Sequential Monitoring of Changes in Housing Prices

Lajos Horv\'ath, Zhenya Liu and Shanglin Lu
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Lajos Horv\'ath: Department of Mathematics, University of Utah
Zhenya Liu: School of Finance, Renmin University of China

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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.

Date: 2020-02
New Economics Papers: this item is included in nep-cna and nep-ecm
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