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A new spatial multiple discrete-continuous modeling approach to land use change analysis.
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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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