Forecasting Real Us House Price: Principal Components Versus Bayesian Regressions
AbstractThis paper analyzes the ability of principal component regressions and Bayesian regression methods under Gaussian and double-exponential prior in forecasting the real house price of the United States (US), based on a monthly dataset of 112 macroeconomic variables. Using an in-sample period of 1992:01 to 2000:12, Bayesian regressions are used to forecast real US house prices at the twelve-months-ahead forecast horizon over the out-of-sample period of 2001:01 to 2004:10. In terms of the Mean Square Forecast Errors (MSFEs), our results indicate that a principal component regression with only one factor is best-suited for forecasting the real US house price. Amongst the Bayesian models, the regression based on the double exponential prior outperforms the model with Gaussian assumptions.
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Bibliographic InfoPaper provided by University of Pretoria, Department of Economics in its series Working Papers with number 200907.
Length: 15 pages
Date of creation: Feb 2009
Date of revision:
Bayesian Regressions; Principal Components; Large-Cross Sections;
Find related papers by JEL classification:
- C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
- C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
- C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
- C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
This paper has been announced in the following NEP Reports:
- NEP-ALL-2009-02-28 (All new papers)
- NEP-ECM-2009-02-28 (Econometrics)
- NEP-FOR-2009-02-28 (Forecasting)
- NEP-URE-2009-02-28 (Urban & Real Estate Economics)
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- Rangan Gupta & Alain Kabundi & Stephen M. Miller, 2009.
"Forecasting the US Real House Price Index: Structural and Non-Structural Models with and without Fundamentals,"
200927, University of Pretoria, Department of Economics.
- Gupta, Rangan & Kabundi, Alain & Miller, Stephen M., 2011. "Forecasting the US real house price index: Structural and non-structural models with and without fundamentals," Economic Modelling, Elsevier, vol. 28(4), pages 2013-2021, July.
- Rangan Gupta & Alain Kabundi & Stephen M. Miller, 2009. "Forecasting the US Real House Price Index: Structural and Non-Structural Models with and without Fundamentals," Working papers 2009-42, University of Connecticut, Department of Economics.
- Rangan Gupta & Alan Kabundi & Stephen M. Miller, 2009. "Forecasting the US Real House Price Index: Structural and Non-Structural Models with and without Fundamentals," Working Papers 1001, University of Nevada, Las Vegas , Department of Economics.
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