Boom-bust cycles and the forecasting performance of linear and non-linear models of house prices
Miles, William
Miles, William
Citations
Altmetric:
Authors
Other Names
Location
Time Period
Advisors
Original Date
Digitization Date
Issue Date
2008-04
Type
Article
Genre
Keywords
Bubbles,Forecasting models,Generalized autoregressive model|Nonlinear techniques
Subjects (LCSH)
Citation
Miles, William. 2008. Boom-bust cycles and the forecasting performance of linear and non-linear models of house prices. Journal of Real Estate Finance and Economics, vol. 36:no. 3:pp 249-264
Abstract
The tremendous rise in house prices over the last decade has been both a national and a global phenomenon. The growth of secondary mortgage holdings and the increased impact of house prices on consumption and other components of economic activity imply ever-greater importance for accurate forecasts of home price changes. Given the boom-bust nature of housing markets, nonlinear techniques seem intuitively very well suited to forecasting prices, and better, for volatile markets, than linear models which impose symmetry of adjustment in both rising and falling price periods. Accordingly, Crawford and Fratantoni (Real Estate Economics 31:223-243, 2003) apply a Markov-switching model to U.S. home prices, and compare the performance with autoregressive-moving average (ARMA) and generalized autoregressive conditional heteroscedastic (GARCH) models. While the switching model shows great promise with excellent in-sample fit, its out-of-sample forecasts are generally inferior to more standard forecasting techniques. Since these results were published, some researchers have discovered that the Markov-switching model is particularly ill-suited for forecasting. We thus consider other non-linear models besides the Markov switching, and after evaluating alternatives, employ the generalized autoregressive (GAR) model. We find the GAR does a better job at out-of-sample forecasting than ARMA and GARCH models in many cases, especially in those markets traditionally associated with high home-price volatility.
Table of Contents
Description
Click on the DOI link to access the article (may not be free).
Publisher
Springer
Journal
Book Title
Series
Journal of Real Estate Finance and Economics;v.36:no.3
Digital Collection
Finding Aid URL
Use and Reproduction
Archival Collection
PubMed ID
DOI
ISSN
0895-5638