Measuring and interpreting urban externalities in real-estate data : a Spatio-Temporal Difference-in-Differences (STDID) estimator
Measuring and interpreting urban externalities in real-estate data : a Spatio-Temporal Difference-in-Differences (STDID) estimator
复制标题
衡量和解释房地产数据中的城市外部性：时空双重差分 (STDID) 估计器
DOI：
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发表时间：
2017
期刊：
影响因子：
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通讯作者：
F. D. Rosiers
中科院分区：
文献类型：
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作者：
Jean Dubé;D. Legros;M. Thériault;F. D. Rosiers
现在，如果不考虑捕获可能的空间效果的显式规范，就几乎不可能处理空间数据。空间计量经济学模型的一个重要特征是将边际效应分解为空间溢出效应和空间外部性。解释空间计量经济学模型的进展现在已经扩展到空间面板案例。然而，几乎没有考虑到使用随时间汇集的空间数据来解释模型的可能性。本文提出了一种时空差分(STDID)估计器来衡量城市外部性的影响，如通过房地产价格揭示的交通基础设施。基于对蒙特利尔郊区通勤列车新发展的实证应用，本文展示了这些命题如何帮助我们更好地理解和评估公共交通系统的变化。
It is now almost impossible to deal with spatial data without considering some explicit specification that captures possible spatial effects. One valuable feature of spatial econometrics models is their decomposition of marginal effects into spatial spillover effect and spatial externalities. Progress in interpreting spatial econometrics models has now been extended to the spatial-panel case. However, little consideration has been given to the possible interpretation of models using spatial data pooled over time. This paper proposes a spatio-temporal difference-in-differences (STDID) estimator to measure the effect of urban externalities, such as transport infrastructures, as revealed through real-estate prices. Based on an empirical application for a new development of commuter trains in the Montreal suburbs, this paper shows how such propositions can help us to better understand and evaluate changes in mass transit systems.