Identifying peer states for transportation system evaluation &; policy analyses

The majority of comparisons between state transportation systems do not control for characteristics that may vary greatly between states (e.g., vehicle miles traveled). A shortcoming of such analyses is that a state’s individual characteristics can be highly influential in determining how transportation policy is set and funds are spent. The purpose of this paper is to extend previous efforts to create groups of similar peer states by developing a new methodological framework that incorporates demographic, temporal, and locational variability into the peer group delineations. We collected historical data for 42 variables on transportation infrastructure, population, economy, growth, topography and weather. To examine trends before and after the passage of ISTEA we gathered data over two time periods: 1985 through 1990 and 1995 through 2000. Using principal components analysis (PCA) we reduced variables into seven components, and then statistically clustered states into peer groups for each time period based on the components and the remaining variables. We identified a range of cluster solutions and demonstrate how cluster statistics help to describe the contextual basis behind the peer grouping. The results of this study are to provide government agencies, researchers and the public with a systematic methodological framework for identifying peer states that reflect similar attributes contributing to the development and maintenance of state transportation systems.

Debbie A. Niemeier (Corresponding author)Email: