.A., and J. T. Akridge (2000). “Computer and Internet adoption on 

large U.S. farms,” International Food and Agribusiness Management 

Review, 3: 323-338.

Goetz, Stephan, and David Debertin (1996). “Rural-urban Locational 

Choices of Medical Doctors: A County-Level Analysis,” Review of 

Agricultural Economics, vol.18, pp. 547-63.

Grant, August E., and Jennifer H. Meadows, editors (2002). Communication 

Technology Update, eighth edition, Woburn, MA: Elsevier Science.
42

Broadband Internet’s Value for Rural America / ERR-78

Economic Research Service/USDA

Greene, W.H. (1993). Econometric Analysis, third ed. Prentice-Hall, Upper 

Saddle River, NJ.

Greenstein, Shane, and Jeff Prince (2006). The Diffusion of the Internet and 

the Geography of the Digital Divide in the United States, National Bureau 

of Economic Research, NBER Working Paper Series, Working Paper 

123182.

Greenstein, Shane (2000). Building and Delivering the Virtual World: 

Commercializing Services for Internet Access, National Bureau of 

Economic Research, Working Paper 7690, May.

Henderson, J., F. Dooley, and J. Akridge (2000). “Adoption of E-Commerce 

strategies for agribusiness fi rms,” http://www.ebscohost.com.

Hooker, N.H., J. Helig, and S. Ernst (2001). “What is unique about 

EAgribusiness?” http://agecon.lib.umn.edu/.

Hopkins, Jeff, and Mitch Morehart (2001). “Farms, the Internet, & 

E-Commerce: Adoption and Implications,” Agriculture Outlook, Nov., 

pp. 17-20.

Horrigan, John B. (2008). “Broadband Adoption, Rural America, and 

Economic Decisions.” Paper presented at the Economic Research 

Service’s Broadband in the Rural Economy workshop, Washington, DC, 

Sept.

Internet Systems Consortium, https://www.isc.org/.

Isserman, Andrew, and Terance Rephan (1995). “The Economic Effects of 

the Appalachian Regional Commission: An Empirical Assessment of 

26 Years of Regional Development Planning,” Journal of the American 

Planning Association, 61:3(Summer), pp. 345-64.

Isserman, Andrew M., and Peter L. Stenberg (1994). The Recovery of Rural 

Economies from Military Base Closures: Control Group Analysis of 

Two Decades of Experience, Research Paper 9408, Regional Research 

Institute, West Virginia University.

Isserman, Andrew M. (1987). Highways and Rural Economic Development: 

Results from Quasi-Experimental Approaches, Research Paper 8907, 

Regional Research Institute, West Virginia University.

Just, D.R. and Just, R.E. (2001). “Harnessing the Internet for farmers,” 

Choices: The Magazine of Food & Resource Issues, 16(2): http://www.

ebscohost.com.

Keeton, William R. (2001). “The Transformation of Banking and Its Impact 

on Consumers and Small Businesses,” Economic Review, Kansas City 

Federal Reserve Bank.
43

Broadband Internet’s Value for Rural America / ERR-78

Economic Research Service/USDA

Kinsey, Jean and Brian Buhr (2003). “E-Commerce: A New Business Model 

for the Food Supply/Demand Chain,” Working Paper 03-01, The Food 

Industry Center, University of Minnesota, February.

Lamie, R. David, David L. Barkley, and Deborah M. Markley (2008). 

“Positive Examples and Lessons Learned from Rural Small Business 

Adoption of E-Commerce Strategies.” Paper presented at the Economic 

Research Service’s Broadband in the Rural Economy workshop, 

Washington, DC, Sept.

Lanvin, Bruno (2008). “Where is e-government going in 2020?” Paper 

presented at the e-leaders conference, The Hague, March 6-7.

Leamer, Edward E., and Michael Storper (2001). The Economic Geography 

of the Internet Age, National Bureau of Economic Research, Working 

Paper 8450, Aug.

Maddala, G.S. (1983). Limited-Dependent and Qualitative Variables in 

Econometrics, Cambridge University Press, New York.

Malecki, Edward J. (2008). “The Rural Digital Economy: Competition and 

the Geography of Telecommunications.” Paper presented at the Economic 

Research Service’s Broadband in the Rural Economy workshop, 

Washington, DC, Sept.

Malecki, Edward J., and Bruno Moriset (2007). The Digital Economy: 

Business Organization, Production Processes and Regional 

Developments, London: Routledge.

Mann, Catherine L. (2008) “Information Technology, Services, and the 

Global Economy,” Paper presented at the Economic Research Service’s 

Broadband in the Rural Economy workshop, Washington, DC, Sept.

Mann, Catherine L. (2006). Accelerating the Globalization of America: The 

Role for Information Technology, Institute for International Economics: 

Washington DC.

Massachusetts Broadband Institute, http://www.masstech.org/broadband/

resources.html.

McFadden, Daniel (1974). “Conditional Logit Analysis of Qualitative Choice 

Behavior,” in Zarembka, P. ed., Frontiers in Econometrics, New York: 

Academic Press.

Moore, Michael Grahame, editor (2007). Handbook of Distance Education, 

NY: Routledge.

Morris, Douglas E., and Lyndon E. Goodridge (2008). “What skills are at 

the end of broadband cables in rural America? Do they match up with 

fi rms wishing to engage rural sourcing?” Paper presented at the Economic 

Research Service’s Broadband in the Rural Economy workshop, 

Washington, DC, Sept.
44

Broadband Internet’s Value for Rural America / ERR-78

Economic Research Service/USDA

National Telephone Cooperative Association, “NTCA Members Internet/

Broadband Survey Report,” Nov. 2000.

Oden, Michael, and Sharon Strover (2002). Links to the Future: The Role 

of Information and Telecommunications Technology in Appalachian 

Economic Development, Appalachian Regional Commission, Washington, 

DC.

Odlyzko, Andrew (2008). “The Internet’s role in aggravating and alleviating 

the energy crises,” Internet Evolution, April 8.

Parker, Edwin B. (2000). “Closing the Digital Divide in Rural America,” 

Telecommunications Policy, 24(4), pp. 281-90.

Parker, Edwin B., and Heather E. Hudson (1992). Electronic Byways: State 

Policies for Rural Development Through Telecommunications, Boulder: 

West View Press.

PEW Internet & American Life Project, http://www.pewinternet.org/index.

asp.

Pociask, Stephen B. (2005). “Broadband Use by Rural Small Businesses,” 

Washington, DC: Small Business Administration, Offi ce of Advocacy.

Poley, Janet (2008). “Rural Distance Education.” Paper presented at the 

Economic Research Service’s Broadband in the Rural Economy workshop, Washington, DC, Sept.

Renkow, Mitchell (2008). “Residential Broadband Availability and 

Adoption: Recent Evidence from Kentucky and North Carolina.” Paper 

presented at the Economic Research Service’s Broadband in the Rural 

Economy workshop, Washington, DC, Sept.

Rogers, Everett M. (1995). Diffusion of Innovations, New York: The Free 

Press.

Stenberg, Peter L., and Mitchell Morehart (2008). “Characteristics of Farm 

and Rural Internet Use in the United States,” Handbook of Research on 

Global Diffusion, Yogesh Dwivedi, et al. (eds.), Idea Group, Inc..

Stenberg, Peter L., and Mitchell Morehart (2007). “The Internet in U.S. Farm 

and Rural Businesses,” in Irene Johansson (eds.), Entrepreneurship and 

Development-Local Processes and Global Patterns, University West, 

Sweden.

Stenberg, Peter L., and Mitchell Morehart (2006). “Determinants of Internet 

Use for Rural and Farm Economic Sectors”, Telecommunication Policy 

Research Conference, Arlington, VA, Sept. 29.

Stenberg, Peter L. (2006). “Investment and Household Adoption of 

Communication and Information Services Across the United States” in 

The Emerging Digital Economy: Entrepreneurship, Clusters and Policy, 
45

Broadband Internet’s Value for Rural America / ERR-78

Economic Research Service/USDA

Borge Johansson, Charlie Karlsson, and Roger Stough (eds.), Springer: 

Berlin, Heidelberg, New York, pp. 263-76.

Stenberg, Peter L. (2004). “United States Policy for Spatial Investment in 

CIT”, Regulation and Capital Market Evaluation in Telecommunications, 

H.J. Piepenbrock,F. Schuster, and E.O. Ruhle (eds.), Springer-Verlag 

Publishing, New York.

Stenberg, Peter L. (2000) “Rural Telecommunication Policy in the U.S.: 

Issues and Economic Consequences.” Electronic proceedings for the 

conference, European Rural Policy at the Crossroads, The Arkleton 

Centre for Rural Development Research, University of Aberdeen, 

Scotland, UK, 29 June-1 July, http:\\www.abdn.ac.uk/arkleton/conf2000/

papers/stenberg.doc, Sept.

Stenberg, Peter L. (editor) (1999). Telecommunications in Rural Economic 

Development. Proceedings from a workshop, Western Rural Development 

Center, Oregon State University, Corvallis, OR, Dec.

Stern, Michael J., Alison E. Adams, and Jeffery Boase (2008). “The Role of 

the Internet in Rural Community Participation: Examples from Survey 

Data.” Paper presented at the Economic Research Service’s Broadband in 

the Rural Economy workshop, Washington, DC, Sept.

Stern, Michael, and Don A. Dillman (2006). “Community Participation, 

Social Ties, and Use of the Internet,” City & Community, vol. 5, 

pp.409-24.

Stoel, Leslie, and Stan Ernst (2008). “Comparing Rural Retailer Internet 

Users and Non-users: Access Speed, Demographics, Attitudes, and 

Beliefs.” Paper presented at the Economic Research Service’s Broadband 

in the Rural Economy workshop, Washington, DC, Sept.

Stricker, S., D.A. Sumner, and R.A.E. Mueller (2003). “Wine on the Web in 

a Global Market: A Comparison of E-Commerce Readiness and Use in 

Australia, California, and Germany.” Paper presented at the EFITA 2003 

Conference, July 5-9.

U.S. Department of Agriculture, National Agricultural Statistics Service 

(2007). Farm Computer Usage and Ownership.

Varian, Hal R. (2003) “Economics of Information Technology.” Raffaele 

Mattioli Lecture, Bocconi University, Milano, Italy, revised March 23.

Verisign, http://www.verisign.com/.

Wellman, Barry, Janet Salaff, Dimitrina Dimitrova, Laura Garton, Milena 

Gulia, and Caroline Haythornthwaite (1996). “Computer Networks 

as Social Networks: Collaborative Work, Telework, and Virtual 

Community,” Annual Review of Sociology, vol. 22, pp. 213- 238.
46

Broadband Internet’s Value for Rural America / ERR-78

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Wheat, Leonard (1970). The Effect of Airline Service on Manufacturing 

Growth in Cities Below 40,000 Population, U.S. Department of 

Commerce, Economic Development Administration, Washington, DC.

Whitacre, Brian E. (2008). “Estimating the Economic Impact of 

Telemedicine in a Rural Community.” Paper presented at the Economic 

Research Service’s Broadband in the Rural Economy workshop, 

Washington, DC, Sept.

Zilberman, David, Mark Metcalfe, and Amir Heiman (2002). “Economics 

and Adoption of Information Technology with Evidence from California.” 

Paper for the Card E-Commerce research mini-conference, Feb. 9.
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Figure A-1

Bureau of the Census Regions

NORTHEAST

CA

MT

AZ

ID

NV

NM

CO

OR

UT IL

WY

KS

IA

NE

SD

MN

ND

WI

MO

WA

MI

IN

PA

NY

OH

ME

MI VTNH

NJ

MA

CT RI

TX

OK

FL

AL GA

AR

LA

NC

MS

TN

VA

KY

SC

WV

MDDE

AK

HI

WEST

SOUTH

MIDWEST

Appendix A: Bureau of the Census Regions
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Appendix B: Data Used in the Study

Agricultural Resources Management Survey

Most of the farm-level data used in the analysis are from the 2007 

Agricultural Resources Management Survey (ARMS), conducted annually 

by USDA’s Economic Research Service and National Agricultural Statistics 

Service. The survey collects information needed to measure the financial 

condition (farm income, expenses, assets, and debts) and operating characteristics of farm businesses, the cost of producing agricultural commodities, 

and the well-being of farm operator households. The target population of the 

survey is operators of farm businesses representing agricultural production in 

the 48 contiguous States. A farm is defined as an establishment that sold or 

normally would have sold at least $1,000 of agricultural products during the 

year. Farms can be organized as proprietorships, partnerships, family corporations, nonfamily corporations, or cooperatives. Data are collected from one 

operator per farm, the senior farm operator. A senior farm operator is the 

operator who makes most of the day-to-day management decisions. For this 

study, operator households organized as nonfamily corporations or cooperatives and farms run by hired managers are excluded.

June Agricultural Survey Data

The June Agricultural Survey is conducted by USDA’s National Agricultural 

Statistics Service every year to provide estimates of farm numbers and land 

in farms, crop acres planted, grains and oilseeds in storage, livestock inventories, and land values. In 1997, 1999, 2001, 2003, 2005, and 2007, the surveys 

included questions about Internet access. In 2005 and 2007, the questions 

addressed broadband Internet access. The 2007 computer usage estimates are 

based on responses from over 31,400 agricultural operations and represent all 

sizes and types of farms.

Federal Communications Commission Form-477 Data

The Federal Communications Commission collects data from Internet 

service providers twice annually: in June and December. The data have been 

collected since December 1999 through what is called the FCC Form-477. 

The data collected include number of lines, various company characteristics, and most importantly where broadband is currently provided. Initially, 

very small providers were not required to file the form, but eventually all 

providers were required to return the form to the FCC every 6 months. On 

the form, a company specifies each ZIP Code in which it has customers. 

Recently, the FCC has started to collect more detailed information on type of 

broadband service and location of broadband service provision.
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PEW Surveys

PEW data are collected by Princeton Survey Research Associates. Sample 

sizes for each survey are around 2,500, with total sampling error of +/-2 

percent and sampling error of +/-3 percent for Internet users. Data were 

collected from various surveys and reports available from PEW Internet & 

American Life Project’s website (http://www.pewinternet.org/index.asp). 

Urban, as defined by the U.S. Census Bureau, includes any population concentration of 2,500 or more people.

Current Population Survey

The U.S. Census Bureau conducts monthly Current Population Surveys. 

The surveys constitute 57,000 households containing 134,000 persons. 

On an irregular basis, the Bureau’s monthly survey includes questions on 

Internet and related technologies. These special surveys provide broadbased and statistically reliable information on the ways that information 

technologies, in general, and broadband more specifically are transforming 

the way we live, work, and learn. As of this writing, the last survey on 

information technology took place in October 2007, but only asked four 

Internet-related questions, whereas an October 2003 survey asked detailed 

questions on what, where, and how the Internet was used. Estimation 

conducted in this report had a sampling error no greater than +/-2 percent. 

Urban, as defined by the U.S. Census Bureau, includes any population 

concentration of 2,500 or more people.
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Appendix C: Using the FCC Data

Broadband Availability Over Time

The growth in broadband availability has been rapid. This can be seen in 

the following maps (fig. C-1 - C-4) developed from the FCC data that show 

broadband availability from December 2000 through December 2006. Each 

dot in the maps represents a ZIP Code area that has at least one provider. The 

dots are located at the population center for their corresponding ZIP Codes. 

Dots are used to represent broadband availability as rural broadband service 

most commonly radiates out from towns into the surrounding countryside. 

These maps give a contrasting view of broadband availability from the isopleth map (fig. 6, p. 16) shown in the main body of this report. Some persistent 

wilderness areas and the development of broadband service along arterial 

roadways become apparent in the dot maps over time (from 2000 to 2006).
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Broadband deployment has generally followed population density. This can 

be seen from the population density map (fig. C-5).

Enhancing the FCC Data

Population and adjoining area affect broadband availability. These facts 

underlie our enhancement of the FCC broadband availability data. From the 

FCC data we developed broadband availability density maps that constitute 

our most basic measure for a number of our research applications. This basic 

broadband database is composed of equally sized 2-km sub-ZIP Code zonal 

building blocks. The databases are further refined and adapted to each line of 

research in our broader rural broadband Internet study.

Essentially, these 2-km grid cells show the likelihood of having broadband 

available at any location within the lower 48 States at different points of 

time. To generate these broadband probability surfaces, we first locate the 

number of providers at the population centroid of the ZIP Code, where 

providers are most likely to maximize potential customers. Next, we pass 

a kernel density function over the provider locations using an 8-km search 

radius. 
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The resulting surface provides estimates of provider access with the highest 

likelihood at the population centroid of ZIP Codes and decreasing probability toward the edge of the search radius. This search radius is larger 

than the typical limitation of DSL Internet service of 15,000 feet (4.5 km); 

due to technical reasons, DSL service cannot go beyond a certain distance 

from its signal’s point of origin without additional equipment along the telephone line. The 8-km search radius helps to balance our assumption that all 

providers within a ZIP Code are centrally within the ZIP Code. Likelihood 

of service increases with more providers within a ZIP Code. Overlapping 

provision areas increase the likelihood of service to any location within the 

overlap, so high provision in adjoining zonal areas further increases the likelihood of broadband availability.

Our density map was tested against June Agricultural Survey data of farm 

broadband use. The June Agricultural Survey (JAS) data are a geographicbased survey of farms in the lower 48 States. Internet use data have been 

collected since 1997. The JAS Internet data give geographic- and timespecific use and non-use of broadband Internet. (See Appendix B for further 

discussion of the JAS data.)

The density map matched very well with the JAS data in all areas except 

what is essentially the Great Plains region. The challenge here is the large 

geographic size of some ZIP Code areas, suggesting that the population 

centroid indicates less well the broadband Internet service area. The location of schools is used to further define the likelihood of broadband Internet 

service in an area; schools are useful because of their widespread use of 

broadband Internet. With the additional data, the surface map was adjusted to 

include additional provision areas. The resulting broadband density is essentially a likelihood measure—the probability of broadband Internet access for 

any given point in geographic space. Likelihood of broadband Internet access 

is centered in urban areas and radiates out from these urban centers (fig. C-6). 

The FCC data and the various selected indices that we developed here, one of 

which is shown in figure C-7, form the basis for much of the analysis in this 

report.

Our data were left as geo-specific or reconstituted into either county or ZIP 

Code areas for our analysis. Reconstitution into ZIP Code or county-level 

estimates required using population weighting of the provider likelihood estimate. A county aggregation of the data can be seen in figure C-7.

Estimation of Expected Number of Broadband Providers Using 

Population Measurements

To estimate the expected number of broadband providers, we began with the 

FCC’s measure of the number of providers in a ZIP Code area in an unmodified form. To avoid disclosure of information on individual companies, areas 

that recorded 1-3 providers were combined into one category and assigned 

a value of 2. We used a population-based regression analysis to measure the 

relationship between the number of broadband providers and three components of U.S. population distribution: the overall population in the ZIP Code 

area in 2005, the percent of the ZIP Code’s population living in urban areas 

as defined by the U.S. Census Bureau in 2000 (the most recent data on urban-
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rural population), and a measure of the ZIP Code’s accessibility to nearby 

populations. 

ZIP Code area accessibility is used to distinguish areas that might be similarly sized but are differently positioned relative to large population centers. 

All things being equal, a nonmetro ZIP Code area adjacent to a metro area 

will likely have more providers than a more isolated area. To calculate 

accessibility for each ZIP Code area a, we identified all other ZIP Code 

areas within 200 miles, divided the population of each of these areas by the 

distance (squared) to area a, and summed the results. Values range from 

0.0002 in Prudhoe Bay, Alaska to 150 million in Los Angeles (table C-1).

The independent variables were logged for the regression analysis to meet 

the assumption of linearity with the dependent variable. Parameter estimates 

represent the change in the number of broadband providers that occurs with 

a 1-percent increase in the independent variable. For example, a 1-percent 

increase in population size will increase the number of providers by 1.07. 

The standardized parameter estimates indicate the relative strength of the 

influence of each independent variable. Population size has twice the effect 
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Table C1

Descriptive statistics and linear regression results measuring the effect of population size, percent urban, 

and population accessibility on number of broadband providers, 2006

Mean Standard 

deviation Minimum Maximum Parameter estimate

Standardized

estimate

Dependent variable:

Number of broadband providers, 2006 6.59 3.58 0 21 n/a n/a

Independent variables:

Population size, 2005 9,922 13,878 0 114,726 1.08 0.55

Percent urban, 2000 39.93 43.90 0 100 2.54 0.22

Population accessibility, 2005 20,944.09 1,045,331.36 0 150,709,763 0.21 0.13

Note: Descriptive statistics for the independent variables are shown for unlogged values; logged values were used in the regression analysis. 

All parameter estimates are significant at the .01 level. The proportion of variation in broadband provision explained by the regression (adjusted 

R-square) equals .63.

Source: USDA, Economic Research Service, using data from the FCC and U.S. Census Bureau.
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on number of broadband providers compared with percent urban, which in 

turn has a stronger effect than accessibility.

Parameter estimates may be used to calculate the expected number of broadband providers in a ZIP Code area. Residuals from the regression show the 

difference between the actual and expected number of providers (fig. 9, p. 

18). For example, Grafton, West Virginia’s ZIP Code area had 10,316 people, 

was 59 percent urban, and had an accessibility measure of 385. Taking the 

natural logs of these values (4, 0.2, and 2.6, respectively), multiplying them 

by their parameter estimates, and summing the results show a predicted value 

for Grafton of 5.4 providers. The number of broadband providers in this ZIP 

Code area, as reported by the FCC in 2006, was 2, so the model indicates that 

Grafton has roughly 3 fewer providers than predicted. 
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Appendix D—Modeling Broadband Use on 

the Farm

Discrete choice models are interpreted in terms of an underlying behavioral 

model, the so-called random utility maximization (RUM) model. The decisionmaker chooses the alternative with the highest utility. Let xij be an attribute vector of alternatives j that individual i faces; let b be the impacts of the 

changes of the attributes; let eij be a random component. The random utility 

function of alternative j for individual i can then be written as 

Uij = b'xij + eij. Suppose that alternative j is chosen and that alternative k is 

not chosen. Individual i will choose j to maximize the random utility function, if and only if Uij > Uik for any k ≠ i. Since eij is a random component 

of the individual utility function, the probability that individual i actually 

chooses alternative j is written as P (Uij>Uik) for any k ≠ i. The true utilities 

of the alternatives are considered random variables, so the probability that the 

alternative is chosen is defi ned as the probability that it has the greatest utility 

among the available alternatives. 

Using the conceptual framework put forth by Flamm and Chaudhuri (2007), 

we assume that the underlying utility of Internet use is related to economic 

and demographic attributes (Flamm and Chaudhuri, 2007). The purchasedecision outcome (j) consists of one of three choices: no purchase, dial-up, or 

broadband. The xij are represented by the explanatory variables described in 

the farm businesses and broadband section. Under certain restrictive assumptions, the probability that individual i chooses alternative j can be expressed 

as Pij = P(Uij>Uik) = exp(b'xij)/ k

K ∑ =1 exp(b'xik). 

The model that results under certain distribution assumptions about e is 

usually called the conditional logit model. Apart from the assumptions underlying the RUM model, the conditional logit model implies that “the choice 

probabilities have the property which is called independence of irrelevant 

alternatives” (McFadden, 1974). This means that the ratio of the probabilities 

of choosing two alternatives is independent of the characteristics of all other 

choice possibilities. The conditional logit model is sometimes called the 

multinomial logit model. Following Greene (1993) and Maddala (1983), this 

latter term is reserved for models where the probabilities of the individual 

making a certain choice are functions of the characteristics of the individual, 

while the term conditional logit model is used when the choice probabilities 

are functions of characteristics of the choice alternatives. The way the problems are set up is different in these two models. The likelihood functions, 

however, will be the same.
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Appendix E—Quasi-Experimental Design

Quasi-experimental design (QED) is a statistical approach that simulates an 

ex-post laboratory experiment featuring both a treatment and control group. 

Selection of control and treatment in QED, unlike a true laboratory experiment, is not perfectly random, hence the term “quasi.” Treatment groups 

are self-selected. Control groups are selected based on their characteristic 

similarity with the initial, or pre-treatment, characteristics of the treatment 

groups. The QED approach taken here follows those of Isserman and Rephan 

(1995). SAS and other software were used in the analysis. A couple of the 

SAS routines used here were initially developed by Isserman.

The closeness between counties that is used to select the control counties is 

derived using a discrete measure called Mahalanobis distance. Mahalanobis 

distance measures the similarity between the treatment county and each 

county that could potentially be part of a control group. The measure is 

derived from the differences between the treatment county’s and another 

county’s characteristics’ measures. The Mahalanobis distance is 

MAHALbj=(Xb-Xj

)

T Σ-1(Xb-Xj

),

where b is the treatment county, j is the potential control group county, X 

is the vector of variables that measure a county’s characteristics, and Σ is 

the variance-covariance matrix of the variables calculated over all possible 

control counties. There are a number of ways to compare treatment versus 

control groups in QED. In the application here, there is one control county 

for each treatment county. No control county is allowed to appear more than 

once in the control group. The pairwise counties are the basic unit of analysis. The difference in growth is computed for each pair. The mean and standard deviations of these differences are computed, as are t-statistics between 

the treatment and control groups.

Robustness checks were made by analyzing prior-period growth rates. A 

tautology did not exist between the selection of control counties and their 

post-economic growth measures as the selection of control counties employs 

a large array of spatial and socioeconomic factors. Control and treatment 

county growth rates were more similar in the prior period, 1997-2000, than in 

the treatment period, 2002-2006. Selection criteria for treatment groups were 

relaxed and strengthened (i.e., cutoff points in broadband likelihood were 

increased and decreased). No appreciable change in outcomes was found as 

a result of these changes; the model was not sensitive to minor changes in 

treatment group inclusiveness.

More analysis on the robustness, however, needs to be completed to further 

substantiate the results and address more completely the issue of causality. 

Treatment group selection and control group characteristic variables will be 

further varied to test sensitivity in selection process.
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Appendix F: Economic Research Service 

Broadband Workshop, September 29-30, 2008

Broadband in the Rural Economy

Keynote: Rural Digital Economy 

Edward Malecki, The Ohio State University

Internet and Rural Business Activity

Broadband Deployment and Economic Development in Kentucky 

and North Carolina

Mitch Renkow, North Carolina State University

Rural Broadband Internet Use and Rural Economy

Peter Stenberg, Economic Research Service, RRED

Comparing Rural Retailer Internet Users and Non-Users: Access Speed, 

Demographics, Attitudes and Beliefs. 

Leslie Stoel and Stan Ernst, Ohio State University

Rural Grocers and Technology Adoption: Attitude Matters. 

Size Matters More.

Stan Ernst and Leslie Stoel, The Ohio State University

Food and Nonfarm Rural Business

Internet Marketing of Nursery and Greenhouse Products

Enefiok Ekanem and Fisseha Tegegne, Tennessee State University

Positive Examples and Lessons Learned from Rural Small Business 

Adoption of E Commerce Strategies

David Lamie, David Barkley, Clemson University, and Deborah Markley, 

University of Missouri

IT and E-Commerce Companies

John Leatherman, Kansas State University, and Hanas Cader, South 

Carolina State University

Farm and Rural Households 

Farm Businesses and Broadband Internet Use

Mitchell Morehart and Peter Stenberg, Economic Research Service

Farming and the Internet: Reasons for Nonuse

Brian Briggeman and Brian Whitacre, Oklahoma State University

What Skills Are at the End of Broadband Cables in Rural America? Do They 

Match Up with Firms Wishing to Engage Rural Sourcing?

Doug Morris and Lyndon Goodridge, University of New Hampshire
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Digital Economy 

IT in the Global Economy

Catherine Mann, Peterson Institute for International Economics 

and Brandeis University 

Effects of Broadband Deployment on Output and Employment 

Robert Crandall, Brookings Institution

Home Broadband Adoption in the United States: Patterns, Barriers, and 

Consequences

John Horrigan, Pew Internet & American Life Project

Community Internet Use

The Role of the Internet in Rural Community Participation—Examples from 

Recent Survey Data

Michael Stern and Alison E. Adams, Oklahoma State University

Rural Distance Education 

Janet Poley, University of Nebraska-Lincoln and President of the American 

Distance Education Consortium

Economic Impact of Rural Telemedicine

Brian Whitacre, Oklahoma State University