Broadband achievement index: Moving beyond availability

摘要

High-speed access to the Internet enhances economic prosperity, social development and global competitiveness. Significant progress has been made in broadband deployment in the last decade. Nevertheless, there are increasing gaps in broadband adoption, use and speed between, as well as within, the states. Federal and state legislators and regulators currently use a number of indicators such as adoption, availability and speed to track states' progress in broadband diffusion in order to design appropriate policy responses. Single indicators, however, when analyzed individually, fall short of capturing multi-dimensional aspects of broadband diffusion and, thus, do not provide an integrated and easily comprehensible picture of states' advancement. To monitor states' overall progress it is useful to aggregate various indicators into a composite index that could measure the overall extent of broadband diffusion. A composite index can also provide with an important benchmark for designing policies to improve states' overall performance. This paper offers a flexible framework for benchmarking states' achievement in broadband diffusion by proposing a composite Broadband Achievement Index (BAI). The index combines several key performance indicators: broadband availability, adoption, competition, speed and the dispersion of broadband adoption within the states utilizing FCC's Form 477 data and the recently collected census block level broadband availability data from NTIA. The purpose is to provide a more comprehensive picture of where the states stand in their evolution toward high-performance America by measuring each state's current broadband achievement relative to other states and providing an important benchmark for assessing state-specific needs. The indicators are combined using the Benefit of the Doubt (BOD) methodology (Cherchye, Moesen, & Van Puyenbroeck, 2004). The methodology is founded on the premise that, absent a consensus on social policy priorities, that are, on which indicators are more important and should be given higher weights in the index, each state is granted leeway for deciding how to weigh its own indicators and the most favorable weights for indicators are determined for each state. A good relative performance in a particular dimension is seen as revealed evidence of setting high state policy priority to that indicator, when each state's specific policy priorities are unknown. Additionally, the Second Order Stochastic Dominance (SOSD) methodology is used to compare the dispersion of adoption in the states. Using SOSD the states are ranked under the assumption that proportionally higher and more equally distributed adoption rates are better.