Sequential Monitoring of Changes in Housing Prices

Lajos Horváth, Zhenya Liu, Shan Lu
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Abstract

We propose a sequential monitoring scheme to find structural breaks in real estate markets. The changes in the real estate prices are modeled by a combination of linear and autoregressive terms. The monitoring scheme is based on a detector and a suitably chosen boundary function. If the detector crosses the boundary function, a structural break is detected. We provide the asymptotics for the procedure under the stability null hypothesis and the stopping time under the change point alternative. Monte Carlo simulation is used to show the size and the power of our method under several conditions. We study the real estate markets in Boston, Los Angeles and at the national U.S. level. We find structural breaks in the markets, and we segment the data into stationary segments. It is observed that the autoregressive parameter is increasing but stays below 1.
房价变化的连续监测
我们提出了一个顺序监测方案,以发现房地产市场的结构性断裂。房地产价格的变化是由线性和自回归的组合项建模。监测方案是基于一个检测器和一个适当选择的边界函数。如果检测器越过边界函数,则检测到结构断裂。给出了该过程在稳定性零假设下的渐近性和在变点备选条件下的停止时间。通过蒙特卡罗仿真验证了该方法在不同条件下的大小和有效性。我们研究波士顿、洛杉矶和美国全国的房地产市场。我们发现市场的结构性断裂,我们把数据分成固定的部分。观察到自回归参数在增大,但保持在1以下。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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