EDITOR’S NOTE: The Daily Yonder loves data. So we’re pleased to introduce a new county-level index that combines technical and socio-economic factors to measure the “digital divide.” We’ll have more stories in the future using this index to look at rural America’s digital-access challenges. In this article, the index’s creator, Roberto Gallardo, explains the numbers and what communities might do with them. If that’s not wonky enough for you, the complete data set by state is available through the Intelligent Community Institute.


Being on the wrong side of the digital divide is the equivalent of not knowing how to read or write 100 years ago. As more and more services—searching/applying for jobs, professional development, school homework, social media, online banking, etc.—exist only in the digital world, not having access or not knowing how to use the technology is leaving people and communities behind.

Public Policy 101 says that a problem first needs to be defined before potential solutions are even discussed. For this reason, the county-level digital divide index was calculated. Although the digital divide is a much more complex concept than an index score, the objective of the index is to serve as a descriptive and pragmatic tool for policymakers and residents. More importantly, it should be used to jumpstart critical conversations around this issue.

The digital divide index (DDI) consists of two components using 2014 data and will be updated annually. It ranges from zero to 100, where a higher number denotes a larger digital divide.

Note that only fixed broadband was used to calculate the index. Mobile wireless was not included primarily because data caps and small screen sizes don’t necessarily help reducing the digital divide.

The first component groups three variables related to broadband availability/adoption (INFA): percent population with no access to fixed broadband 25 Mbps download and 3 Mbps upload (25/3), number of residential broadband connections, and average advertised download and upload speeds.

The second component, groups three socioeconomic characteristics associated with low technology adoption (SE): percent population age 65 and over, percent population 25 and over with less than high school education, and individual poverty rate.

The overall DDI score includes both broadband availability/adoption and socioeconomic characteristics.

If a particular county scored significantly higher in the INFA component compared to the SE score, it implies investments need to be made to improve broadband infrastructure in that particular county. If on the other hand, the SE score is significantly higher compared to the INFA score, more efforts need to be made on digital literacy/inclusion as well as technology relevance.

Figure 1 shows the INFA score divided into four equal groups. The darker color denotes a higher INFA score. Notice the majority of counties in Arkansas, Mississippi and Texas (other than urban counties) are mostly in the higher quartile while the majority of counties in the East and West coasts, North Dakota, and Florida are in the lowest quartile.

Figure 1. INFA Score by Quartiles


Figure 2 shows the SE score by quartiles as well. Notice that the dark color pattern is slightly different than the one seen in the INFA map. This implies that these two different components of the digital divide affect different counties. Counties in Eastern Oregon ranked in the highest quartile as did southeast Georgia and eastern Kentucky.

Figure 2. SE Score by Quartiles


Lastly, Figure 3 (at the top of this article) shows the overall digital divide index (DDI) scores that include INFA and SE scores. These were also divided into four equal groups where the darker color denotes the largest digital divide.

Table 1 (below) shows the top 10 noncore or more rural counties with the highest digital divide as measured by this index. (“Noncore” counties are the most rural. They aren’t in a statistical area with a large or small city, and they have no city of 10,000 residents or more.) The top noncore spot was held by Humphreys County in Mississippi. This particular county scored 86 on the SE component, 91 in the INFA component and 99.8 in the overall DDI score. It had a poverty rate of 39% (more than twice as high as the national average), about 34% of population 25 and over with less than high school (more than twice as high as the national average), and 14% of total population age 65 and over (below the national average).

Regarding broadband availability/adoption, 100% of Humphrey’s County population did not have access to 25/3 fixed broadband and only 20 to 40% of its households had a fixed broadband residential connection of at least 3 Mbps download and 768 Kbps upload. It had an average advertised download speed of 9.6 Mbps, almost three times slower than the 25 Mbps cutoff speed to be even considered broadband and an average advertised upload speed of 1.9 Mbps, below the 3 Mbps cutoff speed.

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In other words, not only are broadband investments needed in Humphreys County to upgrade the existing Internet connectivity, but due to its high poverty rate and those with less than high school, digital literacy and technology relevance efforts are also needed.

Figure 4 shows the average SE, INFA, and DDI scores for the U.S., metropolitan, micropolitan, and noncore counties. Not surprising, noncore or more rural counties had the highest average scores for both components and the overall digital divide score. Important to note is that the highest average score was INFA for the U.S. implying infrastructure investments are required.

Figure 4. Average SE, INFA, and DDI Scores by County Type

Average SE, INFA, and DDI Scores by County Type

The digital divide is a serious and complex issue. If emphasis is placed only in infrastructure, a large component of the divide is overlooked. For those with a higher digital divide, unfortunately primarily rural, efforts on both infrastructure and digital literacy are required. Hopefully this index jumpstarts needed conversations to address this 21st century issue.

To access the full report and download the dataset by state, please go to http://ici.msucares.com/ddi

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