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Is a DFM Well-Suited in Forecasting Regional House Price Inflation?

Author

Listed:
  • Sonali Das

    (LQM, CSIR, Pretoria)

  • Rangan Gupta

    (Department of Economics, University of Pretoria)

  • Alain Kabundi

    (Department of Economics and Econometrics, University of Johannesburg)

Abstract

This 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.

Suggested Citation

  • Sonali Das & Rangan Gupta & Alain Kabundi, 2008. "Is a DFM Well-Suited in Forecasting Regional House Price Inflation?," Working Papers 200814, University of Pretoria, Department of Economics.
    • Handle: RePEc:pre:wpaper:200814
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    Citations

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    Cited by:

    1. Gupta, Rangan & Jurgilas, Marius & Kabundi, Alain, 2010. "The effect of monetary policy on real house price growth in South Africa: A factor-augmented vector autoregression (FAVAR) approach," Economic Modelling, Elsevier, vol. 27(1), pages 315-323, January.
    2. Das, Sonali & Gupta, Rangan & Kabundi, Alain, 2009. "Could we have predicted the recent downturn in the South African housing market?," Journal of Housing Economics, Elsevier, vol. 18(4), pages 325-335, December.

    More about this item

    Keywords

    Dynamic Factor Model; VAR; BVAR; Forecast Accuracy;
    All these keywords.

    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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