Predicting Broadband Expansion: An Analysis of Geographic and Demographic Influences

16 Pages Posted: 23 Aug 2019

See all articles by E. K. Itoku

E. K. Itoku

Columbia University

Aman Varma Mantena

Columbia University

Aaron Sadholz

Columbia University

Anna Zhou

Columbia University

Henning Schulzrinne

Columbia University - Department of Computer Science

Date Written: August 21, 2019

Abstract

High-speed Internet access (’broadband’) is available nearly everywhere in urban and suburban parts of the contiguous U.S. However, there are many rural areas which do not have broadband access yet. We implemented a machine learning framework consisting of multiple supervised models for accurately predicting broadband expansion using geographic and demographic data on a census block group level. We then utilized these models to gain an understanding of how these features relate to broadband expansion. Also, we discussed how this data must be considered differently when investigating unsubsidized broadband expansion rather than government subsidized expansion.

Understanding relationships between geographic and demographic features with respect to broadband speed and accessibility is reliant upon publicly available data provided by the Federal Communications Commission (FCC), United States Census Bureau, and the Universal Service Administrative Company. The project included identifying, cleaning, and aggregating the data as well as creating a cloud-based-storage infrastructure with Google BigQuery.

We found that by considering geographic and demographic data, effective models can be constructed to both understand previous broadband expansion and predict future expansion. Notably, we found that road, housing and population density, winter temperature, and elevation are of significant importance in determining whether an area receives broadband.

Keywords: Broadband, Internet, FCC, Form 477, Census Data

JEL Classification: Z18

Suggested Citation

Itoku, E. K. and Mantena, Aman Varma and Sadholz, Aaron and Zhou, Anna and Schulzrinne, Henning, Predicting Broadband Expansion: An Analysis of Geographic and Demographic Influences (August 21, 2019). Available at SSRN: https://ssrn.com/abstract=3440399 or http://dx.doi.org/10.2139/ssrn.3440399

E. K. Itoku

Columbia University ( email )

3022 Broadway
New York, NY 10027
United States

Aman Varma Mantena

Columbia University ( email )

3022 Broadway
New York, NY 10027
United States

Aaron Sadholz

Columbia University ( email )

3022 Broadway
New York, NY 10027
United States

Anna Zhou

Columbia University ( email )

3022 Broadway
New York, NY 10027
United States

Henning Schulzrinne (Contact Author)

Columbia University - Department of Computer Science ( email )

New York, NY 10027
United States
2129397042 (Phone)

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