Does Place Really Matter?Broadband Availability, Race and            Income                                    Presentatio...
Research Questions• Explore the relationships between broadband  availability and race & ethnicity, income, and  place  – ...
Three Case Studies• Los Angeles  – majority-minority city with large Asian and    Hispanic populations• Chicago  – almost ...
General Findings• “Race” was not a significant determinant of broadband deployment  in low-income, high minority communiti...
Wireline vs. Wireless
Los Angeles: Broadband Providers and Population Density
Los Angeles: Broadband Providers and Household Income
Los Angeles: Broadband Providers and Minorities
Los Angeles: Broadband Providers and Blacks
Los Angeles: Broadband Providers and Hispanics
Los Angeles: Broadband Providers and Asians
Chicago: Broadband Providers and Blacks
Chicago: Broadband Providers and Blacks
South Carolina: Broadband Providers and Population Density
South Carolina: Broadband Providers and Household Income
South Carolina: Broadband Providers and Blacks
Regression Analysis• Dependent Variable: broadband providers in  South Carolina• Explaining Variables  – Model 1: Race and...
Data and Technical Issues• Dataset size – time/resource intensive• Availability of datasets by each geographical  unit• Av...
Going Forward• Availability <> Adoption, Why?• Cost• Type of service: wireline/wireless in relation to  demographics• Speed
Inglewood, CA: Broadband Speed and Blacks
Research Team• Ying Li  yli@jointcenter.org• Nicol Turner-Lee  nturner-lee@jointcenter.org• Samir Gambhir  Gambhir.2@osu.e...
Thank You!
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Does Place Really Matter? Broadband Availability, Race and Income

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Does Place Really Matter? Broadband Availability, Race and Income

  1. 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. 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. 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. 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. 5. Wireline vs. Wireless
  6. 6. Los Angeles: Broadband Providers and Population Density
  7. 7. Los Angeles: Broadband Providers and Household Income
  8. 8. Los Angeles: Broadband Providers and Minorities
  9. 9. Los Angeles: Broadband Providers and Blacks
  10. 10. Los Angeles: Broadband Providers and Hispanics
  11. 11. Los Angeles: Broadband Providers and Asians
  12. 12. Chicago: Broadband Providers and Blacks
  13. 13. Chicago: Broadband Providers and Blacks
  14. 14. South Carolina: Broadband Providers and Population Density
  15. 15. South Carolina: Broadband Providers and Household Income
  16. 16. South Carolina: Broadband Providers and Blacks
  17. 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. 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. 19. Going Forward• Availability <> Adoption, Why?• Cost• Type of service: wireline/wireless in relation to demographics• Speed
  20. 20. Inglewood, CA: Broadband Speed and Blacks
  21. 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. 22. Thank You!

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