Evaluating Alternative Methods of Forecasting House Prices: A Post-Crisis Reassessment

45 Pages Posted: 16 Nov 2010

Date Written: November 15, 2010

Abstract

This paper compares the performance of different forecasting models of California house prices. Multivariate, theory-driven models are able to outperform atheoretical time series models across a battery of forecast comparison measures. Error correction models were best able to predict the turning point in the housing market, whereas univariate models were not. Similarly, even after the turning point occurred, error correction models were still able to outperform univariate models based on MSFE, bias, and forecast encompassing statistics and tests. These results highlight the importance of incorporating theoretical economic relationships into empirical forecasting models.

Keywords: house prices, forecasting, forecast comparison, forecast encompassing

JEL Classification: C52, C53, E37

Suggested Citation

Larson, William D., Evaluating Alternative Methods of Forecasting House Prices: A Post-Crisis Reassessment (November 15, 2010). Available at SSRN: https://ssrn.com/abstract=1709647 or http://dx.doi.org/10.2139/ssrn.1709647

William D. Larson (Contact Author)

Federal Housing Finance Agency ( email )

400 7th Street SW
Washington, DC 20552
United States

Do you have a job opening that you would like to promote on SSRN?

Paper statistics

Downloads
125
Abstract Views
873
rank
290,244
PlumX Metrics