Abstract

Access to broadband has changed how people live and do business. The COVID-19 pandemic has only exposed the existing health, economic, and social challenges within the county, and have highlighted the need to be prepared for such events in the future. Governments of all levels are tasked with easing the burden that citizens and local businesses face. Access to “good” broadband has never been more important than that in the last 2 years. NTIA and FCC’s broadband deployment programs have had socio-economic impacts on the cities in many ways. With the infrastructure bill passed, focus on getting broadband to every corner of the country is necessary and needed.

Project Description & Overview

The scope of the project is to understand and cluster cities according to access and adoption to broadband and the socio-economic affects that has had on it. This will help create models of growth which will be studied to then develop a predictive model that will try to forecast the affect of adopting to broadband in cities that do not have internet access yet. The scope is basically two fold, first we aim at a cluster model groups cities into groups that have seen similar growths keeping in mind that the other factors like population, racial composition as the control factors. The model will have to create fixed effects within time series panels. Second, after we have developed a framework and the model, we would like to use the clusters as training datasets to train data on new cities that have not yet transitioned or just planning to apply for broadband programs. The team will be provided with the cluster analysis and would work on the predictive model aspects. The clusters have been benchmarked and will provide information on how to create a model keeping the control factors in mind.

Datasets

The cluster model and data will be provided to the students in a time series format. The basic broadband data will be a part of that data and other features needed for the model will come from federal and state agencies. 

Competencies

Public policy analysis, machine learning, statistics.

Outcomes & Deliverables

Work with sponsor’s front end team to come up with an interactive dashboard and create all data pipelines needed for data integration.

Students

Xiang Li, Xinghong Wang, Chayuth Yongchaicharn, and Chenyang Zhang