Forecasting the US real house price index: Structural and non-structural models with and without fundamentals
Rangan Gupta,
Alain Kabundi () and
Stephen Miller
Economic Modelling, 2011, vol. 28, issue 4, 2013-2021
Abstract:
We employ a 10-variable dynamic structural general equilibrium model to forecast the US real house price index as well as its downturn in 2006:Q2. We also examine various Bayesian and classical time-series models in our forecasting exercise to compare to the dynamic stochastic general equilibrium model, estimated using Bayesian methods. In addition to standard vector-autoregressive and Bayesian vector autoregressive models, we also include the information content of either 10 or 120 quarterly series in some models to capture the influence of fundamentals. We consider two approaches for including information from large data sets -- extracting common factors (principle components) in factor-augmented vector autoregressive or Bayesian factor-augmented vector autoregressive models as well as Bayesian shrinkage in a large-scale Bayesian vector autoregressive model. We compare the out-of-sample forecast performance of the alternative models, using the average root mean squared error for the forecasts. We find that the small-scale Bayesian-shrinkage model (10 variables) outperforms the other models, including the large-scale Bayesian-shrinkage model (120 variables). In addition, when we use simple average forecast combinations, the combination forecast using the 10 best atheoretical models produces the minimum RMSEs compared to each of the individual models, followed closely by the combination forecast using the 10 atheoretical models and the DSGE model. Finally, we use each model to forecast the downturn point in 2006:Q2, using the estimated model through 2005:Q2. Only the dynamic stochastic general equilibrium model actually forecasts a downturn with any accuracy, suggesting that forward-looking microfounded dynamic stochastic general equilibrium models of the housing market may prove crucial in forecasting turning points.
Keywords: US; House; prices; Forecasting; DSGE; models; Factor; augmented; models; Large-scale; BVAR; models (search for similar items in EconPapers)
Date: 2011
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (41)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0264999311001040
Full text for ScienceDirect subscribers only
Related works:
Working Paper: Forecasting the US Real House Price Index: Structural and Non-Structural Models with and without Fundamentals (2010) 
Working Paper: Forecasting the US Real House Price Index: Structural and Non-Structural Models with and without Fundamentals (2009)
Working Paper: Forecasting the US Real House Price Index: Structural and Non-Structural Models with and without Fundamentals (2009) 
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:ecmode:v:28:y:2011:i:4:p:2013-2021
Access Statistics for this article
Economic Modelling is currently edited by S. Hall and P. Pauly
More articles in Economic Modelling from Elsevier
Bibliographic data for series maintained by Catherine Liu ().