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

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Author Info
Sonali Das () (LQM, CSIR, Pretoria)
Rangan Gupta () (Department of Economics, University of Pretoria)
Alain Kabundi () (Department of Economics and Econometrics, University of Johannesburg)

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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.

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Publisher Info
Paper provided by University of Pretoria, Department of Economics in its series Working Papers with number 200814.

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Length: 21 pages
Date of creation: Jun 2008
Date of revision:
Handle: RePEc:pre:wpaper:200814

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Related research
Keywords: Dynamic Factor Model; VAR; BVAR; Forecast Accuracy;

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Find related papers by JEL classification:
C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Bayesian Analysis
C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Estimation
C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data
C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Other Model Applications

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References listed on IDEAS
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  1. Forni, Mario & Hallin, Marc & Lippi, Marco & Reichlin, Lucrezia, 2002. "Do Financial Variables Help Forecasting Inflation and Real Activity in the Euro Area?," CEPR Discussion Papers 3146, C.E.P.R. Discussion Papers. [Downloadable!] (restricted)
    Other versions:
  2. Rangan Gupta & Sonali Das, 2008. "Spatial Bayesian Methods of Forecasting House Prices in Six Metropolitan Areas of South Africa," Working Papers 200813, University of Pretoria, Department of Economics.
    Other versions:
  3. Forni, Mario & Reichlin, Lucrezia, 1995. "Let's Get Real: A Dynamic Factor Analytical Approach to Disaggregated Business Cycle," CEPR Discussion Papers 1244, C.E.P.R. Discussion Papers. [Downloadable!] (restricted)
  4. Forni, Mario & Lippi, Marco, 2001. "The Generalized Dynamic Factor Model: Representation Theory," Econometric Theory, Cambridge University Press, vol. 17(06), pages 1113-1141, December. [Downloadable!]
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  5. Dua, Pami & Miller, Stephen M & Smyth, David J, 1999. "Using Leading Indicators to Forecast U.S. Home Sales in a Bayesian Vector Autoregressive Framework," The Journal of Real Estate Finance and Economics, Springer, vol. 18(2), pages 191-205, March. [Downloadable!] (restricted)
  6. Elliott, Graham & Rothenberg, Thomas J & Stock, James H, 1996. "Efficient Tests for an Autoregressive Unit Root," Econometrica, Econometric Society, vol. 64(4), pages 813-36, July. [Downloadable!] (restricted)
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  7. James H. Stock & Mark W. Watson, 1999. "Forecasting Inflation," NBER Working Papers 7023, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
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  8. Rangan Gupta & Alain Kabundi, 2008. "A Dynamic Factor Model for Forecasting Macroeconomic Variables in South Africa," Working Papers 200815, University of Pretoria, Department of Economics. [Downloadable!]
  9. Topel, Robert H & Rosen, Sherwin, 1988. "Housing Investment in the United States," Journal of Political Economy, University of Chicago Press, vol. 96(4), pages 718-40, August. [Downloadable!] (restricted)
  10. Bai, Jushan & Ng, Serena, 2007. "Determining the Number of Primitive Shocks in Factor Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 25, pages 52-60, January. [Downloadable!] (restricted)
  11. Domenico Giannone & Troy Matheson, 2006. "A new core inflation indicator for New Zealand," Reserve Bank of New Zealand Discussion Paper Series DP2006/02, Reserve Bank of New Zealand. [Downloadable!]
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  12. Forni, Mario & Hallin, Marc & Lippi, Marco & Reichlin, Lucrezia, 1999. "The Generalized Dynamic Factor Model: Identification and Estimation," CEPR Discussion Papers 2338, C.E.P.R. Discussion Papers. [Downloadable!] (restricted)
    Other versions:
  13. Ben S. Bernanke & Mark Gertler, 1995. "Inside the Black Box: The Credit Channel of Monetary Policy Transmission," NBER Working Papers 5146, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
    Other versions:
  14. Kwiatkowski, Denis & Phillips, Peter C. B. & Schmidt, Peter & Shin, Yongcheol, 1992. "Testing the null hypothesis of stationarity against the alternative of a unit root : How sure are we that economic time series have a unit root?," Journal of Econometrics, Elsevier, vol. 54(1-3), pages 159-178. [Downloadable!] (restricted)
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  15. Forni, Mario, et al, 2001. "Coincident and Leading Indicators for the Euro Area," Economic Journal, Royal Economic Society, vol. 111(471), pages C62-85, May. [Downloadable!] (restricted)
  16. Cristadoro, Riccardo & Forni, Mario & Reichlin, Lucrezia & Veronese, Giovanni, 2005. "A Core Inflation Indicator for the Euro Area," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 37(3), pages 539-60, June.
  17. Geraint Johnes & Thomas Hyclak, . "House Prices and Regional Labor Markets," Working Papers ec15/93, Department of Economics, University of Lancaster.
  18. Thomas Doan & Robert B. Litterman & Christopher A. Sims, 1983. "Forecasting and Conditional Projection Using Realistic Prior Distributions," NBER Working Papers 1202, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
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  19. Dahlquist, Magnus & Pinkowitz, Lee & Stulz, Ren? M. & Williamson, Rohan, 2003. "Corporate Governance and the Home Bias," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 38(01), pages 87-110, March. [Downloadable!]
  20. Sims, Christopher A & Stock, James H & Watson, Mark W, 1990. "Inference in Linear Time Series Models with Some Unit Roots," Econometrica, Econometric Society, vol. 58(1), pages 113-44, January. [Downloadable!] (restricted)
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