1. Does Place Really Matter?
Broadband Availability, Race and
Income
Presentation by
Ying Li, Ph.D.
Research Analyst
Joint Center for Political and Economic Studies
And
Mikyung Baek, Ph. D.
Research and Technical Associate
Kirwan Institute for the Study of Race and Ethnicity
The Ohio State University
At
The National Broadband Map: Early Results from Social Science Research
Washington, DC
Tuesday, March 22, 2011

2. Research Questions
• Explore the relationships between broadband
availability and race & ethnicity, income, and
place
– To what extent is broadband readily available in
low-income communities, especially those where
minorities are more concentrated?
– To what extent do urban and rural penetration
rates show dramatic difference in broadband
service deployment?

3. Three Case Studies
• Los Angeles
– majority-minority city with large Asian and
Hispanic populations
• Chicago
– almost equal numbers of whites, African
Americans and Hispanics
• South Carolina
– large low-income, rural and black populations

4. General Findings
• “Race” was not a significant determinant of broadband deployment
in low-income, high minority communities in all three regions.
• “Income” was more significant in South Carolina and in select areas
where residents were low-income, high minority like Inglewood,
CA
• Wireline and wireless coverage was uneven by income
• Broadband speed might be an additional barrier in deployment in
low-income, minority communities (finding in Inglewood needs
exploration)
• Adoption is still a prime issue because even with some level of
competition, penetration rates are still low.

5. Wireline vs. Wireless

6. Los Angeles: Broadband Providers and Population Density

7. Los Angeles: Broadband Providers and Household Income

8. Los Angeles: Broadband Providers and Minorities

9. Los Angeles: Broadband Providers and Blacks

10. Los Angeles: Broadband Providers and Hispanics

11. Los Angeles: Broadband Providers and Asians

12. Chicago: Broadband Providers and Blacks

13. Chicago: Broadband Providers and Blacks

14. South Carolina: Broadband Providers and Population Density

15. South Carolina: Broadband Providers and Household Income

16. South Carolina: Broadband Providers and Blacks

17. Regression Analysis
• Dependent Variable: broadband providers in
South Carolina
• Explaining Variables
– Model 1: Race and Income, Adjusted R2 = 0.0388
– Subsequent models with more variables,
urban/rural, pop. density, even lower Adj. R2
• Need for more in-depth analysis, possibly
using GWR, Geographic Weighted Regression

18. Data and Technical Issues
• Dataset size – time/resource intensive
• Availability of datasets by each geographical
unit
• Availability of residential subscription data
• Wireless coverage data in GIS format
• Problem with census block ID, inconsistent
with concatenation of ST, CTY, Tract, BG, and
Block IDs (e.g., New York data)

19. Going Forward
• Availability <> Adoption, Why?
• Cost
• Type of service: wireline/wireless in relation to
demographics
• Speed

20. Inglewood, CA: Broadband Speed and Blacks

21. Research Team
• Ying Li
yli@jointcenter.org
• Nicol Turner-Lee
nturner-lee@jointcenter.org
• Samir Gambhir
Gambhir.2@osu.edu
• Mikyung Baek
baek.7@osu.edu

22. Thank You!