IDEAS home Printed from https://ideas.repec.org/
MyIDEAS: Login to save this article

Could we have predicted the recent downturn in the South African housing market?

  • Das, Sonali
  • Gupta, Rangan
  • Kabundi, Alain

This paper develops large-scale Bayesian Vector Autoregressive (BVAR) models, based on 268 quarterly series, for forecasting annualized real house price growth rates for large-, medium- and small-middle-segment housing for the South African economy. Given the in-sample period of 1980:01-2000:04, the large-scale BVARs, estimated under alternative hyperparameter values specifying the priors, are used to forecast real house price growth rates over a 24-quarter out-of-sample horizon of 2001:01-2006:04. The forecast performance of the large-scale BVARs are then compared with classical and Bayesian versions of univariate and multivariate Vector Autoregressive (VAR) models, merely comprising of the real growth rates of the large-, medium- and small-middle-segment houses, and a large-scale Dynamic Factor Model (DFM), which comprises of the same 268 variables included in the large-scale BVARs. Based on the one- to four-quarters-ahead Root Mean Square Errors (RMSEs) over the out-of-sample horizon, we find the large-scale BVARs to not only outperform all the other alternative models, but to also predict the recent downturn in the real house price growth rates for the three categories of the middle-segment-housing over the period of 2003:01-2008:02.

If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.

File URL: http://www.sciencedirect.com/science/article/pii/S1051-1377(09)00019-9
Download Restriction: Full text for ScienceDirect subscribers only

As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.

Article provided by Elsevier in its journal Journal of Housing Economics.

Volume (Year): 18 (2009)
Issue (Month): 4 (December)
Pages: 325-335

as
in new window

Handle: RePEc:eee:jhouse:v:18:y:2009:i:4:p:325-335
Contact details of provider: Web page: http://www.elsevier.com/locate/inca/622881

References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:

as in new window
  1. Anirvan Banerji & Pami Dua & Stephen M. Miller, 2003. "Performance Evaluation of the New Connecticut Leading Employment Index Using Lead Profiles and BVAR Models," Working papers 114, Centre for Development Economics, Delhi School of Economics.
  2. Guangling (Dave) Liu & Rangan Gupta, 2006. "A Small-Scale DSGE Model for Forecasting the South African Economy," Working Papers 200621, University of Pretoria, Department of Economics.
  3. 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.
  4. 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.
  5. 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.
  6. Matteo Iacoviello & Stefano Neri, 2008. "Housing market spillovers : evidence from an estimated DSGE model," Working Paper Research 145, National Bank of Belgium.
  7. Zellner, Arnold, 1986. "A tale of forecasting 1001 series : The Bayesian knight strikes again," International Journal of Forecasting, Elsevier, vol. 2(4), pages 491-494.
  8. Sims, Christopher A, 1980. "Macroeconomics and Reality," Econometrica, Econometric Society, vol. 48(1), pages 1-48, January.
  9. Rangan Gupta & Moses m. Sichei, 2006. "A Bvar Model For The South African Economy," South African Journal of Economics, Economic Society of South Africa, vol. 74(3), pages 391-409, 09.
  10. Rangan Gupta, 2006. "FORECASTING THE SOUTH AFRICAN ECONOMY WITH VARs AND VECMs," South African Journal of Economics, Economic Society of South Africa, vol. 74(4), pages 611-628, December.
  11. Ben S. Bernanke & Mark Gertler, 1995. "Inside the Black Box: The Credit Channel of Monetary Policy Transmission," Journal of Economic Perspectives, American Economic Association, vol. 9(4), pages 27-48, Fall.
  12. Forni M. & Hallin M., 2003. "The Generalized Dynamic Factor Model: One-Sided Estimation and Forecasting," Computing in Economics and Finance 2003 143, Society for Computational Economics.
  13. James H. Stock & Mark W.Watson, 2003. "Forecasting Output and Inflation: The Role of Asset Prices," Journal of Economic Literature, American Economic Association, vol. 41(3), pages 788-829, September.
  14. Richard M. Todd, 1984. "Improving economic forecasting with Bayesian vector autoregression," Quarterly Review, Federal Reserve Bank of Minneapolis, issue Fall.
  15. Dua, Pami & Miller, Stephen M, 1996. "Forecasting Connecticut Home Sales in a BVAR Framework Using Coincident and Leading Indexes," The Journal of Real Estate Finance and Economics, Springer, vol. 13(3), pages 219-35, November.
  16. 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.
  17. Jushan Bai & Serena Ng, 2002. "Determining the Number of Factors in Approximate Factor Models," Econometrica, Econometric Society, vol. 70(1), pages 191-221, January.
  18. Forni, Mario & Hallin, Marc & Lippi, Marco & Reichlin, Lucrezia, 2003. "Do financial variables help forecasting inflation and real activity in the euro area?," Journal of Monetary Economics, Elsevier, vol. 50(6), pages 1243-1255, September.
  19. 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.
  20. Rangan Gupta, 2009. "Bayesian Methods Of Forecasting Inventory Investment," South African Journal of Economics, Economic Society of South Africa, vol. 77(1), pages 113-126, 03.
  21. 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.
  22. Sonali Das & Rangan Gupta & Alain Kabundi, 2008. "Is a DFM Well Suited for Forecasting Regional House Price Inflation?," Working Papers 85, Economic Research Southern Africa.
  23. Carlos Vargas-Silva, 2008. "The effect of monetary policy on housing: a factor-augmented vector autoregression (FAVAR) approach," Applied Economics Letters, Taylor & Francis Journals, vol. 15(10), pages 749-752.
  24. Thomas Doan & Robert B. Litterman & Christopher A. Sims, 1986. "Forecasting and conditional projection using realistic prior distribution," Staff Report 93, Federal Reserve Bank of Minneapolis.
  25. Marco Del Negro, 2001. "Turn, turn, turn: Predicting turning points in economic activity," Economic Review, Federal Reserve Bank of Atlanta, issue Q2, pages 1-12.
  26. Philippe Burger & Lizelle janse Van rensburg, 2008. "Metropolitan House Prices In South Africa: Do They Converge?," South African Journal of Economics, Economic Society of South Africa, vol. 76(2), pages 291-297, 06.
  27. 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.
  28. Thomas Hyclak & Geraint Johnes, 1999. "original: House prices and regional labor markets," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 33(1), pages 33-49.
  29. Rapach, David E. & Strauss, Jack K., 2009. "Differences in housing price forecastability across US states," International Journal of Forecasting, Elsevier, vol. 25(2), pages 351-372.
  30. Lucas, Robert Jr, 1976. "Econometric policy evaluation: A critique," Carnegie-Rochester Conference Series on Public Policy, Elsevier, vol. 1(1), pages 19-46, January.
  31. Spencer, David E., 1993. "Developing a Bayesian vector autoregression forecasting model," International Journal of Forecasting, Elsevier, vol. 9(3), pages 407-421, November.
Full references (including those not matched with items on IDEAS)

This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

When requesting a correction, please mention this item's handle: RePEc:eee:jhouse:v:18:y:2009:i:4:p:325-335. See general information about how to correct material in RePEc.

For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Zhang, Lei)

If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

If references are entirely missing, you can add them using this form.

If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.

If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.

Please note that corrections may take a couple of weeks to filter through the various RePEc services.

This information is provided to you by IDEAS at the Research Division of the Federal Reserve Bank of St. Louis using RePEc data.