A spatial panel ordered-response model with application to the analysis of urban land-use development intensity patterns
A spatial panel ordered-response model with application to the analysis of urban land-use development intensity patterns
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DOI：
10.1007/s10109-012-0165-0
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发表时间：
2013
影响因子：
2.9
通讯作者：
Nazneen Ferdous;C. Bhat
中科院分区：
文献类型：
--
作者：
Nazneen Ferdous;C. Bhat
本文提出并估计了一个带有时间自回归误差项的空间面板有序响应概率单位模型，用于分析城市土地开发强度水平随时间的变化。这样的模型结构保持了土地所有者的决定（未观察到的分析）和土地开发强度水平（观察到的分析）之间的密切联系，并容纳土地所有者之间的空间互动，导致空间溢出效应。此外，模型结构还考虑了空间异质性和空间异方差性。由此产生的模型估计使用复合边际似然（CML）的方法，不需要任何模拟机器，可以应用于任何规模的数据集。模拟实验表明，CML方法恢复模型参数非常好，即使在存在高的空间和时间依赖性。此外，模拟结果表明，忽略空间依赖性和空间异质性时，实际上都存在将导致参数估计的偏差。一个示范练习适用于所提出的模型，以检查城市土地开发强度水平，从得克萨斯州奥斯汀市的地块级数据。
This paper proposes and estimates a spatial panel ordered-response probit model with temporal autoregressive error terms to analyze changes in urban land development intensity levels over time. Such a model structure maintains a close linkage between the land owner’s decision (unobserved to the analyst) and the land development intensity level (observed by the analyst) and accommodates spatial interactions between land owners that lead to spatial spillover effects. In addition, the model structure incorporates spatial heterogeneity as well as spatial heteroscedasticity. The resulting model is estimated using a composite marginal likelihood (CML) approach that does not require any simulation machinery and that can be applied to data sets of any size. A simulation exercise indicates that the CML approach recovers the model parameters very well, even in the presence of high spatial and temporal dependence. In addition, the simulation results demonstrate that ignoring spatial dependency and spatial heterogeneity when both are actually present will lead to bias in parameter estimation. A demonstration exercise applies the proposed model to examine urban land development intensity levels using parcel-level data from Austin, Texas.