Modeling Urban Growth at a Micro Level

Abstract

In this paper, the historical trend of urban growth and the associated drivers were examined through econometric analysis for the rapidly growing Grafton area in the State of Wisconsin. Specifically, panel data analysis was carried out to examine the drivers of urban growth such as demographic factors, location of jobs, travel time, housing types, property values, etc. Results reveal that panel data analysis, particularly the random effects model, was successful in analyzing the drivers of urban growth at the census block group level. This study found that population, local jobs, household income, and house price were positively associated with urban growth. The study also found that urban growth in the study area is not decided by the access to the nearest central city, but other factors, such as the rural atmosphere of the region, local jobs, and emerging centers of employment opportunities, have significant influences on urban development.