  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.
