Area-Based Models of Highway Growth

Abstract

Empirical data and statistical models are employed to predict where new highway routes are most likely to be located. The land use, population distribution, and highway network for the Twin Cities’ Metro Area from 1958 to 1990 are used. Binary logit models estimate the likelihood a particular cell will see the construction of divided highways and secondary highways. The results show that the area’s land-use attributes and population density levels do significantly affect the likelihood of adding new highway routes.