Is a DFM Well Suited for Forecasting Regional House Price Inflation?
AbstractThis paper uses the Dynamic Factor Model (DFM) framework, which accommodates a large cross-section of macroeconomic time series for forecasting regional house price inflation. As a case study, we use data on house price inflation for five metropolitan areas of South Africa. The DFM used in this study contains 282 quarterly series observed over the period 1980Q1-2006Q4. The results, based on the Mean Absolute Errors of one- to four-quarters-ahead out of sample forecasts over the period of 2001Q1 to 2006Q4, indicate that, in majority of the cases, the DFM outperforms the VARs, both classical and Bayesian, with the latter incorporating both spatial and non-spatial models. Our results, thus, indicate the blessing of dimensionality.
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Bibliographic InfoPaper provided by Economic Research Southern Africa in its series Working Papers with number 85.
Date of creation: 2008
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Dynamic Factor Model; VAR; BVAR; Forecast Accuracy;
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
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- Rangan Gupta & Marius Jurgilas & Alain Kabundi, 2009.
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