A Dynamic Model of Community Growth in a Metropolitan Area

A two-tiered dynamic model for allocating residential housing growth both among townships in a metropolitan area and among zones within a township is developed. A metropolitan-level model having data aggregated up to the township level is proposed to explain the effects of metropolitan-level controls (such as employment location and accessibility) and township controls (such as the presence of land-use regulations) on residential growth in each township. A township-level model is proposed to accept growth forecasts generated by the metropolitan model and spatially and temporally allocate this growth within a given township. A case-study metropolitan area and one township within it are chosen and a data base is developed, using published and raw data sources. Multiple linear regression analysis is used to calibrate and validate these models. Metropolitan-model results indicate good model fit (R2 = 0.835, overall model F value = 15.9) with accessibility to employment being the dominant explanatory independent variable with a strong positive correlation (partial R2 = 0.71) to the rate of housing growth. Other independent variables in the model include the property tax rate in the analysis zone (negative correlation), housing value (weak positive correlation), and land-use controls (weak negative correlation). These results support a theory of metropolitan growth that says accessibility to employment weighted by available land for development, availability of existing residential development, and low tax rates promote residential growth. A significant factor is that the presence or absence of land-use controls does not meaningfully affect growth.