What we can learn from selected, unmatched data: Measuring internet inequality in Chicago

By integrating a big dataset of Internet Speedtest (R) measurements from Ookla (R) with data on household in-comes from the American Community Survey (ACS), we attempt to measure Internet speeds across income tiers. In the Ookla data, each measurement is technically rigorous but the sample frame is unknown. The ACS provides necessary information on income and Internet access from a known sample frame. Our likelihood combines these data and endogenizes selection effects to identify Internet speed distributions by income tier. We credibly identify the speed distribution for middle and high-income households. However, because the participation rate of low-income households in the Speedtest data is so limited, the speed estimates for these households are not identified.

Automated summary

This study aims to measure internet speeds across income tiers by integrating data from Internet Speedtest measurements and household income data. The speed distribution for middle and high-income households is reliably identified. However, because of the limited participation rate of low-income households, the speed estimates for these households are not determined accurately.