ABSTRACT

The paper proposes a Bayesian multinomial logit model to analyse spatial patterns of urban expansion. The specification assumes that the log-odds of each class follow a spatial autoregressive process. Using recent advances in Bayesian computing, our model allows for a computationally efficient treatment of the spatial multinomial logit model. This allows us to assess spillovers between regions and across land-use classes. In a series of Monte Carlo studies, we benchmark our model against other competing specifications. The paper also showcases the performance of the proposed specification using European regional data. Our results indicate that spatial dependence plays a key role in the land-sealing process of cropland and grassland. Moreover, we uncover land-sealing spillovers across multiple classes of arable land.

摘要

本文提出了贝叶斯多项logit模型来分析城市扩张的空间格局。该规范假设每个类的对数几率遵循空间自回归过程。利用贝叶斯计算的最新进展，我们的模型允许对空间多项式 logit 模型进行计算有效的处理。这使我们能够评估区域之间和跨土地利用类别的溢出效应。在一系列蒙特卡洛研究中，我们将我们的模型与其他竞争规范进行了基准测试。该论文还展示了使用欧洲区域数据提出的规范的性能。我们的研究结果表明，空间依赖性在农田和草地的封地过程中起着关键作用。此外，我们还发现了多类耕地的封地溢出效应。