high-speed broadband internet in north carolinacompared to member nations of the organisation for...

High-Speed Broadband Internet in North Carolina:

It’s fast, but is it effective?

By

Eleanor Blake

March 14, 2011

A paper submitted to the faculty of

The University of North Carolina at Chapel Hill

in partial fulfillment of the requirements for the degree

Master of Public Administration

This paper represents work done by a UNC MPA student. It is not a formal report of the School of

Government, nor is it the work of School of Government faculty.

Executive Summary

Improved access and faster speeds of broadband Internet are predicted to transform life for

Americans. As access to and adoption of high-speed broadband Internet has increased in the past

decade, how has it impacted the economy, education and quality of life for North Carolinians? This

research looks at the effect of broadband adoption in North Carolina and finds that the current

adoption rate of broadband Internet has significant influence on select economic factors, but no

measurable influence on a select set of social or educational indicators.

2 | H i g h - S p e e d B r o a d b a n d I n t e r n e t i n N C

Background

High-speed broadbandi Internet is no longer a convenience or just for entertainment. It is now a national goal

that is predicted to improve education, quality of life and economic performance. The extensive National

Broadband Plan refers to it as essential 21st century infrastructure that is “transforming the landscape of

America more rapidly and more pervasively than earlier infrastructure networks” (Federal Communications

Commission, 2010, p. 3). The Pew Internet and American Life Project’s Home Broadband Adoption 2009

(Horrigan, 2009) report found that 43% of Americans believe lack of Internet to be a disadvantage for

conducting particular activities, primarily job seeking and building career skills.

North Carolina, like many other states, and the federal government are working to improve the speed and

availability of broadband in hopes of achieving an array of positive outcomes. On a global scale, the United

States has room to improve. While in the year 2000 the U.S. had the highest percentage of population

connected to the Internet, it is now ranked 18th for both adoption and access

ii and 24

th for advertised speed

compared to member nations of the Organisation for Economic Co-operation and Development.iii North

Carolina ranked 14th among U.S. states for broadband adoption rates in 2009.

iv The Federal Communications

Commission (FCC) adoption data show the average broadband subscription in North Carolina as just below

400 homes per 1,000 (at a speed of 768 kbps). See Appendix 2: Broadband Adoption Map.

North Carolina is active in expanding broadband infrastructure and improving broadband speeds, primarily

to underserved areas and key institutions.v In 2010, North Carolina received over $275 million in federal

grants for broadband expansion, and initiatives such as the e-NC Authority,vi MCNC

vii and other businesses

are rolling out fiber to connect North Carolina homes and institutions. As the state moves forward with

broadband initiatives, an understanding of the effects of broadband is needed. This research explores whether

broadband has had a measurable impact on 2009 economic, social and educational outcomes. Empirical

investigation into the impact of broadband efforts can inform North Carolina practitioners and policy makers

working to build and implement the state’s Internet strategy.

Previous Research

Research on broadband began in earnest in the early 2000s after the technology-influenced economic boom

of the late 1990s. During this time Internet deployment was in its early stages and much of the research was

hypothetical and forward-looking, predicting billions of dollars in GDP growth and over a million jobs

created (Gillett, Lehr, & Osorio, 2006, p.6). More recent reports have analyzed the impact of broadband in

municipalities, states, regions and the nation and have primarily utilized longitudinal methods, analysis of

growth and change rates, and examination of comparable communities.

A number of studies have reported economic growth related to broadband. Measuring Broadband’s

Economic Impact (Gillett, Lehr, & Osorio, 2006) found that, nationwide, broadband contributed to job

creation, the number of businesses (with greater growth in the IT-intensive sector), and property values, but

no statistical impact was found for wages. A study by Jed Kolko (2010) also found mixed results nationwide,

reporting broadband was not associated with employment rate or wages, but did impact business activity. An

increase in gross sales in a community in Florida was attributed to its municipally-owned broadband network

(Ford & Koutsky, 2005). And a study of the commercial benefits of broadband in the rural Appalachia region

found modest impact on firm productivity and wages in particular regions and scenarios (Burton & Hicks,

2005).


Research on the social benefits of broadband is more prognostic, predicting improved access to health care,viii

ix reduced energy consumption,

x and improvement of public safety.

xi A survey of the residents of New

Brunswick rural areas of Canada found that broadband improved quality of life through streamlined daily

operations and enhanced access to information, without negatively impacting longstanding social

relationships (Selouani & Hamam, 2007).

Educational research has focused primarily on Internet access within schools and its effect on educational

performance, highlighting the opportunities and challenges of technology in primary and secondary schools.

Effects on test scores have been mixed (Underwood, et al., 2005); a study by Goolsbee and Guryan (2005) on

the impact of E-rate government Internet subsidies in schools found no significant effect on performance

scores.

Beyond survey-based studies and data collected by the e-NC Authority, the impact of broadband has not

been empirically evaluated for North Carolina. This research seeks to provide greater understanding of the

influence broadband Internet has had on North Carolina economic, social and educational attainment.

Methodology

Data Analysis Methods

This study uses correlations and regression analyses to examine the relationship between broadband Internet

adoption in North Carolina and a set of economic, social and educational indicators. Correlations were

examined between broadband and indicators proven or hypothesized to be affected by broadband in prior

research. xii

xiii

In order to test for spurious relationships in the correlations, multiple regression analyses were

used to determine if broadband is a significant influencing factor on the dependent variables when

controlling for other significant independent variables and controls, such as population density, educational

attainment and income per capita. Broadband adoption data, along with other influencing factors and

controls, were tested in multiple models to measure the influence and power with which broadband affects a

range of economic, social and educational indicators.

Eight regression models were run to test for broadband’s impact. The dependent variables selected for the

models are those that have shown to be influenced by broadband in previous research or are key indicators of

economic, educational and social wellbeing. For economic influence, three dependent variables were

selected. Income per capita and median home value were used as measures of current personal wealth,xiv

while retail sales was used as a measure of current economic productivity.xv

Educational impact is gauged

using End-of-Grade (EOG) school test scores and End-of-Course (EOC) school test scores.xvi

The social

dependent variables used for this research were crime index, teen pregnancy and poverty.xvii

Previous

research was used to inform model construction and the inclusion of control variables with careful attention

to avoiding multicollinearity. See Appendix 3: Variable Definitions.

Data Collection Methods

Broadband adoption data were collected at the county level from the FCC’s form 477 reports, the standard

for broadband subscribership data.xviii

This data represent fixed lines of broadband Internet in homes and

does not include access to the Internet via wireless or mobile connections. Adoption rates are reported in

ranges, 0 to 5,xix

and indicate households per 1,000 with broadband connections. Rates are connections at the

768 kbps speed, the FCC’s high-speed definition in 2009 when the data were collected. North Carolina


adoption rates range from 2 to 5 with an average of 2.83, indicating adoption at the higher end of the 200 to

400 connections per 1,000 households range.

The three economic dependent variables, income per capita, median home value and retail sales, were

collected from the NC Department of Commerce and are calculated based on U.S. Census data and statistical

projections conducted by the geographic information systems company ESRI. School test scores and all other

educational data are from the NC Department of Public Instruction and were aggregated to the county level

based on reporting by school districts in the NC School Report Cards. For the social dependent variables,

teen pregnancy rate is collected by the NC Department of Health and Human Services and is measured as the

number of babies born to teenagers age 15 to 19 per 1,000 births. Crime index, a combination of eight FBI-

defined crimes, comes from the NC Department of Commerce and data calculated by the company Applied

Geographic Solutions. Poverty rate, the percent of people earning less than an income threshold set by the

federal government, also comes from the Department of Commerce and statistical calculations by ESRI.

Other demographic data were included in the research as independent variables and controls and were

collected from a variety of sources, including the U.S. Census, NC Department of Commerce and the NC

Department of Public Instruction. See Appendix 3: Variable Definitions and Appendix4: Data Descriptive

Statistics.

Findings

Results of the correlation analysis indicate significant relationships with seven of the eight outcome

variables. Broadband adoption has a strong positive correlation with the economic indicators income per

capita and median home value, and a weaker, but significant and positive correlation with retail sales. The

educational indicators, EOG and EOC school test scores, both have a relatively weak, positive relationship

with broadband adoption. There is a significant negative relationship between broadband adoption and

poverty rate and between broadband and teen pregnancy, while the correlation with crime index is not at a

statistically significant level (Table 1). With the exception of crime index, relationships were confirmed in

the expected direction for economic, educational and social indicators. These initial results provide evidence

of a potential influence of broadband adoption on key economic, social, and educational outcomes.

Table 1: Correlations Results

Outcome Correlations with Broadband Adoption

Outcome Variable Correlation with Broadband, R

Income per Capita -0.591**

Median Home Value -0.644**

Retail Sales -0.306**

EOG Test Scores -0.347**

EOC Test Scores -0.288**

Crime Index -0.172**

Teen Pregnancy -0.455**

Percent Poverty -0.475**

**significant at the 0.01 level


While initial correlations indicated statistically significant relationships between broadband economic, social

and educational measures, regression analysis allowed for more sophisticated investigation of these

relationships. Regression results for the eight models found that the adoption of broadband was significant in

only two, those measuring economic attainment: income per capita and median home values. The model

examining income per capita explained 80.6% of the variance, and broadband as an independent variable was

significant at the <0.01 level, influencing income along with (but with less power than) educational

attainment and population density. The median home value model accounted for 65.4% of the variance in

home values, and broadband was a significant predictor along with income and urban-rural designation.

Contrary to findings in other regions of the U.S.,xx

broadband was not a significant influencing factor on

retail sales when combined with the major factors of income, urban-rural designation and poverty. These

findings show that broadband does, to some degree, positively influence personal economy, but the lack of a

statistically significant relationship with retail sales does not indicate impact on current business activity. The

presence and adoption of broadband in North Carolina counties, therefore, is shown to be important for the

particular economic outcomes of income and home values.

Broadband was not found to be a statistically significant predictor in the models testing selected educational

and social outcomes, despite the significant correlations. The major drivers of EOG and EOC test scores

were poverty, population density and teachers with advanced degrees. Crime index, teen pregnancy and

poverty rate were largely influenced by income (Table 2). See Appendix 6 for detailed results.

Broadband adoption, as it currently exists, is not shown by this research to be an important factor for

improvement and advancement of education and social wellbeing or for all economic outcomes at this time.

There is a possibility that certain economic measures respond more quickly to high-speed broadband

infrastructure and that the positive influence on educational attainment and social wellbeing may yet to be

fully realized. Future studies are key, but this research does not support North Carolina’s recent and past

investment in broadband availability in terms of generating all the expected positive results.

Table 2: Multiple Regression Results

Multiple Regression Results: Broadband’s Influence on Dependent Variables

Dependent Variable Broadband Beta Coefficient Broadband Significance

Income per Capita -0.198 <0.0100

Median Home Value -0.283 <0.0100

Retail Sales -0.117 0.158

EOG Test Scores -0.027 0.761

EOC Test Scores -0.000 0.999

Crime Index -0.193 0.061

Teen Pregnancy -0.069 0.497

Poverty -0.043 0.664


Limitations

Because income and home values are themselves important determinants of wellbeing, reverse causality is a

potential limitation. This research does show broadband adoption to be a significant influencing factor on

income and home values. However, greater wealth allows an ability to purchase broadband and related

technologies, and there is a possibility that income as an independent factor determines broadband adoption.

Limitations also exist with the current broadband data. The changing speed and technology of high-speed

Internet means that the definition and measurement of broadband are also frequently changing. The FCC’s

1999 minimum broadband speed was 200 kbps downstream, a speed incapable of managing the degree of

high-quality video, voice, graphics and data sent and received on the Internet today. The 2010 Broadband

Plan increased the speed minimum from 768 kbps to 4 Mbps, a new definition that discounts 66% of U.S.

Internet connections.xxi

These inconsistent definitions, as well as the difficulty in gathering complete access

and adoption data from private providers, limit broadband impact studies.

Additionally, the particular data set and methods used in this research do not explore broadband’s influence

on economic productivity factors such as employment, indicators with varying relationships to broadband

according to other studies.xxii

Conclusion & Recommendations

This study finds that broadband adoption is important for North Carolina economy, influencing residents’

personal economics through increased income and home values. With no evidence of broadband’s influence

on the selected educational and social indicators, the findings are not completely consistent with the

predictions and stories of the full economic, social and educational benefits of broadband.

Further research is needed to substantiate North Carolina’s current investment and pursuits, and definitive

results will depend on the accumulated results of continued studies utilizing a variety of approaches and

improved data. Time-series analyses in prior research did find measurable broadband impact; a longitudinal

study is required to test for a potential lag in the fuller impact of broadband in North Carolina. Additionally,

comprehensive studies must include Internet connections to businesses and institutions, as well as

households, to fully capture impact. Wireless connections and mobile 3G and 4G networks also contribute to

connectedness and may prove to be more popular Internet services in the future.

With millions of dollars and other resources dedicated to broadband, North Carolina policy makers and

practitioners can evaluate this study not as validation or invalidation, but as benchmark data for current and

past broadband initiatives, as well as evidence of greater need for improved data measurement and tracking,

continued research, and strategic broadband initiatives based on measurable results.

i The FCC defines broadband, or high speed Internet, as “advanced communications systems capable of providing high-speed transmission of services such as data, voice, and video over the Internet and other networks.” Technologies include digital subscriber line (DSL), fiber optic cable, coaxial cable, wireless technology and satellite. The 2010 National Broadband Plan sets the speed standard of these technologies at 4 Mbps actual download and 1 Mbps actual upload. http://www.fcc.gov/broadband/ ii Adoption, a.k.a. subscribership or penetration, is the number or percentage of households with purchased

broadband lines. Access refers to the number or percentage of households able to access broadband, regardless of subscription.


iii 2009 data. Data collection and interpretation, as well as rankings, are controversial.

http://www.oecd.org/sti/ict/broadband iv http://www.ntia.doc.gov/reports/2010/ESA_NTIA_US_Broadband_Adoption_Report_11082010.pdf

v Gaps in availability in North Carolina occur according to rural-urban areas and by tiers. Nationwide, disparity is also

attributed to differences in racial and ethnic backgrounds. http://www.pewcenteronthestates.org/ report_detail.aspx?id=59149 vi The e-NC Authority’s mission is to ensure that residents and businesses in North Carolina, particularly in rural and

distressed urban areas, are aware of high-speed Internet services and capabilities, have affordable access to them, and know how to use them. e-NC.org vii

MCNC received two federal grants for expansion of the NC Research and Education Network. https://www.mcnc.org/btop viii

Pew Internet and the American Life Project’s Internet “health seekers” survey. http://www.pewInternet.org/ Reports/2000/The-Online-Health-Care-Revolution/Summary.aspx ix Report on the impacts of telemedicine. http://www.broadband.gov/docs/ws_adoption_unserved/

ACLP_Broadband_Telemedicine_Overview.pdf x Smart grid technology can save energy. http://www.e-renewables.com/documents/Smart%20Grid/

Smart%20Grid%20Enabling%20the%2021st%20Century%20Economy.pdf xi The 2010 National Broadband Plan (The Federal Communications Commission, 2010, Chapter 16).

http://www.broadband.gov/plan/ xii

“Like electricity a century ago, broadband is a foundation for economic growth, job creation, global competitiveness and a better way of life.” The National Broadband Plan (The Federal Communications Commission, 2010, p. xi). http://www.broadband.gov/plan/ xiii

The e-NC broadband report (Baller & Lide, 2008, p. 2). xiv

Gillett, et al. (2006) found no impact on wages (a proxy for income), but it is used in this paper’s research as a strong indicator of long-term economic performance. Kelly (2003) showed home values are higher in communities with greater broadband infrastructure. xv

Ford & Koutsy (2005) found greater growth in gross sales in a Florida county that provides broadband utility than in comparable counties. xvi

Goolsbee & Guryan (2005) used standardized end-of-year test scores as a measure of educational attainment. xvii

The NC Rural Center Data Dictionary (2009) collects data on poverty rate, teen pregnancy rate and crime as measures of wellbeing. xviii

Purchased broadband home connections of at least 768 kbps downstream advertised speed reported by telephone companies, cable system operators, terrestrial wireless service providers, satellite service providers and other facilities-based providers of advanced telecommunications capability. xix

0 = zero, 1 = zero < x <= 200, 2 = 200 < x <= 400, 3 = 400 < x <= 600, 4 = 600 < x <= 800, 5 = 800 < x xx

Ford & Koutsy (2005) found greater growth in gross sales in a Florida county that provides broadband utility than in comparable counties. xxi

FCC 9/10 news release. http://www.fcc.gov/wcb/iatd/comp.html xxii

Kolko (2010) found no impact of broadband on the unemployment rate. Gillett et al. (2006) found increased employment due to broadband.


APPENDIX 1: Bibliography

Balanskat, A., Blamire, R., & Kefala, S. (2006). The ICT Impact Report: A review of studies of ICT

impact on schools in Europe. European Schoolnet.

Baller, J., & Lide, C. (2008). Bigger Vision, Bolder Action, Brighter Future: Capturing the Promise of

Broadband for North Carolina and America. The Baller Herbst Law Group for e-NC.

Bifulco, R., & Ladd, H. F. (2006). The Impacts of Charter Schools on Student Achievement: Evidence

from North Carolina. American Education Finance Association.

Boyd, D., Lankford, H., Loeb, S., Rockoff, J., & Wyckoff, J. (2008). The Narrowing Gap in New York

City Teacher Qualifications and Its Implications for Student Achievement in High-Poverty

Schools. Journal of Policy Analysis and Management, 27(4), 793-818.

Burton, M. L., & Hicks, M. J. (2005). The Residential and Commercial Benefits of Rural Broadband:

Evidence from Central Appalachia. West Virginia Development Office, A Vision Shared.

Crandall, R. W., & Jackson, C. L. (2001). The $500 Billion Opportunity: The Potential Economic Benefit

of Widespread Diffusion of Broadband Internet Access. Criterion Economics, L.L.C.

Federal Communications Commission (2010). Connecting America: The National Broadband Plan.

Feser, E. (2005). North Carolinians Online: Trends from the Citizen Surveys 1999-2004. The e-NC

Authority.

Ford, G. S., & Koutsky, T. M. (2005, April). Broadband and Economic Development: A Municipal Case

Study from Florida. Applied Economic Studies.

Futernic, K. (2010). Incompetent Teachers or Dysfunctional Systems? Re-framing the Debate on Teacher

Quality and Accountability. WestEd.

Gillett, S. E., Lehr, W. H., & Osorio, C. A. (2006). Measuring Broadband's Economic Impact. U.S.

Department of Commerce, Economic Development Administration.

Goolsbee, A., & Guryan, J. (2006). The Impact of Internet Subsidies in Public Schools. Review of

Economics and Statistics, 88(2), 226-347.

Horrigan, J. (2009). Home Broadband Adoption 2009. Pew Internet & American Life Project,

Washington, D.C.

Kelly, D. J. (2003). A Study of the Economic and Communitiy Benefits of Cedar Falls, Iowa's Municipal

Telecommunications Network. Iowa Association of Municipal Utilities, Telecommunications

Division.

Kolko, J. (2010). Does Broadband Boost Local Economic Development? Public Policy Institute of

California.


Machin, S., McNally, S., & Silva, O. (2006). New Technology in Schools: Is There a Payoff? The

Institute for the Study of Labor.

National Telecommunications and Information Administration (2010). Exploring the Digital Nation:

Home Broadband Internet Adoption in the United States. U.S. Department of Commerce.

Pew Center on the States (2010). Bringing America Up to Speed: States' Role in Expanding Broadband.

Pew Charitable Trusts.

Selouani, S.-A., & Hamam, H. (2007). Social Impact of Broadband Internet: A Case Study in the

Shippagan Area, a Rural Zone in Atlantic Canada. Journal of Information, Information

Technology, and Organizations, 2, 79-94.

Underwood, J., Ault, A., Banyard, P., Bird, K., Dillon, G., Hayes, M., et al. (2005). The Impact of

Broadband in Schools. Nottingham Trent University. Becta ICT Research.


APPENDIX 2: Broadband Adoption Map


APPENDIX 3: Variable Definitions

Variable Definition Source Prior Studies Study Findings Used in research?

Broadband

Adoption

Lines in service, or purchased household Internet connections, of at least 768 kbps downstream

FCC Form 477

Used as the measure of broadband for all studies consulted

All reviewed studies found that broad-band improved select indicators

Yes

Access

Percent of households with access to at least 4 Mbps downstream

National Broadband Plan Maps

N/A None No. Not recommended for analysis due to statistical pre-diction methods

Economic

Retail Sales

Derived from receipts (net of sales taxes, refunds, and returns) of businesses primar-ily engaged in the re-tailing of merchandise

NC Depart-ment of Commerce EDIS database

Ford & Koutsky, Broadband and Economic Development: A Municipal Case Study from Florida (2005)

Greater growth of gross sales was shown in a Florida county with broadband utility than in comparable counties

Yes

Job creation The number of new jobs (based on a survey of NC indust-rial and commercial companies)


Gillett et al., Measuring the Economic Impact of Broadband Deployment (2006)

Greater growth in employment ob-served in commun-ities with greater broadband

No. Complete data for all industries not available

Kolko, Broadband and Local Growth (2010)

Found a positive relationship between broadband and employment growth, especially in IT-intensive businesses and in areas with lower population density

Wages Average gross annual wages across all industries. (Includes salaries, bonuses, stock options, tips and other gratuities, and the value of meals and lodging, where supplied)

US Bureau of Labor Statistics


Broadband does not improve wages

Yes, income used


Unaffected by broadband


Burton & Hicks, The Residential and Commercial benefits of rural broadband: Evi-dence from Central Appalachia (2005)

Hypothesizes that broadband will increase wages due to observed improve-ment in firm product-ivity

Number of Establish-

ments

An economic unit that produces goods or services

US Bureau of Labor Statistics


Growth in estab-lishments, especially IT-related, due to broadband from 1998-2002

No. Little correlation

Small Employers

Businesses with few or no employees (and not represented in Census establish-ment data)

N/A Gillett et al., Measuring the Economic Impact of Broadband Deployment (2006)

Used as a control for the effect of broad-band on other econ-omic indicators

No. Unable to obtain data

Median Home Value

Median value of owner-occupied housing


Kelly, A Study of the Economic and Community Benefits of Cedar Falls, Iowa’s Muni-cipal Telecommun-ications Network (2003)

Higher in a com-munity with municipal broadband infrastruc-ture compared to similar communities

Yes


Hypothesized that broadband would increase home values and tax base, but not increase employment rate or wages

Unemploy-ment Rate

The number of unemployed divided by the labor force



Unaffected by broadband

Yes

Income per Capita

Average income per individual



Broadband does not significantly impact wages

Yes. Is a strong measure of long-term economic performance

Labor Force The total number of people employed and seeking employment




No. Unable to obtain partici-pation rate data

IT-Intensive Firms

The share of establishments in the IT-intensive sector

N/A Gillett et al. Measuring the Economic Impact of Broadband Deployment (2006)


No. No standard definition


Social

Voter Turnout

The number who voted as a percentage of registered voters for the November 2008 election

Democracy North Carolina

O’Brian, Measuring Citizen Engagement: The North Carolina Civic Index (2003)

Voter turnout and the improvement in citizen engagement build and improve communities

No. Not correlated and entire civic index not available at county level

Jacksonville Com-munity Council, Inc., Quality of Life Progress Report for Jacksonville and Northern Florida (2010)

Use voter turnout rate as a measure of quality of life

NC Rural Center Data Dictionary (2009)

Used as a measure of community health

Teen Pregnancy

The number of babies born to teenagers (females age 15-19) per 1,000 births

NC DHHS, State Center for Health Statistics

Adam Mellows-Facer, Social Indicators (2004)

Use teen pregnancy statistics as a snap-shot of social health, among many indi-cators

Yes

Jacksonville Com-munity Council, Inc., Quality of Life Progress Report for Jacksonville and Northern Florida (2010)

Use teen pregnancy rate as a measure of quality of life

Crime Index

An index of the eight crimes the FBI combines to produce its annual crime index


Adam Mellows-Facer, Social Indicators (2004)

Use number of crimes as a snapshot of social health, among many indicators

Yes



Infant Mortality

Infant deaths per 1,000 live births

State Center for Health Statistics, NC DHHS



No

US Dept. of Health and Human Services

Considers infant mortality to be one of the most important indicators of health

Jacksonville Community Council, Inc., Quality of Life Progress Report for Jacksonville and Northern Florida (2010)



Percent Uninsured

Percentage of population under age 65 without health insurance

UNC Sheps Center for Health Services Research

Jacksonville Community Council, Inc., Quality of Life Progress Report for Jacksonville and Northern Florida (2010)


No

Percent in Poverty

The percent of people earning less than the income threshold set by the federal government




Yes

Education

End of Grade & End of

Course scores

The percentage of students that score at or above grade level on end-of-grade and end-of-course tests

NC DPI School Report Cards

Bifulco & Ladd, The Impact of Charter Schools on Student Achievement: Evidence from North Carolina (2006)

Used as a measure of student performance for comparing different schools

Yes

Machin et al., New Technology in Schools: Is there a payoff? (2006)

An indicator of school performance used to measure the effects of technology funding

Goolsbee & Guryan, The Impact of Internet Subsidies in Public Schools (2005)

Use the California standardized end-of-year tests for math, reading and science for students in primary and secondary schools. Find no relation to Internet in the school and test scores

School funding

The total amount of funding from local, state and federal levels to each county, per student, in dollars


Machin et al., New Technology in Schools: Is there a payoff? (2006)

Technology funding found to positively impact test scores for certain grades and subjects, but other support and training needed for full impact

Yes

Students per Internet-

Connected Computer

Number of students per Internet-connected computer in each county


Balanskat et al., The ICT Impact Report: A review of studies of ICT impact on schools in Europe (2006)

Technology and connectivity in schools has positive impact on some grades and subjects

Yes


Goolsbee & Guryan, The Impact of Internet Subsidies in Public Schools (2005)

Use “previous techno-logy histories” to control for historical, longitudinal, differen-ces that may affect improvement in stu-dent achievement

Teachers with

Advanced Degrees

The percentage of teachers who have completed an advanced college degree, including a master's or doctoral degree in elementary, middle and high schools


Futernick, Incom-petent Teachers or Dysfunctional Sys-tems? Reframing the debate on teacher quality and accountability (2010)

Advocates that a quality and supportive teaching environment is more necessary than individual teacher attributes

Yes

Boyd et al., The Narrowing Gap In New York City Teacher Qualifica-tions and Its Impli-cations for Student Achievement in High-Poverty Schools (2008)

Advanced degrees tend to be found in more economically prosperous areas and therefore may be highly correlated with economic status

Dropout Rate

Number of students grades 7-13 dropping out in one year, divided by total students grades 7-13

NC DPI Goolsbee & Guryan, The Impact of Internet Subsidies in Public Schools (2005)

Found no significant impact on dropout rate

Yes

Educational Attainment

The percentage of the population to attain at least a bachelor’s degree


Bifulco & Ladd, The Impact of Charter Schools on Student Achievement: Evi-dence from North Carolina (2006)

Used as a control for student scores

Yes

Controls

Population density

Average number of people per square mile



Found that broad-band, not population growth was the cause of economic growth

Yes

Tier Designation

Classification by the NC Department of Commerce indicating economic disadvan-tage (1) and economic prosperity (3)

NC Rural Center



Yes

Urban-Rural Designation

Designation as urban or rural as defined by the NC General Assembly

NC Rural Center

Yes


APPENDIX 4: Variable Descriptive Statistics

N Minimum Maximum Mean Std. Deviation

Broadband

Adoption (lines in service) 100 2 5 2.83 .711

Access (percent served) 100 .22 1.00 .7879 .17464

Economic

Retail Sales 100 9605091 12112045802 9.25E8 1.873E9

Wages 100 24660 61104 31692.07 5330.944

Number of Establishments 100 97 32369 2420.91 4573.950

Median Home Value 100 78284 214644 122434.62 30516.357

Unemployment Rate 100 .066 .161 .11063 .021836

Income per Capita 100 1.600400E4 3.633900E4 2.19294900E4 3.926953096E3

Educational

EOG Index 100 .5475 .9125 .750426 .0805034

EOC Index 100 .5210 .9270 .799070 .0742824

Dropout Rate 100 .67 5.02 2.9174 .85555

Funds per Student 100 6980 18468 9223.26 1565.747

Teacher Degree Index 96 .11 .43 .2543 .05924

Educational Attainment 100 .0858 .5430 .176116 .0838571

Social

Voter Turnout 100 .5783 .7773 .692916 .0398298

Turnout Gain 100 -.0461 .2795 .059601 .0439009

Teen Pregnancy 100 18.5 55.3 33.566 6.8529

Number of Physicians 100 .0 93.3 14.174 12.9401

Crime Index 100 6 239 88.74 41.562

Infant Mortality Rate 100 .0 20.8 7.605 4.5396

Percent Uninsured 100 .166 .288 .20239 .020691

Percent in Poverty 100 8.9 32.3 18.323 4.8959

Controls

Tier Designation 100 1 3 1.79 .743

Urban-Rural Designation 100 0 1 .15 .359

Population Density 100 9.0 1734.0 191.421 254.6498

Valid N (listwise) 96


APPENDIX 5: Correlations of All Collected Variables with Broadband Adoption

Variable Correlation with Broadband, R

Retail Sales -0.306**

Annual Wages -0.365**

Number of Establishments -0.310**

Median Home Value -0.644**

Unemployment Rate -0.407**

Income Per Capita -0.591**

Population Density -0.336**

EOG 3rd

Grade Reading -0.411**

EOG 3rd

Grade Math -0.300**

EOG 8th

Grade Reading -0.370**

EOG 8th

Grade Math -0.201**

EOG Overall Reading -0.389**

EOG Overall Math -0.281**

EOG Subjects Index -0.347**

EOC English 1 -0.252**

EOC Algebra -0.228**

EOC Biology -0.323**

EOC Subjects Index -0.288**

Percent Students Taking SAT -0.412**

Average SAT Score -0.535**

Dropout Rate -0.101**

School Funds – Local -0.594**

School Funds – State -0.410**

School Funds – Federal -0.496**

Total Funds per Student -0.221**

Students per Internet Computer -0.165**

Teachers with Degrees – Elementary Schools -0.150**

Teachers with Degrees – Middle Schools -0.153**


Teachers with Degrees – High Schools -0.158**

Teaching Degree Index -0.178**

Educational Attainment – High School Degree -0.684**

Educational Attainment – Bachelor’s Degree -0.544**

Voter Turnout 2008 -0.052**

Percent Improved Turnout 2008 -0.137**

Teen Pregnancy Rate -0.455**

Number of Physicians -0.330**

Crime Index -0.172**

Infant Mortality Rate -0.207**

Percent Uninsured -0.109**

Percent Poverty -0.475**


*significant at the 0.05 level


APPENDIX 6: Regression Results

Variables Results

Economic Model 1: Income per Capita Beta (Sig.)

- Broadband adoption

- Educational attainment (Bachelors)

- Unemployment rate

- Urban-rural designation

- Population density

-0.198 (<0.01)**

-0.591 (<0.01)**

-0.054 (0.322)

-0.042 (0.551)

-0.320 (<0.01)**

R2

-0.816

R2

Adj. -0.806

Economic Model 2: Median Home Value Beta (Sig.)




- Income per capita

- Poverty rate

-0.283 (<0.01)**

-0.055 (0.630)

-0.214 (0.023)*

-0.581 (<0.01)**

-0.149 (0.068)

R2

-0.672

R2

Adj. -0.654

Economic Model 3: Retail Sales Beta (Sig.)



- Income per capita

- Poverty rate

- Unemployment rate

-0.117 (0.158)

-0.320 (<0.01)**

-0.730 (<0.01)**

-0.212 (0.013)*

-0.038 (0.585)

R2

-0.627

R2

Adj. -0.608




Variables Results

Education Model 1: End-of-Grade Test Scores

Beta (Sig.)


- Poverty rate

- Students per Internet computer

- Teachers with degrees

- Funds per student


-0.027 (0.761)

-0.556 (<0.01)**

-0.067 (0.473)

-0.328 (<0.01)**

-0.002 (0.985)

-0.202 (0.017)*

R2

-0.522

R2

Adj. -0.490

Education Model 2: End-of-Course Test Scores

Beta (Sig.)


- Poverty rate

- Students per Internet computer

- Teachers with degrees

- Funds per student

- Population Density

-0.000 (0.999)

-0.549 (<0.01)**

-0.000 (0.997)

-0.179 (0.065)

-0.066 (0.572)

-0.141 (0.152)*

R2 -0.345

R2

Adj. -0.301




Variables Results

Social Model 1: Crime Index Beta (Sig.)


- Income per capita


- Dropout rate

-0.193 (0.061)

-0.454 (0.002)**

-0.784 (<0.01)**

-0.160 (0.056)

R2 -0.380

R2

Adj. -0.354

Social Model 2: Teen Pregnancy Rate


- Income per capita

- Population Density

- Unemployment rate


-0.069 (0.497)

-0.678 (<0.01)**

-0.140 (0.341)

-0.129 (0.141)

-0.059 (0.626)

R2 -0.436

R2

Adj. -0.406

Social Model 3: Poverty Rate


- Income per capita


- Median home value

-0.043 (0.664)

-0.654 (<0.01)**

-0.295 (0.01)**

-0.224 (0.072)

R2 -0.483

R2

Adj. -0.461



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