A new spatial multiple discrete-continuous modeling approach to land use change analysis.
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2013-09-01
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Abstract:This report formulates a multiple discrete-continuous probit (MDCP) land-use model within a
spatially explicit economic structural framework for land-use change decisions. The spatial
MDCP model is capable of predicting both the type and intensity of urban development patterns
over large geographic areas, while also explicitly acknowledging geographic proximity-based
spatial dependencies in these patterns. At a methodological level, the report focuses on
specifying and estimating a spatial MDCP model that allows the dependent variable to exist in
multiple discrete states with an intensity associated with each discrete state. The formulation
also accommodates spatial dependencies, as well as spatial heterogeneity and heteroscedasticity,
in the dependent variable, and should be applicable in a wide variety of fields where social and
spatial dependencies between decision agents (or observation units) lead to spillover effects in
multiple discrete-continuous choices (or states). A simulation exercise is undertaken to evaluate
the ability of the proposed maximum approximate composite marginal likelihood (MACML)
approach to recover parameters from a cross-sectional spatial MDCP model. The results show
that the MACML approach does well in recovering parameters. An empirical demonstration of
the approach is undertaken using the city of Austin parcel level land use data.
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