The Out-of-Sample Forecasting Performance of Non-Linear Models of Regional Housing Prices in the US
55 Pages Posted: 31 Aug 2012 Last revised: 18 Mar 2015
Date Written: August 30, 2012
This paper provides out-of-sample forecasts of linear and non-linear models of US and Census regions housing prices. The forecasts include the traditional point forecasts, but also include interval and density forecasts of the housing price distributions. The non-linear smooth-transition autoregressive model outperforms the linear autoregressive model in point forecasts at longer horizons, but the linear autoregressive model dominates the non-linear smooth-transition autoregressive model at short horizons. In addition, we generally do not find major differences in performance for the interval and density forecasts between the linear and non-linear models. Finally, in a dynamic 25-step ex-ante and interval forecasting design, we, once again, do not find major differences between the linear and nonlinear models.
Keywords: Forecasting, Linear and non-linear models, US and Census housing price indexes
JEL Classification: C32, R31
Suggested Citation: Suggested Citation