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Sequential Monitoring of Changes in Housing Prices

Author

Listed:
  • Lajos Horv'ath

    (Department of Mathematics, University of Utah)

  • Zhenya Liu

    (School of Finance, Renmin University of China
    CERGAM, Aix--Marseille University)

  • Shanglin Lu

    (School of Finance, Renmin University of China)

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.

Suggested Citation

  • Lajos Horv'ath & Zhenya Liu & Shanglin Lu, 2020. "Sequential Monitoring of Changes in Housing Prices," Papers 2002.04101, arXiv.org.
    • Handle: RePEc:arx:papers:2002.04101
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    References listed on IDEAS

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