Sequential Monitoring of Changes in Housing Prices
47 Pages Posted: 1 Mar 2020
Date Written: January 30, 2020
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.
Keywords: Sequential Change Point Detection, Weak Dependence, Linear Model, Autoregressive Model, Real Estate Market
JEL Classification: C32, C58, R30
Suggested Citation: Suggested Citation