In August, Roberto Gallardo, the Director of the Purdue Center for Regional Development wrote an article that takes a quantitative look at measuring the digital divide. Gallardo has created what he calls the Digital Divide Index (DDI) that allows for the mapping of various socioeconomic factors that can limit households from buying broadband. I obviously want you to read the rest of my blog first, but it’s then worth popping out and playing with the DDI map.
The Digital Divide Index creates a value for every county in the country, with values ranging from 1 to 100, with 100 meaning the highest level of digital divide. The DDI map also plots an infrastructure/adoption (INFA) score and a Socioeconomic score (SE) for every county.
The Infrastructure/Adoption (INFA) score includes five variables that are related to broadband adoption:
- The percentage of homes that are not receiving 100/20 Mbps broadband as measured by the Ookla speed test.
- Percentage of homes without a computer.
- Percentage of homes that don’t have a broadband subscription.
- Download speeds.
- Upload speeds.
The Socioeconomic Score (SE) includes the following five variables:
- Percentage of the population over age 65.
- The percentage of the population age 25 and older that didn’t complete high school.
- The individual poverty rate.
- The percentage of the population with a disability.
- A newly calculated digital inequality or internet income ratio.
The DDI is the first attempt I’ve seen to bring together such a broad range of variables and relate them to the digital divide. Gallardo uses FCC 2020 data in creating the DDI. He also grabbed information from the U.S. Census Bureau’s 5-year American Community Survey, the Bureau of Economic Analysis, Lightcast (formerly known as Economic Modeling Specialists, Inc. or EMSI), and Venture Forward by GoDaddy.
Gallardo assigned values to each county using the many variables. Gallardo then separated counties into three equal groups by the values. The average DDI score for the lowest third of counties was 17.33, while the score of the top third was 36.58. Numerically, this infers that the third of the counties with the most digital divide issues have twice the digital divide issue, on average than counties with the least amount of digital divide issues. This is not a surprising finding, but I’ve never seen it expressed numerically.
The article goes on to create charts that compare the variables between the lowest and highest-ranking counties. For example, the report compared urban and rural. Not surprising, the percentage of counties with the worst DDI scores is almost four times more rural than urban. It turns out that other variables don’t differ between the highest and lowest DDI rankings, such as the percentage of children in the population.
This kind of report is useful for those interested in fixing the digital divide in a community. The report provides some interesting clues about how to find homes that are on the wrong side of the digital divide. For example, households that include somebody with a disability look to be far more likely to be on the wrong side of the digital divide.