Land Use Change: A Spatial Multinomial Choice Analysis

Urban decentralization and dispersion trends have led to increased conversion of rural lands in many urban peripheries and exurban regions of the U.S. The growth of the exurban areas has outpaced growth in urban and suburban areas, resulting in growth pressures at the urban-rural fringe. A thorough analysis of land use change patterns and the ability to predict these changes are necessary for the effective design of regional environmental, growth, and development policies. We estimate a multinomial discrete choice model with spatial dependence using parcel-level data from Medina County, Ohio. Accounting for spatial dependence should result in improved statistical inference about land use changes. Our spatial model extends the binary choice “linearized logit” model of Klier and McMillen (2008) to a multinomial setting. A small Monte Carlo simulation indicates that this estimator performs reasonably well. Preliminary results suggest that the location of new urban development is guided by a preference over lower density areas, yet in proximity to current urban development. In addition, we find significant evidence of spatial dependence in land use decisions.